{"task_type": "generation", "dataset": "semeval-2015", "input": ["Judging from previous posts this used to be a good place, but not any longer."], "output": "[['place', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We, there were four of us, arrived at noon - the place was empty - and the staff acted like we were imposing on them and they were very rude."], "output": "[['staff', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They never brought us complimentary noodles, ignored repeated requests for sugar, and threw our dishes on the table."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was lousy - too sweet or too salty and the portions tiny."], "output": "[['food', 'food quality', 'negative'], ['portions', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["After all that, they complained to me about the small tip."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Avoid this place!"], "output": "[['place', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have eaten at Saul, many times, the food is always consistently, outrageously good."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Saul is the best restaurant on Smith Street and in Brooklyn."], "output": "[['Saul', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The duck confit is always amazing and the foie gras terrine with figs was out of this world."], "output": "[['foie gras terrine with figs', 'food quality', 'positive'], ['duck confit', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wine list is interesting and has many good values."], "output": "[['wine list', 'drinks style_options', 'positive'], ['wine list', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["For the price, you cannot eat this well in Manhattan."], "output": "[['NULL', 'restaurant prices', 'positive'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I was very disappointed with this restaurant."], "output": "[['restaurant', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ive asked a cart attendant for a lotus leaf wrapped rice and she replied back rice and just walked away."], "output": "[['cart attendant', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had to ask her three times before she finally came back with the dish Ive requested."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was okay, nothing great."], "output": "[['Food', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Chow fun was dry; pork shu mai was more than usually greasy and had to share a table with loud and rude family. "], "output": "[['Chow fun', 'food quality', 'negative'], ['pork shu mai', 'food quality', 'negative'], ['NULL', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I/we will never go back to this place again."], "output": "[['place', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Went on a 3 day oyster binge, with Fish bringing up the closing, and I am so glad this was the place it O trip ended, because it was so great!"], "output": "[['Fish', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was devine, oysters where a sensual as they come, and the price can't be beat!!!"], "output": "[['Service', 'service general', 'positive'], ['oysters', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You can't go wrong here."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Every time in New York I make it a point to visit Restaurant Saul on Smith Street."], "output": "[['Restaurant Saul', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everything is always cooked to perfection, the service is excellent, the decor cool and understated."], "output": "[['NULL', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['decor', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had the duck breast special on my last visit and it was incredible."], "output": "[['duck breast special', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Can't wait wait for my next visit."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And I hate to say this but I doubt I'll ever go back. "], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is very average...the Thai fusion stuff is a bit too sweet, every thing they serve is too sweet here."], "output": "[['food', 'food quality', 'negative'], ['Thai fusion stuff', 'food quality', 'negative'], ['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The only thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree."], "output": "[['Grilled Chicken special with Edamame Puree', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had never had Edamame pureed before but I thought it was innovative and tasty (could've used a bit more salt)."], "output": "[['Edamame pureed', 'food quality', 'positive'], ['Edamame pureed', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The decor is night tho...but they REALLY need to clean that vent in the ceiling...its quite un-appetizing, and kills your effort to make this place look sleek and modern."], "output": "[['place', 'ambience general', 'negative'], ['decor', 'ambience general', 'positive'], ['vent', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Their sake list was extensive, but we were looking for Purple Haze, which wasn't listed but made for us upon request!"], "output": "[['sake list', 'drinks style_options', 'positive'], ['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The spicy tuna roll was unusually good and the rock shrimp tempura was awesome, great appetizer to share!"], "output": "[['spicy tuna roll', 'food quality', 'positive'], ['rock shrimp tempura', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We went around 9:30 on a Friday and it had died down a bit by then so the service was great!"], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["we love th pink pony."], "output": "[['pink pony', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["THe perfect spot."], "output": "[['spot', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food-awesome."], "output": "[['Food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service- friendly and attentive."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ambiance- relaxed and stylish."], "output": "[['Ambiance', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Don't judge this place prima facie, you have to try it to believe it, a home away from home for the literate heart."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the food is decent."], "output": "[['food', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["however, it's the service that leaves a bad taste in my mouth."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["i happen to have a policy that goes along with a little bit of self-respect, which includes not letting a waiter intimidate me, i.e. make me feel bad asking for trivialities like water, or the check."], "output": "[['waiter', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["i know, you were too busy showing off your vintage tee shirt and looking bored, but my agenda is i'm here to eat and enjoy the company of friends, seeking a pleasant experience."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["well, i didn't find it there, and trust, i have told everyone i can think of about my experience. "], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the last time i walked by it looked pretty empty. hmmm."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place has got to be the best japanese restaurant in the new york area."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had a great experience."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food is great."], "output": "[['Food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service is top notch."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have been going back again and again."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I tend to judge a sushi restaurant by its sea urchin, which was heavenly at sushi rose."], "output": "[['sea urchin', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It melted in my little mouth and the perfect consistency-not too fishy, creamy, and slightly buttery."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sushi seemed pretty fresh and was adequately proportioned."], "output": "[['sushi', 'food quality', 'positive'], ['sushi', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The rice to fish ration was also good--they didn't try to overpack the rice."], "output": "[['rice to fish ration', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We took advanatage of the half price sushi deal on saturday so it was well worth it."], "output": "[['half price sushi deal', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Surprisingly nothing could be further from the truth."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["In the evening, this place attracted a well dressed, with it, NY crowd."], "output": "[['crowd', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was well prepared and the service impecable."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm going back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Quite simply it's like stepping out of Manhattan and into a haven of tranquility."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The Prix Fixe menu is worth every penny and you get more than enough (both in quantity AND quality)."], "output": "[['Prix Fixe menu', 'food quality', 'positive'], ['Prix Fixe menu', 'food style_options', 'positive'], ['Prix Fixe menu', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will be going back and heartily recommend it!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is terrific, as is the value."], "output": "[['NULL', 'food quality', 'positive'], ['NULL', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["$6 and there is much tasty food, all of it fresh and continually refilled."], "output": "[['food', 'food style_options', 'positive'], ['food', 'food quality', 'positive'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I am not a vegetarian but, almost all the dishes were great."], "output": "[['dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go hungry and enjoy."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food here is rather good, but only if you like to wait for it."], "output": "[['food', 'food quality', 'positive'], ['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I like the somosas, chai, and the chole, but the dhosas and dhal were kinda dissapointing."], "output": "[['somosas', 'food quality', 'positive'], ['chai', 'food quality', 'positive'], ['chole', 'food quality', 'positive'], ['dhosas', 'food quality', 'negative'], ['dhal', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service varys from day to day- sometimes they're very nice, and sometimes not."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The kitchen however, is almost always slow."], "output": "[['kitchen', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also, specify if you like your food spicy- its rather bland if you don't."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The ambience is pretty and nice for conversation, so a casual lunch here would probably be best."], "output": "[['ambience', 'ambience general', 'positive'], ['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you've ever been along the river in Weehawken you have an idea of the top of view the chart house has to offer."], "output": "[['view', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Add to that great service and great food at a reasonable price and you have yourself the beginning of a great evening."], "output": "[['service', 'service general', 'positive'], ['food', 'food quality', 'positive'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The lava cake dessert was incredible and I recommend it."], "output": "[['lava cake dessert', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Once you step into Cosette, you're miraculously in a small, off-the-beaten path Parisian bistro."], "output": "[['Cosette', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This tiny restaurant is as cozy as it gets, with that certain Parisian flair."], "output": "[['restaurant', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was average to above-average; the French Onion soup filling yet not overly impressive, and the desserts not brilliant in any way."], "output": "[['food', 'food quality', 'positive'], ['French Onion soup', 'food quality', 'negative'], ['French Onion soup', 'food style_options', 'positive'], ['desserts', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["However, go for the ambience, and consider the food just a companion for a trip across the world!"], "output": "[['ambience', 'ambience general', 'positive'], ['food', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["IT WAS HORRIBLE."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza was delivered cold and the cheese wasn't even fully melted!"], "output": "[['pizza', 'food quality', 'negative'], ['cheese', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It looked like shredded cheese partly done - still in strips."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This has got to be one of the most overrated restaurants in Brooklyn."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza is overpriced and soggy."], "output": "[['pizza', 'food quality', 'negative'], ['pizza', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Yes, they use fancy ingredients, but even fancy ingredients don't make for good pizza unless someone knows how to get the crust right."], "output": "[['ingredients', 'food quality', 'positive'], ['pizza', 'food quality', 'negative'], ['crust', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A big disappointment, all around."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I think I've had some the best meals of my life at minnow."], "output": "[['meals', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The seafood is amazing, there's a good wine list, and the ever-changing menu always offers some great surprises."], "output": "[['seafood', 'food quality', 'positive'], ['wine list', 'drinks style_options', 'positive'], ['menu', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The combination of super-fresh ingredients in the dishes are unusual but really delicious."], "output": "[['ingredients', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Worth the trip from Manhattan."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Best Pastrami I ever had and great portion without being ridiculous."], "output": "[['Pastrami', 'food quality', 'positive'], ['portion', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My wife had the fried shrimp which are huge and loved it."], "output": "[['fried shrimp', 'food style_options', 'positive'], ['fried shrimp', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["As a Japanese native, I've lived in the Tristate area for over 8 years, but I was just so amazed at this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is the most Japanese it can ever get."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The signs, the specials menus, food, and even all the waitstaff are ALL TOTALLY Japanese."], "output": "[['signs', 'restaurant miscellaneous', 'positive'], ['specials menus', 'food style_options', 'positive'], ['food', 'food quality', 'positive'], ['waitstaff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is worth an one-hour drive."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I am so coming back here again, as much as I can."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Leon is an East Village gem: casual but hip, with well prepared basic French bistro fare, good specials, a warm and lively atmosphere."], "output": "[['Leon', 'restaurant general', 'positive'], ['Leon', 'ambience general', 'positive'], ['specials', 'food quality', 'positive'], ['atmosphere', 'ambience general', 'positive'], ['French bistro fare', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My wife and I always enjoy the young, not always well trained but nevertheless friendly, staff, all of whom have a story."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Decent wine at reasonable prices."], "output": "[['wine', 'drinks quality', 'neutral'], ['wine', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Have been dozens of times and never failed to enjoy the experience."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Our teenage kids love it, too."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everytime I decide to try another place on the UES, I get angry that I didn't just go to Zucchero Pomodori."], "output": "[['Zucchero Pomodori', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is by far my favorite place in the neighborhood."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service is excellent, the decor is great, and the food is delicious and comes in large portions."], "output": "[['service', 'service general', 'positive'], ['decor', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['portions', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm partial to the Gnocchi."], "output": "[['Gnocchi', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is incredibly tiny."], "output": "[['place', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They refuse to seat parties of 3 or more on weekends."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The hostess is rude to the point of being offensive."], "output": "[['hostess', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was bland oily."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I just don't understand all the hype..."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We have been to this place many times, and always have great food, wine, and service."], "output": "[['food', 'food quality', 'positive'], ['wine', 'drinks quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were worried we would have trouble getting in, but somehow managed to have a short wait."], "output": "[['wait', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["As always we had a great glass of wine while we waited."], "output": "[['glass of wine', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When we sat, we got great and fast service."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The people that work there are always so friendly you forget you are in New York sometimes."], "output": "[['people', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Make sure you try this place as often as you can."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is a fun restaurant to go to."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza is yummy and I like the atmoshpere."], "output": "[['pizza', 'food quality', 'positive'], ['atmoshpere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But the pizza is way to expensive."], "output": "[['pizza', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I went there for lunch and it was not as good as I expected from the reviews I read."], "output": "[['lunch', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Sauce was watery and the food didn't have much flavor."], "output": "[['Sauce', 'food quality', 'negative'], ['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I don't think I would go again."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is great."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had a huge group for my birthday and we were well taken care of."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The waitress was very patient with us and the food is phenomenal!"], "output": "[['waitress', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was prompt, friendly and great."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Slightly on the pricey side but worth it!"], "output": "[['NULL', 'restaurant prices', 'negative'], ['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great pizza and fantastic service."], "output": "[['pizza', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["There was a small wait, but shorter than I expected."], "output": "[['wait', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Located at the end of a magnificent block."], "output": "[['NULL', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Very cozy and warm inside....."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will be back!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is the best sushi in new york city - hands down."], "output": "[['sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place is small and cramped but the food is fantastic."], "output": "[['place', 'ambience general', 'negative'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Get the tuna of gari."], "output": "[['tuna of gari', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Planet Thailand has always been a hit with me , I go there usually for the sushi, which is great , the thai food is excellent too ."], "output": "[['sushi', 'food quality', 'positive'], ['thai food', 'food quality', 'positive'], ['Planet Thailand', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["With the great variety on the menu , I eat here often and never get bored ."], "output": "[['menu', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The atmosphere isn't the greatest , but I suppose that's how they keep the prices down ."], "output": "[['atmosphere', 'ambience general', 'negative'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's all about the food !!"], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["first it took us a long time to find the place."], "output": "[['place', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["but when we looked at the menu, there weren't a lot of choices, most of them were dumplings in the appetizer section."], "output": "[['menu', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["those rolls were big, but not good and sashimi wasn't fresh."], "output": "[['rolls', 'food style_options', 'neutral'], ['rolls', 'food quality', 'negative'], ['sashimi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["they were dry and disgusting, i didn't even finish my first piece."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Hurley's is like Cheers where everyone knows your name and they are ACTUALLY glad you came."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try the crunchy tuna, it is to die for."], "output": "[['crunchy tuna', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try everything for that matter, it is all good."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have been going there since it opened and I can't get enough."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["First went here to enjoy their garden terrace."], "output": "[['garden terrace', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was amazing, and the service was prompt and helpful, but not over-bearing or rushed."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The Steak Tartare is a great bet, they fix it for you at the table."], "output": "[['Steak Tartare', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Admittedly some nights inside the restaurant were rather warm, but the open kitchen is part of the charm."], "output": "[['open kitchen', 'ambience general', 'positive'], ['restaurant', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great wine selection, Gigondas is worth the price, and the house champagne is a great value."], "output": "[['wine selection', 'drinks style_options', 'positive'], ['Gigondas', 'drinks quality', 'positive'], ['house champagne', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It may be a bit packed on weekends, but the vibe is good and it is the best French food you will find in the area."], "output": "[['NULL', 'ambience general', 'neutral'], ['vibe', 'ambience general', 'positive'], ['French food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Have recommended the place to friends, always gets good response."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best, freshly baked bread!"], "output": "[['crust', 'food quality', 'positive'], ['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I take all my NYC guests to VT's."], "output": "[[\"VT's\", 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not sure where the previous reviewer, lonk, dined, but Saul is in a great neighborhood and has great food!"], "output": "[['neighborhood', 'location general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've been there three times and have always had wonderful experiences."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'd highly recommend it for a special occasion -- it provides and intimate setting and nice service."], "output": "[['setting', 'ambience general', 'positive'], ['service', 'service general', 'positive'], ['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm not sure where the other reviewers ate but it seems as if we visited two different restaurants because my friends and I all enjoy Mizu very much... and we're repeat customers."], "output": "[['Mizu', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Even after they overcharged me the last time I was there."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Make sure you have the Spicy Scallop roll.. ."], "output": "[['Spicy Scallop roll', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["it's delicious!"], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Moules were excellent, lobster ravioli was VERY salty!"], "output": "[['Moules', 'food quality', 'positive'], ['lobster ravioli', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Took my mom for Mother's Day, and the maitre d' was pretty rude."], "output": "[[\"maitre d'\", 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Told us to sit anywhere, and when we sat he said the table was reserved."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Stepped on my foot on the SECOND time he reached over me to adjust lighting."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Tiny dessert was $8.00...just plain overpriced for what it is."], "output": "[['dessert', 'food quality', 'negative'], ['dessert', 'food style_options', 'negative'], ['dessert', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The drinks are always welll made and wine selection is fairly priced."], "output": "[['drinks', 'drinks quality', 'positive'], ['wine selection', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try their chef's specials-- they are to die for."], "output": "[[\"chef's specials\", 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service is not exactly five star, but thats not really a big deal."], "output": "[['Service', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Downstairs lounge is always a good attraction"], "output": "[['Downstairs lounge', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Raga's is a romantic, cozy restaurant."], "output": "[[\"Raga's\", 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The exotic food is beautifully presented and is a delight in delicious combinations."], "output": "[['exotic food', 'food style_options', 'positive'], ['exotic food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is also extremely well priced."], "output": "[['NULL', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff is incredibly helpful and attentive."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The bar is very well stocked with interesting beers and well priced wines."], "output": "[['bar', 'drinks style_options', 'positive'], ['beers', 'drinks style_options', 'positive'], ['wines', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is one of my favorite restaurants and it is not to be missed."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Your friends will thank you for introducing them to this gem!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When we stumbled on Leon, we thought that we had found quite the gem BUT, we were certainly wrong."], "output": "[['Leon', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The waitress moved our table practically into the bathroom and when we asked to cancel our dinner orders because we did not want to eat sitting on the toilet, we were told no..."], "output": "[['waitress', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Then, to top things off, she dropped used silverware on my boyfriend's jacket and did not stop to apologize or clean the mess that was left on clothes. "], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Such a disappointment..."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Rude service, medicore food...there are tons of restaurants in NY...stay away from this one"], "output": "[['service', 'service general', 'negative'], ['food', 'food quality', 'neutral'], ['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had a grat time at Jekyll and Hyde!"], "output": "[['Jekyll and Hyde', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I loved everythig about it-especially the shows and actors."], "output": "[['NULL', 'restaurant general', 'positive'], ['shows', 'ambience general', 'positive'], ['actors', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Our server was very helpful and friendly."], "output": "[['server', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I am bringing my whole family back next time."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was good too."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The tuna and wasabe potatoes are excellent."], "output": "[['tuna', 'food quality', 'positive'], ['wasabe potatoes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The outdoor atmosphere of sitting on the sidewalk watching the world go by 50 feet away on 6th avenue on a cool evening was wonderful."], "output": "[['outdoor atmosphere', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Inside is a little cramped, but to be expected."], "output": "[['NULL', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was prompt and courteous."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This was a repeat visit and we'll definitely be back again."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great service, great food."], "output": "[['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Prices are in line."], "output": "[['NULL', 'restaurant prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But too far east!"], "output": "[['NULL', 'location general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza is delicious - they use fresh mozzarella instead of the cheap, frozen, shredded cheese common to most pizzaria's."], "output": "[['pizza', 'food quality', 'positive'], ['fresh mozzarella', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Two complaints- their appetizer selection stinks, it would be nice to get some mozzarella sticks on the menu."], "output": "[['appetizer selection', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also, because it is so thin, it gets cold very quickly and its not that filling."], "output": "[['NULL', 'food quality', 'negative'], ['NULL', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wait staff is blantently unappreciative of your business but its the best pie on the UWS!"], "output": "[['Wait staff', 'service general', 'negative'], ['pie', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["By far the best salad I have had in a fast food restaurant."], "output": "[['salad', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["fine dining restaurant quality."], "output": "[['dining', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Over 100 different choices to create your own."], "output": "[['NULL', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A must try!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["On a recent Sunday afternoon, a friend and I accidently found this great restaurant on our way to see the pulitzer prize winning play DOUBT."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This was the perfect quiet, relaxing, and delicious accompaniment to our afternoon of theater."], "output": "[['NULL', 'food quality', 'positive'], ['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The chicken pot pie is excpetiona, the cheeseburger huge and delictable, and the service professional wan warm."], "output": "[['chicken pot pie', 'food quality', 'positive'], ['cheeseburger', 'food style_options', 'positive'], ['cheeseburger', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["With so many poor experiences to be had in the theater district, is truly an excellent find!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We will return many times for this oasis in mid-town."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff is no nonsense."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food options rule."], "output": "[['food', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When I lived upstate for a while I would buy freeze the bagels and they would still be better than any else."], "output": "[['bagels', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Worth visiting the 1st Ave spot because it is the original store."], "output": "[['1st Ave spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["He served me an Uni Hand roll, which I never had before, and let me tell you...IT WAS HEAVEN!"], "output": "[['Uni Hand roll', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sake menu should not be overlooked!"], "output": "[['sake menu', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["All in all, this midtown gem instantly became one of my favorite sushi restaurants in the city."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try the lobster teriyaki and the rose special roll."], "output": "[['lobster teriyaki', 'food quality', 'positive'], ['rose special roll', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was very good - prompt, attentive and non-intrusive."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was very good as well, considering that we tried the budget selection (though I wish the pork belly that I ordered was roasted a bit longer, so that fat was more of a melt-in-your-mouth experience)."], "output": "[['Food', 'food quality', 'positive'], ['pork belly', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wine list selection is good and wine-by-the-glass was generously filled to the top."], "output": "[['Wine list selection', 'drinks style_options', 'positive'], ['wine-by-the-glass', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Traditional French decour was pleasant though the hall was rather noisy - the restaurant was full and we had to raise our voices to be able to maintain a conversation."], "output": "[['Traditional French decour', 'ambience general', 'positive'], ['hall', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've been to at Cafe Spice probably 5-8 times, it is probably still the best Indian restaurant around Union Square."], "output": "[['Cafe Spice', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["To sum it up: Service varies from good to mediorce, depending on which waiter you get; generally it is just average Ok. "], "output": "[['Service', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Seating is always prompt, though the restaurant does fill up in the evening."], "output": "[['Seating', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food is usually very good, though ocasionally I wondered about freshmess of raw vegatables in side orders."], "output": "[['Food', 'food quality', 'positive'], ['raw vegatables in side orders', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["As many other reviewers noticed, your order is often slow to arrive - this is particularly true in the evening but is not a problem during lunch time."], "output": "[['NULL', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The decor is vibrant and eye-pleasing with several semi-private boths on the right side of the dining hall, which are great for a date."], "output": "[['decor', 'ambience general', 'positive'], ['semi-private boths', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have NEVER been disappointed in the Red Eye."], "output": "[['Red Eye', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The first time I went, and was completely taken by the live jazz band and atmosphere, I ordered the Lobster Cobb Salad."], "output": "[['live jazz band', 'ambience general', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's simply the best meal in NYC."], "output": "[['meal', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You cannot go wrong at the Red Eye Grill."], "output": "[['Red Eye Grill', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If we were to move from the upper east side, we would genuinely miss this restaurant."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The restaurant is cute but not upscale."], "output": "[['restaurant', 'restaurant general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes."], "output": "[['food', 'food quality', 'positive'], ['balance of herbs and tomatoes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would highly recommend it."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's one of our favorite places to eat in NY."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We had a great time at the Jekyll and hyde Pub last night."], "output": "[['Jekyll and hyde Pub', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["After really enjoying ourselves at the bar we sat down at a table and had dinner."], "output": "[['bar', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The server was really cool and served us our food and drinks with a smile."], "output": "[['server', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place's decor and hidden bathrooms made for a good laugh."], "output": "[['decor', 'ambience general', 'positive'], ['hidden bathrooms', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend visiting this restaurant and having dinner and drinks!"], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you are the type of person who likes being scared and entertained, this is a great place to go and eat."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My husband and I thougt it would be great to go to the Jekyll and Hyde Pub for our anniversary, and to our surprise it was fantastic."], "output": "[['Jekyll and Hyde Pub', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The have over 100 different beers to offer thier guest so that made my husband very happy and the food was delicious, if I must recommend a dish it must be the pumkin tortelini."], "output": "[['beers', 'drinks style_options', 'positive'], ['food', 'food quality', 'positive'], ['pumkin tortelini', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The entertainment was great they have shows that go on through out the dinner."], "output": "[['entertainment', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Please take my advice, go and try this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You will not be disapointed at all."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were not dissappointed in the least bit by this little gem."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The bagel was huge."], "output": "[['bagel', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They were served warm and had a soft fluffy interior."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The workers there also absolutely load the bagel with cream cheese (gets a little messy)."], "output": "[['bagel', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I loved it and would HIGHLY RECOMMEND."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This was my frist time at Cafe St. Bart's and I must say how delicous the food and the service was."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have to highly recommend the lobster roll - not to much mayo; you can tell it was a fresh lobster."], "output": "[['lobster roll', 'food quality', 'positive'], ['lobster', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Other guests enjoyed pizza, santa fe chopped salad and fish and chips."], "output": "[['pizza', 'food quality', 'positive'], ['santa fe chopped salad', 'food quality', 'positive'], ['fish and chips', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend Cafe St. Bart's for their food, the ambience and wonderful service."], "output": "[['food', 'food quality', 'positive'], ['ambience', 'ambience general', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["All the staff is absolutely professional!! "], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["(that is A MUST, but not every restaurant can do...) "], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["There's nice and quiet, small but enough for 6 (or more)."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This restaurant was way overhyped."], "output": "[['restaurant', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My chow fun and chow see was really bland and oily."], "output": "[['chow fun and chow see', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Okay-i don't mind the oily part (cause most are cooked that way) but it was way too bland."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The scallion pancakes and fried dumplings were nothing out of the ordinary."], "output": "[['scallion pancakes', 'food quality', 'neutral'], ['fried dumplings', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was the only thing good about this restaurant."], "output": "[['service', 'service general', 'positive'], ['restaurant', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's boring on the inside, and our sushi was pretty below average... the tuna was soggy and the other rolls had no flavor."], "output": "[['NULL', 'ambience general', 'negative'], ['sushi', 'food quality', 'negative'], ['tuna', 'food quality', 'negative'], ['rolls', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I definitely wouldn't go back."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Their pad penang is delicious and everything else is fantastic."], "output": "[['pad penang', 'food quality', 'positive'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The price is reasonable although the service is poor."], "output": "[['NULL', 'restaurant prices', 'positive'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["fresh restaurant was amazing........ food was delicious and of course fresh."], "output": "[['fresh restaurant', 'restaurant general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["great for a romantic evening, or a fun evening with friends..."], "output": "[['NULL', 'ambience general', 'positive'], ['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will be going back very soon."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["keep up the good work."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Hats off to the chef."], "output": "[['chef', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was wonderful."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the salads are delicious, both refreshing and very spicy."], "output": "[['salads', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We had Pam's special fried fish and it was amazing."], "output": "[[\"Pam's special fried fish\", 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["too large for just two people but nothing was left."], "output": "[['NULL', 'food style_options', 'negative'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great vibe, lots of people."], "output": "[['vibe', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My husbands was perfect, my was well done and dry."], "output": "[['NULL', 'food quality', 'positive'], ['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I didn't complain, I liked the atmosphere so much."], "output": "[['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["On a hot day it was fabulous to stop in and enjoy lunch."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ambience is so cute and quaint, good for business although we were there on vacation."], "output": "[['Ambience', 'ambience general', 'positive'], ['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Salads were fantastic."], "output": "[['Salads', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Although we were looking for regular lettuce and some walnuts the salads we got were great."], "output": "[['salads', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ingredients are organic which is a real plus for me."], "output": "[['Ingredients', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We will be back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is some really good, inexpensive sushi."], "output": "[['sushi', 'food quality', 'positive'], ['sushi', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The spicy Tuna roll is huge and probably the best that I've had at this price range."], "output": "[['spicy Tuna roll', 'food style_options', 'positive'], ['spicy Tuna roll', 'food quality', 'positive'], ['spicy Tuna roll', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The Yellowtail was particularly good as well."], "output": "[['Yellowtail', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have reservations about the all you can eat deal, however -- the choices are fairly limited and you can probably order more food than you can eat for less than $18 by just going off the menu."], "output": "[['all you can eat deal', 'food style_options', 'negative'], ['all you can eat deal', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["In any event, this is a place I'll be sure to stop by again when I'm in this part of town."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Big Wong gets big Ups for a fine establishment."], "output": "[['Big Wong', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They have it all -- great price, food, and service."], "output": "[['NULL', 'restaurant general', 'positive'], ['NULL', 'restaurant prices', 'positive'], ['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The atmosphere is noisy and the waiters are literally walking around doing things as fast as they can."], "output": "[['atmosphere', 'ambience general', 'negative'], ['waiters', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is prepared quickly and efficiently."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And it all comes at a very reasonable price (congee, noodles, and rice dishes are no more than $3-6 each)."], "output": "[['NULL', 'food prices', 'positive'], ['congee', 'food prices', 'positive'], ['noodles', 'food prices', 'positive'], ['rice dishes', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The takeout is great too since they give high quality tupperware as well."], "output": "[['takeout', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is always very crowded and popular."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Enjoyed a very nice Caesar Salad while my wife had arugula and goat cheese....both very tasty."], "output": "[['Caesar Salad', 'food quality', 'positive'], ['arugula and goat cheese', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We both opted for a pasta dish and they were served timely and fresh."], "output": "[['NULL', 'service general', 'positive'], ['pasta dish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We concluded with tiramisu chocolate cake, both were delicious."], "output": "[['tiramisu chocolate cake', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We'd go back again"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I recently went to this restaurant with some co-workers for lunch and had an amazing time."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff was accomodating, the food was absolutely delicious and the place is lovely."], "output": "[['staff', 'service general', 'positive'], ['food', 'food quality', 'positive'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We even had a visit from the Manager who wanted to make sure we were enjoying ourselves."], "output": "[['Manager', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Yes, the prices are high, but I felt it was worth it."], "output": "[['NULL', 'restaurant prices', 'negative'], ['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We all felt it was worth it."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["sometimes i get good food and ok service."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["sometimes i get bad food and bad service, sometimes i get good good and bad service."], "output": "[['food', 'food quality', 'negative'], ['service', 'service general', 'negative'], ['service', 'service general', 'negative'], ['good', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["it is not consistent."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place is a BISTRO which means: simple dishes and wine served efficiently in a bustling atmosphere."], "output": "[['dishes', 'food style_options', 'positive'], ['wine', 'drinks style_options', 'positive'], ['NULL', 'service general', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And where does Patis go wrong; no where. "], "output": "[['Patis', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You are not eating haut cuisine with subtle hints of whatever but: Cassuolet, Steake Fritte, Tripe Stew, etc; simple stuff."], "output": "[['NULL', 'food style_options', 'positive'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And evaluated on those terms Pastis is simply wonderful."], "output": "[['Pastis', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Right off the L in Brooklyn this is a nice cozy place with good pizza."], "output": "[['pizza', 'food quality', 'positive'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Mine was a little burnt but still delicious with goat cheese and panchetta (raddichio was kind of bitter though)."], "output": "[['raddichio', 'food quality', 'negative'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My friend got the mushroom pizza which tasted better."], "output": "[['mushroom pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sangria was pretty tasty and good on a hot muggy day."], "output": "[['sangria', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Kind of a small place but I guess if they are not too busy might be able to fit a group or kids."], "output": "[['place', 'restaurant miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Overall I would recommend it and go back again."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I started out with a Bombay beer which was big enough for two."], "output": "[['Bombay beer', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["MMmmm... it was delicious."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was slow, but the people were friendly."], "output": "[['Service', 'service general', 'negative'], ['people', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's a nice place to relax and have conversation."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I can't wait to go back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is authentic Italian - delicious!"], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Pizza is terrific, as is homemade pasta."], "output": "[['Pizza', 'food quality', 'positive'], ['homemade pasta', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ambience is delightful, service impeccable."], "output": "[['Ambience', 'ambience general', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm still mad that i had to pay for lousy food."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The hanger steak was like rubber and the tuna was flavorless not to mention it tasted like it had just been thawed."], "output": "[['hanger steak', 'food quality', 'negative'], ['tuna', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was also horrible and the ambience is not that great."], "output": "[['Service', 'service general', 'negative'], ['ambience', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["DO not try unless you're just going there to hang out like the rest of the hipsters who apparently have no sense of taste."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I go and eat out at many different restaurants and this is one place you have go and try."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is my first time writing a review for a restaurant because the food and service was excellent."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The filet mignon dish was superb!"], "output": "[['filet mignon dish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would defiantly come back here again as one of my top choices."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's a small cute restaurant."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I absolutely love this place!!!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I like the ambience, it's very dark and original."], "output": "[['ambience', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sushi is amazing!!! "], "output": "[['sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And amazingly cheap."], "output": "[['NULL', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Big thumbs up!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Very affordable and excellent ambient!"], "output": "[['ambient', 'ambience general', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ordered some beef and noodle soup dishes from the Thai section of the menu but nothing we got was Thai."], "output": "[['beef and noodle soup dishes', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were very disappointed."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We won't go to this place again for a good meal."], "output": "[['meal', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["However, I think this place is a good hang out spot."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My Girlfriend and I stumbled onto this hopping place the other night and had a great time!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["THe Pizza and wine were excellent-the service too--but what really MADE this place was the backyard dining area."], "output": "[['Pizza', 'food quality', 'positive'], ['wine', 'drinks quality', 'positive'], ['service', 'service general', 'positive'], ['backyard dining area', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is one the nicest outdoor restaurants I have ever seen in NY--I am from Italy and this place rivals the ones in my country."], "output": "[['outdoor restaurants', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They tell me they are going to cover the garden in glass for the winter, so i'm looking forward to going there on a snowy night to enjoy it."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Check this place out!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["HIGHLY RECOMMENDED!!!!!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["First of all, this place is *not* romantic, as claimed by Citysearch's editorial review."], "output": "[['place', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Either that, or the editor's idea of romance must be sharing a conversation with the next table, while trying to speak louder than the traffic on 57th."], "output": "[['NULL', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The tables are crammed way too close, the menu is typical of any Italian restaurant, and the wine list is simply overpriced."], "output": "[['tables', 'ambience general', 'negative'], ['menu', 'food style_options', 'neutral'], ['wine list', 'drinks prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Slightly above average wines start at $70+ with only one selection listed at $30+."], "output": "[['wines', 'drinks quality', 'negative'], ['wines', 'drinks prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service is not what one would expect from a joint in this price category."], "output": "[['Service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["For instance, plates were just dumped on the table, I was handed the wine list upside down, etc.... "], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Somehow working the italian charm with constant mille grazie does not constitute proper service."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["To be completely fair, the only redeeming factor was the food, which was above average, but couldn't make up for all the other deficiencies of Teodora."], "output": "[['food', 'food quality', 'positive'], ['Teodora', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not one of our meals was edible - bland and/or made with weird rosemary or orange flavoring."], "output": "[['meals', 'food quality', 'negative'], ['rosemary or orange flavoring', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Fish was overdone."], "output": "[['Fish', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Cute place, nice wait staff but would never go there again."], "output": "[['wait staff', 'service general', 'positive'], ['place', 'ambience general', 'positive'], ['place', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Someone else recommended the dessert - we also left that."], "output": "[['dessert', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["One of us actually liked the expresso - that's it."], "output": "[['expresso', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Skip this restaurant, it's a big disappointment."], "output": "[['restaurant', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Myagi is one of my favorite restaurants in the City; the place the negative reviews describe sound like they were somewhere else."], "output": "[['Myagi', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've never had bad service and the fish is fresh and delicious."], "output": "[['service', 'service general', 'positive'], ['fish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Their tuna tartar appetizer is to die for."], "output": "[['tuna tartar appetizer', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I come from a family of pizzeria owners, and I'm almost ashamed to say that the pizza in Fornino's blows my families receipies away."], "output": "[['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is simply amazing."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place is so cool and the service is prompt and curtious."], "output": "[['service', 'service general', 'positive'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend to anyone to give this place a try."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You will find yourself returning quite often."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A restaurant that doesn't try to do anything except serve great food with great service in a pleasant atmosphere."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["No gimmicks here -- the food speaks for itself in its freshness and preparation."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The dining room is quietly elegant with no music to shout over -- how refreshing!"], "output": "[['dining room', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was impeccable and unobtrusive -- the staff knows what they are there to do -- to know their menu, present your meal, and attend to your needs."], "output": "[['service', 'service general', 'positive'], ['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Looking around, I saw a room full of New Yorkers enjoying a real meal in a real restaurant, not a clubhouse of the fabulous trying to be seen."], "output": "[['meal', 'food quality', 'positive'], ['restaurant', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Beautiful experience."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The view is breathtaking the service is top notch... the ambiance is wonderfull."], "output": "[['view', 'location general', 'positive'], ['service', 'service general', 'positive'], ['ambiance', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff offers impeccable service."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had Lobster Bisque it has 2 oz. of Maine Lobster in it."], "output": "[['Lobster Bisque', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque."], "output": "[['New England Chowder', 'food quality', 'positive'], ['Lobster Bisque', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was divine melts in your mouth."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My boyfriend had Prime Rib it was good ."], "output": "[['Prime Rib', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We didn't want a bottle of bubbly on a weekday so we each got little bottles of Korbett it was just enough. "], "output": "[['bottles of Korbett', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's cuz it's so good you need to taste it!!! "], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["All in all we're already coming up with excuses to go ahead really soon in the next few wks!!!!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My wife and I ate here earlier this week and have not stopped ranting and raving about the food."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you like spicy food get the chicken vindaloo."], "output": "[['chicken vindaloo', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's very spicy but not offensive."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We will definitely go back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go to Volare for 1st class service and terrific food."], "output": "[['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The portions are large and the servers always surprise us with a different starter."], "output": "[['portions', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wine list is excellent."], "output": "[['wine list', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is amazing... especially if you get the Chef's tasting menu and your favourite bottle (or two!) of wine from an extensive selection of wines."], "output": "[['food', 'food quality', 'positive'], ['selection of wines', 'drinks style_options', 'positive'], [\"Chef's tasting menu\", 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place is small and intimate and you may feel a little crowded, but the service is excellent and it's great for friends out, a romantic date, or a special occassion."], "output": "[['service', 'service general', 'positive'], ['place', 'ambience general', 'negative'], ['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you don't like."], "output": "[['food', 'food prices', 'negative'], ['prixe fixe tasting menu', 'food quality', 'positive'], ['prixe fixe tasting menu', 'food prices', 'positive'], ['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Please be aware that it's CASH or AMEX only!"], "output": "[['NULL', 'restaurant miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["With the exception of our lemon salad that had so much pepper on it that our eyes started watering, the food here was decent, not great."], "output": "[['food', 'food quality', 'neutral'], ['lemon salad', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The menu is very limited - i think we counted 4 or 5 entrees."], "output": "[['menu', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ordered the special, grilled branzino, that was so infused with bone, it was difficult to eat."], "output": "[['grilled branzino', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The decor in this place is very diner-ish and the kind of place you expect in the East Village - not romantic, just simple, small and sparse."], "output": "[['decor', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Problem is nothing at Prune is particularly memorable."], "output": "[['Prune', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["No plans to return anytime soon."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is so much fun."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Our family never expected such incredible entertainment in a restaurant."], "output": "[['entertainment', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Our food was great too!"], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And really large portions."], "output": "[['portions', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff was the friendliest that have seen in New York."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We will go back every time we are in the City."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you want something really different than try Jekyll and Hyde."], "output": "[['Jekyll and Hyde', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is a lot of fun with live entertainment and all kinds of Disney type special effects."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was pretty tradional but it was hot and good with large portions."], "output": "[['food', 'food quality', 'positive'], ['portions', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend it."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place is a lot of fun."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My six year old loved it."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The characters really make for an enjoyable experience."], "output": "[['characters', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food however, is what one might expect."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is very overpriced and not very tasty."], "output": "[['NULL', 'food quality', 'negative'], ['NULL', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["However, I think Jeckll and Hydes t is one of those places that is fun to do once."], "output": "[['Jeckll and Hydes', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We had a good time."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Went there with my wife and we had to wait for a table even though you could see there many that were empty with not reservation sigh on them."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was slow had to wait to order and get food although not crowded."], "output": "[['Service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Drinks way over priced."], "output": "[['Drinks', 'drinks prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was good not great not worth the wait or another visit"], "output": "[['Food', 'food quality', 'neutral'], ['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great pizza for lunch place."], "output": "[['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was quick."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza was great."], "output": "[['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And it was quick which is very important."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was wonderful."], "output": "[['NULL', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Whenever you need a Sushi fix, Mizu will be there with quality fish and great service."], "output": "[['fish', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Delivery is fast too."], "output": "[['Delivery', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great friendly service, Fast seating, Fast Delivery, Excellent sushi."], "output": "[['service', 'service general', 'positive'], ['seating', 'service general', 'positive'], ['Delivery', 'service general', 'positive'], ['sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A little overpriced but worth it once you take a bite."], "output": "[['NULL', 'food prices', 'negative'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ess-A-Bagel (either by Sty-town or midtown) is by far the best bagel in NY."], "output": "[['bagel', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The bagels always warm, soft on the inside, crispy on the outside and enormous in size."], "output": "[['bagels', 'food quality', 'positive'], ['bagels', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They have a huge selection of different cream cheeses and all of their salads are great."], "output": "[['salads', 'food quality', 'positive'], ['cream cheeses', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The lox is always fresh too."], "output": "[['lox', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Highly recommended to all!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not impressed with the food."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Prices too high for this cramped and unappealing resturant."], "output": "[['resturant', 'restaurant prices', 'negative'], ['resturant', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Zero ambiance to boot."], "output": "[['ambiance', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I thought this place was totally overrated."], "output": "[['place', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everything we had was good or ok....but definitely nothing great."], "output": "[['NULL', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The ambience was nice, but service wasn't so great."], "output": "[['ambience', 'ambience general', 'positive'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When you add it all together, it just doesn't seem worth it to me...especially considering the prices."], "output": "[['NULL', 'restaurant general', 'negative'], ['NULL', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is the BEST Shabu-Shabu Restaurant in the Try-State Area."], "output": "[['Shabu-Shabu Restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have lived in Japan for 7 years and the taste of the food and the feel of the restaurant is like being back in Japan."], "output": "[['food', 'food quality', 'positive'], ['feel', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Thius is a must for anyone who loves Shabu-Shabu."], "output": "[['Shabu-Shabu', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The atmosphere is nothing special, but it feels like a Sushi establishment in Tokyo."], "output": "[['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The owner and staff are all Japanese as well and that adds to the entire ambiance."], "output": "[['owner', 'restaurant miscellaneous', 'positive'], ['staff', 'restaurant miscellaneous', 'positive'], ['ambiance', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Despite a slightly limited menu, everything prepared is done to perfection, ultra fresh and a work of food art."], "output": "[['menu', 'food style_options', 'negative'], ['NULL', 'food quality', 'positive'], ['NULL', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I must give it Yon out of Yon stars!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Taxan delicious!"], "output": "[['Taxan', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We weren't!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The prices were CHEAP compared to the quality of service and food."], "output": "[['NULL', 'restaurant prices', 'positive'], ['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We liked it so much, that we will always make it a point to dine here when we visit New York."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The location and ambience is Ok but the food is what makes up for it."], "output": "[['location', 'location general', 'neutral'], ['ambience', 'ambience general', 'neutral'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["There is a lot of variety even for people who eat vegetarian like me."], "output": "[['NULL', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try green curry with vegetables."], "output": "[['green curry with vegetables', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The quantity is also very good, you will come out satisfied."], "output": "[['quantity', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service is ok, some of the people didn't get what they asked for."], "output": "[['service', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I was there on sat. for my birthday and we had an excellent time."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had the best ravioli ever."], "output": "[['ravioli', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wine the service was very good too."], "output": "[['wine', 'drinks quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Moderate prices."], "output": "[['NULL', 'restaurant prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A little noise but I think that was because of our party!"], "output": "[['NULL', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This quaint and romantic trattoria is at the top of my Manhattan restaurant list."], "output": "[['trattoria', 'ambience general', 'positive'], ['trattoria', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is delicious - from the specials to the regular menu-fare, the dishes are never a disappointment."], "output": "[['food', 'food quality', 'positive'], ['dishes', 'food quality', 'positive'], ['specials', 'food quality', 'positive'], ['regular menu-fare', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Whether it's the parmesean porcini souffle or the lamb glazed with balsamic vinegar, you will surely be transported to Northern Italy with one bite."], "output": "[['parmesean porcini souffle', 'food quality', 'positive'], ['lamb glazed with balsamic vinegar', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Although the tables may be closely situated, the candle-light, food-quality and service overcompensate."], "output": "[['candle-light', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['tables', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A guaranteeed delight!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have known about this secret for the last 13 years, Emilio(the Godfather) has continued to serve food and wine for the gods at mortal prices."], "output": "[['food', 'food quality', 'positive'], ['wine', 'drinks quality', 'positive'], ['food', 'food prices', 'positive'], ['wine', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you go, try the marinara/arrabiatta sauce, the mozzarella en Carozza is mmmmmmmm..... everything is just delicious."], "output": "[['marinara/arrabiatta sauce', 'food quality', 'positive'], ['mozzarella en Carozza', 'food quality', 'positive'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Check out the secret back room."], "output": "[['back room', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I pray it stays open forever."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Thank You Emilio."], "output": "[['Emilio', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I found the food, service and value exceptional everytime I have been there."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was authentic."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I felt as though I were eating in Paris."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was excellent - friendly and attentive."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The prices are wonderfully low."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Very good wine choices."], "output": "[['wine choices', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Who has room for Cheesesticks with the best pizza in NYC!"], "output": "[['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Get the pepperoni - YUM - and a family style salad."], "output": "[['pepperoni', 'food quality', 'positive'], ['family style salad', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great staff."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Always great service!"], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I go twice a month!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Fantastic!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is good, I can't lie."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But the staff was so horrible to us."], "output": "[['staff', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The hostess and the waitress were incredibly rude and did everything they could to rush us out."], "output": "[['hostess', 'service general', 'negative'], ['waitress', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were planning to get dessert but the waitress basically through the bill at us before we had a chance to order."], "output": "[['waitress', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is pricey, and yes, the food is worth it; but the service makes you feel like you should be paying a quater of the price."], "output": "[['place', 'restaurant prices', 'negative'], ['food', 'food quality', 'positive'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Save yourself the time and trouble and skip this one!"], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Amma is nothing special."], "output": "[['Amma', 'restaurant general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I ate here a week ago and found most dishes average at best and too expensive."], "output": "[['dishes', 'food quality', 'negative'], ['dishes', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Will not be back."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Don't dine at Tamarind for the vegetarian dishes, they are simply not up to par with the non-veg selections."], "output": "[['vegetarian dishes', 'food quality', 'negative'], ['non-veg selections', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Decor is nice though service can be spotty."], "output": "[['Decor', 'ambience general', 'positive'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is always packed."], "output": "[['place', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Most importantly, food is excellent."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try the sea bass."], "output": "[['sea bass', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Highly recommended."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["First of all Dal Bukhara Rocks."], "output": "[['Dal Bukhara', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I am happy i did the food was awsome."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["JUST AWSOME."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["and yes Dal Bukhara is so dam good and so are all the kababs."], "output": "[['kababs', 'food quality', 'positive'], ['Dal Bukhara', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["but overall i give it a 10"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["10"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Haru on Park S is simply disgusting."], "output": "[['Haru on Park S', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The fish was not fresh and the rice tasted old and stale."], "output": "[['fish', 'food quality', 'negative'], ['rice', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Quite frankly, this is some of the worst sushi I have ever tried."], "output": "[['sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Will never be back."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["honestly the worst sushi my husband and i had in our entire lives."], "output": "[['sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["not sure why this restaurant would be rated that highly."], "output": "[['restaurant', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the all-u-can-eat sushi is definitely in very poor quality."], "output": "[['all-u-can-eat sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["limited menu, no-so-fresh ingredients, thinly-sliced fish, fall-apart rice. "], "output": "[['menu', 'food style_options', 'negative'], ['ingredients', 'food quality', 'negative'], ['fish', 'food style_options', 'negative'], ['rice', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the only things u could really taste are the very salty soy sauce (even its low sodium), the vinegar-soaked rice, and the scallion on top of the fish. "], "output": "[['soy sauce', 'food quality', 'negative'], ['rice', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the waitstaffs are nice though."], "output": "[['waitstaffs', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["wont come back again for sure!"], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have been to Roth's twice and both times were very disappointing."], "output": "[[\"Roth's\", 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Both times I was extremely dissappointed by the service, which was boarderline rude."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They wouldnt even let me finish my glass of wine before offering another."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Much of the time it seems like they do not care about you."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The dinner was ok, nothing I would have again."], "output": "[['dinner', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had their eggs benedict for brunch, which were the worst in my entire life, I tried removing the hollondaise sauce completely that was how failed it was."], "output": "[['eggs benedict', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This was a great surprise."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["With the theater 2 blocks away we had a delicious meal in a beautiful room."], "output": "[['meal', 'food quality', 'positive'], ['room', 'ambience general', 'positive'], ['NULL', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was attentive."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I look forward to eating here again"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Planet Thai is great!"], "output": "[['Planet Thai', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We love the food, drinks, and atmosphere!"], "output": "[['food', 'food quality', 'positive'], ['drinks', 'drinks quality', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The svc can be a bit rude at times, esp if you have big group, but overall the restaurant is a must!"], "output": "[['svc', 'service general', 'negative'], ['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try the Pad Thai, it's fabulous and their prices are so cheap!"], "output": "[['Pad Thai', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Just because it's cheap does NOT mean the portions are small or the food is nasty, IT IS GREAT!"], "output": "[['portions', 'food style_options', 'positive'], ['food', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They forgot a sandwich, didn't include plastic forks, and didn't include pita with the hummus platter."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also, the sandwiches (nearing $7) didn't come with anything like chips or a side."], "output": "[['sandwiches', 'food style_options', 'negative'], ['sandwiches', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Overall, not worth the money."], "output": "[['NULL', 'restaurant general', 'negative'], ['NULL', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Eating in, the atmosphere saves it, but at your desk, it's a very disappointing experience."], "output": "[['atmosphere', 'ambience general', 'positive'], ['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Chennai Garden is my favorite Indian restaurant in the city."], "output": "[['Chennai Garden', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They have authentic Indian at amazin prices."], "output": "[['Indian', 'food quality', 'positive'], ['Indian', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This restaurant is VEGETARIAN; there are NO MEAT dishes whatsoever."], "output": "[['MEAT dishes', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The seats are uncomfortable if you are sitting against the wall on wooden benches."], "output": "[['seats', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's a rather cramped and busy restaurant and it closes early."], "output": "[['restaurant', 'restaurant miscellaneous', 'negative'], ['restaurant', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Patroon features a nice cigar bar and has great staff."], "output": "[['cigar bar', 'ambience general', 'positive'], ['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is tasty and portion sizes are appropriate."], "output": "[['food', 'food quality', 'positive'], ['portion sizes', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is a nice restaurant if you are looking for a good place to host an intimate dinner meeting with business associates."], "output": "[['restaurant', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not a great place for family or general dining."], "output": "[['place', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["LLOOVVE THIS PLACE."], "output": "[['PLACE', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food is excellent."], "output": "[['Food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Fish is so very fresh."], "output": "[['Fish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Waitstaff are very friendly."], "output": "[['Waitstaff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Love YUKA."], "output": "[['YUKA', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Mermaid Inn is an overall good restaurant with really good seafood."], "output": "[['seafood', 'food quality', 'positive'], ['Mermaid Inn', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The menu is limited but almost all of the dishes are excellent."], "output": "[['menu', 'food style_options', 'negative'], ['dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The lobster sandwich is good and the spaghetti with Scallops and Shrimp is great."], "output": "[['lobster sandwich', 'food quality', 'positive'], ['spaghetti with Scallops and Shrimp', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service is good and ambience is good for a date or group outing."], "output": "[['service', 'service general', 'positive'], ['ambience', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The only fallback on this restaurant is the prices."], "output": "[['restaurant', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Even though its good seafood, the prices are too high."], "output": "[['seafood', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The lobster sandwich is $24 and although it was good it was not nearly enough to warrant that price."], "output": "[['lobster sandwich', 'food quality', 'positive'], ['lobster sandwich', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were very pleasantly surprised."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was delicious (I had a halibut special, my husband had steak), and the service was top-notch."], "output": "[['food', 'food quality', 'positive'], ['halibut special', 'food quality', 'positive'], ['steak', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When my dessert came, there was a candle in it - not because anyone asked for one - but because the waiter must have seen me opening my birthday card and gift, and said he knew it was a special occassion of some sort."], "output": "[['waiter', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Truly the mark of an attentive waiter."], "output": "[['waiter', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend the restaurant based on our experience last night."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ate at this Thai place following the reviews but very unhappy with the foods."], "output": "[['foods', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We thought that this place is using too much of MSG cooking in the foods."], "output": "[['foods', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They don't concern much of customer's health, just want to make money."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["please don't fool us."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I recommend the jelly fish, drunken chicken and the soupy dumplings, certainly the stir fry blue crab."], "output": "[['jelly fish', 'food quality', 'positive'], ['drunken chicken', 'food quality', 'positive'], ['soupy dumplings', 'food quality', 'positive'], ['stir fry blue crab', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is so cheap and the waiters are nice."], "output": "[['food', 'food prices', 'positive'], ['waiters', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Of course, it is crowded but who cares."], "output": "[['NULL', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Authentic Shanghai style and I cannot recommend a better Shanghai place in New York."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Have frequented 'ino for several years and the food remains excellent."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Cheese plate is a varied delight and great bargain at $10."], "output": "[['Cheese plate', 'food quality', 'positive'], ['Cheese plate', 'food style_options', 'positive'], ['Cheese plate', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The large selection of bruschettas, paninis, tramezzinis keep the palate from stagnating."], "output": "[['bruschettas', 'food style_options', 'positive'], ['paninis', 'food style_options', 'positive'], ['tramezzinis', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["(The asparagus, truffle oil, parmesan bruschetta is a winner!)"], "output": "[['asparagus, truffle oil, parmesan bruschetta', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wine list is extensive without being over-priced."], "output": "[['Wine list', 'drinks style_options', 'positive'], ['Wine list', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Be sure to try the seasonal, and always delicious, specials."], "output": "[['specials', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Definitely a neighborhood favorite."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I loved this place!!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I almost hesititate to write a review because the atmosphere was so great and I would hate for it too become to crowded."], "output": "[['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was very good, a great deal, and the place its self was great."], "output": "[['food', 'food quality', 'positive'], ['food', 'food prices', 'positive'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wait staff is very freindly, they make it feel like you're eating in a freindly little european town."], "output": "[['wait staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I like Cafe Noir dont get me wrong, it is jsut that the people who work there are evil and incompetent!!"], "output": "[['people', 'service general', 'negative'], ['Cafe Noir', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was terrible, we had to wait for everything and ask several of different people for the same thing before we were allowed to be served."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The waitress, seems to be more concerned of looking good than actually waitressing."], "output": "[['waitress', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["After dinner the manager grabbed my boyfriend, asked him: Where are you from...maybe you dont know how things work in America...and in the end stormed away almost teareyed yelling that tips are the only thing they survive on."], "output": "[['manager', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We did tip, I guess the model/waitress just wanted more and complained to the manager."], "output": "[['waitress', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The whole set up is truly unprofessional and I wish Cafe Noir would get some good staff, because despite the current one this is a great place."], "output": "[['staff', 'service general', 'negative'], ['Cafe Noir', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Pizza here is consistently good."], "output": "[['Pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Salads are a delicious way to begin the meal."], "output": "[['Salads', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You should pass on the calamari."], "output": "[['calamari', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is thick and slightly soggy."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Decor is charming."], "output": "[['Decor', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service is average."], "output": "[['Service', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["What a great place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The ambience was so fun, and the prices were great, on top of the fact that the food was really tasty."], "output": "[['ambience', 'ambience general', 'positive'], ['NULL', 'restaurant prices', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I wasn't thrilled to have to wait on line for thirty minutes, but I guess that's the price you pay for a popular place."], "output": "[['NULL', 'service general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would definitely recommend SEA if you like thai cuisine!"], "output": "[['thai cuisine', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I was here a few weeks back and we had the worst customer service experience at a restaurant ever."], "output": "[['customer service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A gentleman, maybe the manager, came to our table, and without so much as a smile or greeting asked for our order."], "output": "[['gentleman', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When asked about how a certain dish was prepared in comparison to a similar at other thai restaurants, he replied this is not Mcdonald's, every place makes things differently "], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["While it is understandable that every place is indeed different, there was not a need to be uncourteous to customers and downright rude."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Never again!"], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I absolutely Loved this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Excellent atmosphere, delicious dishes good and friendly service."], "output": "[['atmosphere', 'ambience general', 'positive'], ['dishes', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["this is can became on e of the NY Italian Food fare institutions."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I think that it is absolutely brilliant and well runned business operation."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wine list is also really nice."], "output": "[['wine list', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everything was wonderful; food, drinks, staff, mileau."], "output": "[['NULL', 'restaurant general', 'positive'], ['food', 'food quality', 'positive'], ['drinks', 'drinks quality', 'positive'], ['staff', 'service general', 'positive'], ['mileau', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would highly recommend this place!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have been to Casimir over 5 times and I have always had a great time there."], "output": "[['Casimir', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is great and reasonably priced."], "output": "[['food', 'food quality', 'positive'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have tried to make reservations, but both times, the hostess didn't have my name."], "output": "[['hostess', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If the weather is nice, try to snag an outside table."], "output": "[['outside table', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The staff has been nice, but they seemed really stressed and the unisex bathroom needs to be cleaned more often."], "output": "[['staff', 'service general', 'positive'], ['unisex bathroom', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My boyfriend and I went there to celebrate my birthday the other night and all I can say is that it was magnificent."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["From the spectacular caviar to the hospitable waitstaff, I felt like royalty and enjoyed every second of it."], "output": "[['caviar', 'food quality', 'positive'], ['waitstaff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Considering we were the last patrons there and it was after the closing time, the waitstaff did not rush us at all and made us feel comfortable and relaxed."], "output": "[['waitstaff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service."], "output": "[['caviar', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Nice Family owned traditional restaurant."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Fresh ingredients and everything is made to order."], "output": "[['ingredients', 'food quality', 'positive'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I was pleasantly surprised to find this gem in Hoboken."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Friendly staff that actually lets you enjoy your meal and the company you're with."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I found the food to be outstanding, particulary the salmon dish I had."], "output": "[['food', 'food quality', 'positive'], ['salmon dish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I also ordered the Change Mojito, which was out of this world."], "output": "[['Change Mojito', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My friends settled for rice dishes, but we came back the following day to try the dim sum, which was good...not outstanding, but good."], "output": "[['dim sum', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ate out in the back patio, which is worth it as it's cool and the music is hear well there."], "output": "[['back patio', 'ambience general', 'positive'], ['music', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Overall, excellent restaurant!"], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was good."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place was nice and calm."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["but the service was a bit slow."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The buffet had a nice selection."], "output": "[['buffet', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was average or above including some surprising tasty dishes."], "output": "[['food', 'food quality', 'positive'], ['dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was also very good."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would go back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I got an excellent piece of cheesecake and we had several other nice pastries."], "output": "[['cheesecake', 'food quality', 'positive'], ['pastries', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would recommend Roxy's for that, but not for their food."], "output": "[['food', 'food quality', 'negative'], ['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My son and his girlfriend both wanted cheeseburgers and they were huge!"], "output": "[['cheeseburgers', 'food style_options', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But, they were too big for the bun."], "output": "[['NULL', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Consequently, their burgers fell apart in their hands and made such a mess that they did'nt feel like finishing them."], "output": "[['burgers', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also they were $15 each!"], "output": "[['NULL', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I had a huge pastrami sandwich on a roll."], "output": "[['pastrami sandwich on a roll', 'food style_options', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was $14 not really bad for a pound of Pastrami-but it didn't have much taste-I've had better for less elsewhere!"], "output": "[['NULL', 'food prices', 'neutral'], ['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is really trendi but they have forgotten about the most important part of a restaurant, the food."], "output": "[['food', 'food quality', 'negative'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The last two times I ordered from here my food was soo spicy that I could barely eat it, and the spice took away from the flavor of the dish."], "output": "[['food', 'food quality', 'negative'], ['spice', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And the Tom Kha soup was pathetic."], "output": "[['Tom Kha soup', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you want good authentic Thai this place is not the place to go."], "output": "[['Thai', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We went here for lunch a couple of weeks ago on a Saturday, and I was thoroughly impressed with the food."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pesto pizza was excellent, thin-crust pizza with a nice amount of spicy Italian cheese that I'd never heard of before."], "output": "[['pesto pizza', 'food quality', 'positive'], ['spicy Italian cheese', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Conveniently located too, being right on Bedford ave."], "output": "[['NULL', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["THe back garden sitting area is very pleasant, where you can see their personal herb garden."], "output": "[['back garden sitting area', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will definetly be going back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We had the lobster sandwich and it was FANTASTIC."], "output": "[['lobster sandwich', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My husband said he could've eaten several more, the portion was fine for me he even exclaimed that the french fries were the best he has had."], "output": "[['NULL', 'food style_options', 'negative'], ['portion', 'food style_options', 'positive'], ['french fries', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We had the scallops as an appetizer and they were delicious and the sauce was wonderful."], "output": "[['scallops', 'food quality', 'positive'], ['sauce', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We waited at the bar and had martinis that were just right."], "output": "[['martinis', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We will be back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["love the food."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["it's the only place you can get yummy authentic japanese comfort food."], "output": "[['japanese comfort food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["and you can't beat the prices."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["highly recommended."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've lived in NY for 5 years and this place has it all."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great food, good size menu, great service and an unpretensious setting."], "output": "[['food', 'food quality', 'positive'], ['menu', 'food style_options', 'positive'], ['service', 'service general', 'positive'], ['setting', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The dishes offered were unique, very tasty and fresh from the lamb sausages, sardines with biscuits, large whole shrimp to the amazing pistachio ice cream (the best and freshest I've ever had)."], "output": "[['dishes', 'food quality', 'positive'], ['lamb sausages', 'food quality', 'positive'], ['sardines with biscuits', 'food quality', 'positive'], ['large whole shrimp', 'food quality', 'positive'], ['pistachio ice cream', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm glad I was introduced to this place and this is a rare gem in NY."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The freshest, best variety, and the fastest delivery."], "output": "[['NULL', 'food quality', 'positive'], ['NULL', 'food style_options', 'positive'], ['delivery', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also very inexpensive."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A great choice at any cost and a great deal."], "output": "[['NULL', 'restaurant general', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was excellent and the food was delicious."], "output": "[['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We are very particular about sushi and were both please with every choice which included: ceviche mix (special), crab dumplings, assorted sashimi, sushi and rolls, two types of sake, and the banana tempura."], "output": "[['sushi', 'food quality', 'positive'], ['ceviche mix (special)', 'food quality', 'positive'], ['crab dumplings', 'food quality', 'positive'], ['assorted sashimi', 'food quality', 'positive'], ['sushi', 'food quality', 'positive'], ['rolls', 'food quality', 'positive'], ['two types of sake', 'drinks quality', 'positive'], ['banana tempura', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Definitely a great spot for a nice occasion or date."], "output": "[['spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Average to good Thai food, but terrible delivery."], "output": "[['Thai food', 'food quality', 'positive'], ['delivery', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've waited over one hour for food."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They were very abrupt with me when I called and actually claimed the food was late because they were out of rice."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A Thai restaurant out of rice during dinner?"], "output": "[['Thai restaurant', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food arrived 20 minutes after I called, cold and soggy."], "output": "[['food', 'food quality', 'negative'], ['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is a wonderful place on all stand points especially value ofr money."], "output": "[['place', 'restaurant prices', 'positive'], ['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["An excellent service"], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were greeted promptly by the waiter who was very nice and cordial."], "output": "[['waiter', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["She was very helpful in suggesting us drinks and helped us in ordering a lot of good dishes since we knew nothing about Indian food."], "output": "[['NULL', 'service general', 'positive'], ['dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food looked very appetizing and delicious since it came on a variety of fancy plates."], "output": "[['food', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ended our great experience by having Gulab Jamun (dessert) recommended by the waiter."], "output": "[['Gulab Jamun (dessert)', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I thanked my friend who recommended me this restaurant and will certainly recommend it to others."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service here was great, food was fantastic."], "output": "[['Service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Guacamole+shrimp appetizer was really great, we both had the filet, very good, didn't much like the frites that came with, but the filet was so good, neither of us cared."], "output": "[['Guacamole+shrimp appetizer', 'food quality', 'positive'], ['filet', 'food quality', 'positive'], ['frites', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Will absolutely visit again."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You cannot go wrong with this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is outstanding and the service is quick, friendly and very professional."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Always a nice crowd, but never loud."], "output": "[['crowd', 'restaurant miscellaneous', 'positive'], ['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go here."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good for dates or with friends."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I am reluctant to write because I would not want my jem of a pizza place to become overcrowded."], "output": "[['pizza place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["However, it is jus too good to not praise it."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["By far, the best pizza in Manhattan."], "output": "[['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The crust is thin, the ingredients are fresh and the staff is friendly."], "output": "[['crust', 'food quality', 'positive'], ['staff', 'service general', 'positive'], ['ingredients', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The menu has so many fish items and oysters."], "output": "[['menu', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The fish was really,really fresh."], "output": "[['fish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We all agreed that mare is one of the best seafood restaurants in New York."], "output": "[['mare', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I stumbled upon this great pizzeria as I explored my new neighborhood."], "output": "[['pizzeria', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["All of the pizzas are terrific and the price is even better!"], "output": "[['pizzas', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I highly recommend the Sophia pizza."], "output": "[['Sophia pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's to die for!"], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was mediocre at best but it was the horrible service that made me vow never to go back."], "output": "[['food', 'food quality', 'negative'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Immediately after we paid, the waiter took the money and said, okay, you guys are outta here."], "output": "[['waiter', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["So rushing us out was absolutely unnecessary!"], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["For the people who want great food plus great service, Roxy is a place to AVOID!"], "output": "[['food', 'food quality', 'negative'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The first time the sushi was outstanding, the second time it was a little bland."], "output": "[['sushi', 'food quality', 'positive'], ['sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm sure I'll return for a final judgement tho."], "output": "[['NULL', 'restaurant general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The blond wood decor is very soothing, the premium sake is excellent and the service is great."], "output": "[['blond wood decor', 'ambience general', 'positive'], ['premium sake', 'drinks quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Mizu is the Japenese find in Grammercy."], "output": "[['Mizu', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["While their kitchen food is delicious, their Sushi is out of this world."], "output": "[['kitchen food', 'food quality', 'positive'], ['Sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Mizu is home to creative and unique rolls not to found anywhere else."], "output": "[['rolls', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not only is the cuisine the best around, the service has always been attentive and charming."], "output": "[['cuisine', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Warning: You may find it difficult to dine at other Japanese restaurants after a visit to Mizu!"], "output": "[['Mizu', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Thalia is a beautiful restaurant with beautiful people serving you, but the food doesn't quite match up."], "output": "[['people', 'service general', 'positive'], ['food', 'food quality', 'negative'], ['Thalia', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I ordered the smoked salmon and roe appetizer and it was off flavor."], "output": "[['smoked salmon and roe appetizer', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The entree was bland and small, dessert was not inspired."], "output": "[['entree', 'food quality', 'negative'], ['entree', 'food style_options', 'negative'], ['dessert', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I expected quite a bit more from such an expensive menu."], "output": "[['menu', 'food prices', 'negative'], ['menu', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The view is spectacular, and the food is great."], "output": "[['view', 'location general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wonderful strawberry daiquiries as well!"], "output": "[['strawberry daiquiries', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Definitely worth the trip to Battery Park City!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["One of my favorite places in Manhattan."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Authentic Taiwanese food that's cheap... what more could you ask for?"], "output": "[['Taiwanese food', 'food quality', 'positive'], ['Taiwanese food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["(Besides that there should be more restaurants like it around the city)."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The cold appetizer dishes taste like the way I remember them to taste when I was growing up in Taiwan."], "output": "[['cold appetizer dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["delicious simple food in nice outdoor atmosphere."], "output": "[['food', 'food quality', 'positive'], ['food', 'food style_options', 'positive'], ['outdoor atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Kind, attentive wait staff."], "output": "[['wait staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I really like both the scallops and the mahi mahi (on saffron risotto-yum!)."], "output": "[['scallops', 'food quality', 'positive'], ['mahi mahi (on saffron risotto', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My friend devoured her chicken and mashed potatos."], "output": "[['chicken and mashed potatos', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Delicious crab cakes too."], "output": "[['crab cakes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Even if the food wasn't this good, the garden is a great place to sit outside and relax."], "output": "[['garden', 'ambience general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great neighborhood joint."], "output": "[['joint', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is a nice pizza place with good selection of thin crust pizza including the Basil slice."], "output": "[['selection of thin crust pizza', 'food style_options', 'positive'], ['selection of thin crust pizza', 'food quality', 'positive'], ['pizza place', 'restaurant general', 'positive'], ['Basil slice', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Their calzones are horrific, bad, vomit-inducing, YUCK."], "output": "[['calzones', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They smell like they stuff them with old canned vegetables like the spinach mushroom calzone."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The counter service is bad."], "output": "[['counter service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They charge different prices all the time."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They're rude at times, and not very friendly."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["NO PIZZA 33 for me!"], "output": "[['PIZZA 33', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Anybody who likes this place must be from a different planet, where greasy, dry and tasteless are complimentary."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The dosas are skimpy, unattractive and drip with grease, and personally I'd drink popcorn topping before I'd eat another one of these."], "output": "[['dosas', 'food style_options', 'negative'], ['dosas', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sandwiches are dry, tasteless and way overpriced."], "output": "[['sandwiches', 'food quality', 'negative'], ['sandwiches', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Calling the place Hampton Chutney Co. does warn you that these folks offer more style than substance, but in this unattractive room with unhelpful clerks there was a dearth of the former too."], "output": "[['place', 'restaurant general', 'negative'], ['room', 'ambience general', 'negative'], ['clerks', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Seriously, this place kicks ass."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The atmosphere is unheralded, the service impecible, and the food magnificant."], "output": "[['atmosphere', 'ambience general', 'positive'], ['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Best Italian food I ever had (and being Italian, that means alot)."], "output": "[['Italian food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is nearly impossible to get a table, so if you ever have the chance to go here for dinner, DO NOT pass it up."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is such a lovely, peaceful place to eat outside."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The restaurant looks out over beautiful green lawns to the Hudson River and the Statue of Liberty."], "output": "[['restaurant', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is set far from the small street it's on, and there is no traffic noise."], "output": "[['NULL', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is good, especially their more basic dishes, and the drinks are delicious."], "output": "[['food', 'food quality', 'positive'], ['basic dishes', 'food quality', 'positive'], ['drinks', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is a great place to take out-of-towners, and perfect for watching the sunset."], "output": "[['place', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great sushi experience."], "output": "[['sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Nice value."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Unique apppetizers."], "output": "[['apppetizers', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try sushimi cucumber roll."], "output": "[['sushimi cucumber roll', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good spreads, great beverage selections and bagels really tasty."], "output": "[['spreads', 'food quality', 'positive'], ['beverage selections', 'drinks style_options', 'positive'], ['bagels', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["THE BIG COMPLAINT: NO TOASTING AVAILABLE."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Murray won't do it."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But who says Murray's is anything about service."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["So close, but not good enough."], "output": "[['NULL', 'restaurant general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Don't be fooled by crowds of people."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service is awful."], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is not worth the prices."], "output": "[['place', 'restaurant general', 'negative'], ['place', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Also, don't plan on asking for your favorite roll, if it's not on the menu, you can't have it."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Love Pizza 33.."], "output": "[['Pizza 33', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will be out with friends and all of a sudden I am hungry and I only crave one thing... their Pizza."], "output": "[['Pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It hits the spot every time"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This tiny Williamsburg spot is always pleasantly surprising."], "output": "[['Williamsburg spot', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pizza is delicious and the proprietor is one of the nicest in NYC."], "output": "[['pizza', 'food quality', 'positive'], ['proprietor', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've been many time and have never been disappointed."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They even scoop it out nice (for those on a diet) not too much not to little."], "output": "[['NULL', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The cream cheeses are out of this world and I love that coffee!!"], "output": "[['cream cheeses', 'food quality', 'positive'], ['coffee', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A little crowded but they move that line really fast!"], "output": "[['NULL', 'service general', 'positive'], ['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A little pricey but it really hits the spot on a Sunday morning!"], "output": "[['NULL', 'restaurant prices', 'negative'], ['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Bagels are ok, but be sure not to make any special requests!"], "output": "[['Bagels', 'food quality', 'neutral'], ['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I asked for an open faced cheese sandwich and the manager basically told me to take my business elsewhere!"], "output": "[['manager', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Be sure not to get anything other than bagels!.."], "output": "[['NULL', 'food quality', 'negative'], ['bagels', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the turkey burgers are scary!"], "output": "[['turkey burgers', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The worst excuse for Japanese food I've ever encountered."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The soup for the udon was soy sauce and water."], "output": "[['soup for the udon', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The sushi was awful!"], "output": "[['sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The rice was poor quality and was cooked so badly it was hard."], "output": "[['rice', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Furthermore, the rice had no seasoning, so the sushi was bland and disgusting."], "output": "[['rice', 'food quality', 'negative'], ['sushi', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The fish was adequate, but inexpertly sliced."], "output": "[['fish', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is obvious that no one in the restaurant has any idea about or experience with Japanese cuisine."], "output": "[['Japanese cuisine', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good, fast service."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I would highly recommend."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food is great and inexpensive."], "output": "[['Food', 'food quality', 'positive'], ['Food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The location is perfect."], "output": "[['location', 'location general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Give it a try and enjoy."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Well, this place is so Ghetto its not even funny."], "output": "[['place', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you'll love it here."], "output": "[['bottle', 'drinks prices', 'negative'], ['music', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Would NEVER go back there."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Awsome Pizza especially the Margheritta slice."], "output": "[['Pizza', 'food quality', 'positive'], ['Margheritta slice', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Always busy but fast moving."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great atmoshere and worth every bit."], "output": "[['atmoshere', 'ambience general', 'positive'], ['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Open late (well as late as I ever got there and I'm a night person)"], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Winnie and her staff are the best crew you can find serving you."], "output": "[['staff', 'service general', 'positive'], ['Winnie', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is reliable and the price is moderate."], "output": "[['food', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["What more can you ask for?"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["For authentic Thai food, look no further than Toons."], "output": "[['Thai food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Try the Pad Thai, or sample anything on the appetizer menu...they're all delicious."], "output": "[['Pad Thai', 'food quality', 'positive'], ['appetizer menu', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everything about this restaurant was special."], "output": "[['restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was attentive, yet discreet."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The flavors robust and subtle."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The brioche and lollies as party favors is a cute and sweet touch to a most memorable meal."], "output": "[['brioche and lollies', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm saving up for my next visit."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place was quiet and delightful."], "output": "[['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was good and food is wonderful."], "output": "[['Service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I did not try the caviar but I tried their salmon and crab salad (they are all good) "], "output": "[['salmon', 'food quality', 'positive'], ['crab salad', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is definitely a good spot for snacks and chat."], "output": "[['spot', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["As a retired hipster, I can say with some degree of certainty that for the last year Lucky Strike has been the best laid-back late night in the city."], "output": "[['Lucky Strike', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wait staff is pleasant, fun, and for the most part gorgeous (in the wonderful aesthetic beautification way, not in that she's-way-cuter-than-me-that-b@#$* way)."], "output": "[['wait staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is yummy, especially their cooked-to-perfection mussels in spicy tomato sauce and their shoestring crispy fries."], "output": "[['food', 'food quality', 'positive'], ['mussels in spicy tomato sauce', 'food quality', 'positive'], ['fries', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But the best part about LS is the late night atmosphere, delightfully free of the BTs."], "output": "[['late night atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You can get a completely delish martini in a glass (that's about 2 1/2 drinks) for $8.50 (I recommend the Vanilla Shanty, mmmm!) in a great homey setting with great music."], "output": "[['martini', 'drinks quality', 'positive'], ['martini', 'drinks style_options', 'positive'], ['martini', 'drinks prices', 'positive'], ['Vanilla Shanty', 'drinks quality', 'positive'], ['setting', 'ambience general', 'positive'], ['music', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The in-house lady DJ on Saturday nights has outrageously good taste in music, and moreover, takes requests."], "output": "[['in-house lady DJ', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You can't go wrong with this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Suan is a great place that I often take my friends (classmates) too."], "output": "[['Suan', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Its location is good and the fact that Hutner College is near and their prices are very reasonable, makes students go back to Suan again and again."], "output": "[['location', 'location general', 'positive'], ['Suan', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I LOVE their Thai"], "output": "[['Thai', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["noodles with shrimp and chicken and coconut juice is the MUST!"], "output": "[['noodles with shrimp and chicken and coconut juice', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I will go back to Suan soon!"], "output": "[['Suan', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["In summer-eat outside on a terrace (another great feature of Suan)!!!"], "output": "[['terrace', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I cannot imagine a friendlier staff working in a restaurant."], "output": "[['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I cannot imagine better Indian food in all of the city."], "output": "[['Indian food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I cannot imagine you not rushing out to eat there."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["During the course of the past 3 months, the chef and staff changed and it was not for the better."], "output": "[['chef', 'food quality', 'negative'], ['staff', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I wish they would change back to what it was before."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food now is inconsistent."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is the kind of place you'd like to take all your friends to and still keep a secret."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The setting is casual and romantic."], "output": "[['setting', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Prices are very good."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is excellent! "], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["if you're daring, try the balsamic vinegar over icecream, it's wonderful!"], "output": "[['balsamic vinegar over icecream', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Do not get the Go Go Hamburgers, no matter what the reviews say."], "output": "[['Go Go Hamburgers', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They were such a rip-off ($8.95 for four small meat patties in steamed buns) and not worth trying."], "output": "[['NULL', 'food quality', 'negative'], ['NULL', 'food style_options', 'negative'], ['NULL', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The rest of the dim sum, though pricey by Chinatown standards, is worth it."], "output": "[['dim sum', 'food prices', 'negative'], ['dim sum', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Steamed fresh so brought hot hot hot to your table."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wait here is long for dim sum, but if you don't like sharing tables or if the typical raucous dim sum atmosphere is not your gig, this is a sleek (for Chinatown) alternative."], "output": "[['wait', 'service general', 'negative'], ['atmosphere', 'ambience general', 'negative'], ['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A few tips: skip the turnip cake, roast pork buns and egg custards."], "output": "[['turnip cake', 'food quality', 'negative'], ['roast pork buns', 'food quality', 'negative'], ['egg custards', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["These are overpriced and you can get better just around the corner:"], "output": "[['NULL', 'food prices', 'negative'], ['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I was pleasantly suprised."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was exceptional."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I choose to go with one of the special, the braised lamb shank in red wine, which was excellent."], "output": "[['braised lamb shank in red wine', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was friendly and the atmosphere was casual."], "output": "[['service', 'service general', 'positive'], ['atmosphere', 'ambience general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The restaurant is a bit noisy but that is something that can be overlooked once you sit down and enjoy a great meal"], "output": "[['meal', 'food quality', 'positive'], ['restaurant', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["this little place has a cute interior decor and affordable city prices."], "output": "[['interior decor', 'ambience general', 'positive'], ['place', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the pad se ew chicken was delicious, however the pad thai was far too oily."], "output": "[['pad se ew chicken', 'food quality', 'positive'], ['pad thai', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Have eaten at Ginger House several times, and it's always good."], "output": "[['Ginger House', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The fried dumplings are GREAT!"], "output": "[['fried dumplings', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Finally a reliable Chinese restaurant!"], "output": "[['Chinese restaurant', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place would be so much better served by being run by a group that actually understands customer service."], "output": "[['customer service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They are not helpful in the least and will give you the grand run around so by the time the event date rolls around you will not only regret chosing this place, but also become hostile!"], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Nobody at this restaurant will give firm answers about anything and in the end, not one person takes responsibility for anything."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Terrible, terrible management - deserves to be shut-down."], "output": "[['management', 'service general', 'negative'], ['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Never fails to please."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["delicious bagels, especially when right out of the oven."], "output": "[['bagels', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Spreads and toppings are great - though a bit pricey."], "output": "[['Spreads', 'food quality', 'positive'], ['toppings', 'food quality', 'positive'], ['Spreads', 'food prices', 'negative'], ['toppings', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service is fast and friendly."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Only drawback - they won't toast your bagel, and they don't make eggs for the bagel."], "output": "[['NULL', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But that is highly forgivable."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is decent at best, and the ambience, well, it's a matter of opinion, some may consider it to be a sweet thing, I thought it was just annoying."], "output": "[['food', 'food quality', 'negative'], ['ambience', 'ambience general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If celebrities make you sweat, then your in for a ride, but if your like most around these parts then you'll just yawn and wonder whats with all the hype."], "output": "[['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Rao is a good restaurant, but it's nothing special."], "output": "[['Rao', 'restaurant general', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But after last night, Spice Grill is the only place I'm eating indian cuisine."], "output": "[['indian cuisine', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["You must try the shrimp appetizers."], "output": "[['shrimp appetizers', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Even my Indian friend couldn't believe how good and tasty everything was."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place has the the correct ambience and an excellent staff to make you feel like a guest and a friend at the same time."], "output": "[['ambience', 'ambience general', 'positive'], ['staff', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great food, great prices, great service."], "output": "[['food', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you are looking for a good quality, cheap eats - this is the place."], "output": "[['eats', 'food quality', 'positive'], ['eats', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["it's a perfect place to have a amanzing indian food."], "output": "[['indian food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I really loved the different and inovated touch that's the cheff gives to the food."], "output": "[['cheff', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["also it's great to have dinner in a very romantic and confortable place, the service it's just perfect...they're so frendly that we never want to live the place!"], "output": "[['place', 'ambience general', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Their bagels are fine, but they are a little overcooked, and not really a 'special' bagel experience."], "output": "[['bagels', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great bagels made the old-fashioned way."], "output": "[['bagels', 'food quality', 'positive'], ['bagels', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Drawbacks: service is slow and they don't toast!"], "output": "[['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was absolutely amazing!!"], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The baked clams octopus we shared as appetizers were the best we've ever had!! "], "output": "[['baked clams octopus', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The lamb was tender so full of flavor, the dessert was divine!!"], "output": "[['lamb', 'food quality', 'positive'], ['dessert', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The waiter was attentive."], "output": "[['waiter', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The place itself is beautiful the bar scene seems to be happening."], "output": "[['place', 'ambience general', 'positive'], ['bar scene', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Downtown Dinner 2002 - Prixe fix: Appetizers were ok, waiter gave me poor suggestion..try the potato stuff kanish best one."], "output": "[['Appetizers', 'food quality', 'neutral'], ['waiter', 'service general', 'negative'], ['potato stuff kanish', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Small servings for main entree, i had salmon (wasnt impressed) girlfriend had chicken, it was good."], "output": "[['salmon', 'food quality', 'negative'], ['chicken', 'food quality', 'positive'], ['servings for main entree', 'food general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Dessert is a joke...dont bother"], "output": "[['Dessert', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Volare virgins or weekly regulars, everyone gets treated the same and you can't ask for more than that when the service is this friendly."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The restaurant has a Family feel, not least with regard to the portions which are enormous; the veal alone could have single-handedly solved third world famine."], "output": "[['restaurant', 'ambience general', 'positive'], ['portions', 'food style_options', 'positive'], ['veal', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The anti-pasta was excellent, especially the calamari, as were the filling pasta mains."], "output": "[['anti-pasta', 'food quality', 'positive'], ['calamari', 'food quality', 'positive'], ['pasta mains', 'food quality', 'positive'], ['pasta mains', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The wine list is extensive and can easily hike up an otherwise reasonably priced meal."], "output": "[['wine list', 'drinks style_options', 'positive'], ['meal', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Still, any quibbles about the bill were off-set by the pour-your-own measures of liquers which were courtesey of the house..."], "output": "[['NULL', 'restaurant prices', 'neutral'], ['measures of liquers', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Fantastic place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Cute and decorative."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A pleasant surprise."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go there to relax and feel like your somewhere else."], "output": "[['NULL', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Lucky Strike is a great casual place to just grab a bite to eat."], "output": "[['Lucky Strike', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great food, great decor, great service."], "output": "[['food', 'food quality', 'positive'], ['decor', 'ambience general', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I recommend it!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is the perfect spot for meeting friends, having lunch, dinner, pre-theatre or after-theatre drinks!"], "output": "[['spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["(Always ask the bartender for the SEASONAL beer!!!"], "output": "[['SEASONAL beer', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Guaranteed to be a tasty experience!)"], "output": "[['NULL', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Excellent spot for holiday get togethers with co-workers or friends that you haven't seen in a while."], "output": "[['spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have been doing all of the above at the Heartland Brewery for over 5 years now and I HAVE NEVER BEEN DISAPPOINTED!"], "output": "[['Heartland Brewery', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["All the people that I bring there go back on their own and bring THEIR friends!"], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go there once and oh yes...you will go back...you will..."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["What a great place!"], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not the typical NYC gimmick theme restaurant."], "output": "[['restaurant', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A cool bar with great food, and tons of excellent beer."], "output": "[['bar', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['beer', 'drinks quality', 'positive'], ['beer', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["And even with it's Pub atmosphere they were great to my kids too!"], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Loved it!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The shrimp scampi was excellent and the antipasti were plentiful."], "output": "[['shrimp scampi', 'food quality', 'positive'], ['antipasti', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It is expensive but well worth the money."], "output": "[['NULL', 'restaurant prices', 'negative'], ['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If you venture off the island of Manhattan and can't seem to find a great Italian restaurant, drive to Corona."], "output": "[['Corona', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The only thing more wonderful than the food (which is exceptional) is the service."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The only thing the waiters don't do for you is wipe your chin when you leave."], "output": "[['waiters', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wonderful at holiday time."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Cozy romantic atomosphere with only around 15 tables at most."], "output": "[['atomosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service was very prompt but slightly rushed."], "output": "[['Service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was very good, but not what I would consider out of this world."], "output": "[['Food', 'food quality', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Go here for a romantic dinner but not for an all out wow dining experience."], "output": "[['NULL', 'ambience general', 'positive'], ['NULL', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My friend from Milan and myself were pleasantly surprised when we arrived and everyone spoke italian."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Too bad the food wasn't of the same heritage."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The porcini mushroom pasta special was tasteless, so was the seafood tagliatelle."], "output": "[['porcini mushroom pasta special', 'food quality', 'negative'], ['seafood tagliatelle', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A real dissapointment."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["But that wasn't the icing on the cake: a tiramisu that resembled nothing I have ever had."], "output": "[['tiramisu', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They should have called it mascarpone with chocolate chips-good but a far cry from what the name implies."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Priced at upper intermediate range."], "output": "[['NULL', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I really liked this place."], "output": "[['place', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Everything I had was good, and I'm a eater."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was pretty inexpensive too."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place has the best Chinese style BBQ ribs in the city."], "output": "[['BBQ ribs', 'food quality', 'positive'], ['BBQ ribs', 'food style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I also recommend the rice dishes or the different varieties of congee (rice porridge)."], "output": "[['rice dishes', 'food quality', 'positive'], ['congee (rice porridge)', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's great to go for a quick lunch either alone or with a friend."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's definately not a place to go if you want to impress someone."], "output": "[['place', 'restaurant miscellaneous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["However, if you want great food at a great price and don't mind the decor, you can't beat this place."], "output": "[['food', 'food quality', 'positive'], ['decor', 'ambience general', 'neutral'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Quick and friendly service."], "output": "[['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is one of the best comfort food places in the city."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It's somewhere you can eat and be happy."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["When you're sitting in their main dining room (which has a spectacular, hand-painted high ceiling) you'd never know there was a world outside."], "output": "[['main dining room', 'ambience general', 'positive'], ['ceiling', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is wonderful, tasty and filling, and the service is professional and friendly."], "output": "[['food', 'food quality', 'positive'], ['food', 'food style_options', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I can't wait for summer, when they serve outside on their gigantic patio."], "output": "[['patio', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I recently tried Suan and I thought that it was great."], "output": "[['Suan', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This little place definitely exceeded my expectations and you sure get a lot of food for your money."], "output": "[['food', 'food style_options', 'positive'], ['place', 'restaurant general', 'positive'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals."], "output": "[['service', 'service general', 'positive'], ['food', 'food quality', 'positive'], ['hot sauce', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have to say that I am pleasantly suprised and I will most likely stop in again if I am in the neighborhood."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["They all know you."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good food."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good drink."], "output": "[['drink', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["How do you rate home?"], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have never had cheescake like this."], "output": "[['cheescake', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I thought I had died and gone to heaven."], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great spot, whether looking for a couple of drinks or quiet dinner."], "output": "[['spot', 'restaurant general', 'positive'], ['spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Warm and friendly in the winter and terrific outdoor seating in the warmer months."], "output": "[['NULL', 'ambience general', 'positive'], ['outdoor seating', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is great and they have a good selecion of wines at reasonable prices."], "output": "[['food', 'food quality', 'positive'], ['wines', 'drinks style_options', 'positive'], ['wines', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Have been several times and it never dissapoints."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were less than impressed."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["While the ambiance and atmosphere were great, the food and service could have been a lot better."], "output": "[['ambiance', 'ambience general', 'positive'], ['atmosphere', 'ambience general', 'positive'], ['food', 'food quality', 'negative'], ['service', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["We ordered the chicken casserole, but what we got were a few small pieces of chicken, all dark meat and on the bone."], "output": "[['chicken casserole', 'food quality', 'negative'], ['chicken casserole', 'food style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Probably would not go again..."], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["i've been to sapphire twice and both times the food was fine, if not good."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["stick with the chicken, beef, and lamb dishes."], "output": "[['chicken', 'food quality', 'positive'], ['beef', 'food quality', 'positive'], ['lamb dishes', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["service is friendly, and never had a problem walking in and getting a table."], "output": "[['service', 'service general', 'positive'], ['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["skip dessert."], "output": "[['dessert', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Best Reuben sandwich ever!"], "output": "[['Reuben sandwich', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["A classic!"], "output": "[['NULL', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Don't miss Bloom's on your next trip to Manhatten."], "output": "[[\"Bloom's\", 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It was the first place we ate on our first trip to New York, and it will be the last place we stop as we head out of town on our next trip to New York."], "output": "[['place', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Thanks Bloom's for a lovely trip."], "output": "[[\"Bloom's\", 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was not fresh, the sauces were bland and very oily."], "output": "[['food', 'food quality', 'negative'], ['sauces', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["It just wasn't Thai."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Was surprisingly disappointed."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Pizza was a little soggy."], "output": "[['Pizza', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ravioli was good...but I have to say that I found everything a bit overpriced."], "output": "[['Ravioli', 'food quality', 'positive'], ['NULL', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Not enough wines by the glass either."], "output": "[['wines by the glass', 'drinks style_options', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Service, however, was excellent...and I liked the setting/atmosphere a lot. "], "output": "[['Service', 'service general', 'positive'], ['setting/atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was just average...if they lowered the prices just a bit, it would be a bigger draw."], "output": "[['Food', 'food quality', 'neutral'], ['NULL', 'restaurant prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This place is a great bargain."], "output": "[['place', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Authentic Pakistani food."], "output": "[['Pakistani food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["People are always friendly."], "output": "[['People', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Just straight up cheap, good food."], "output": "[['food', 'food quality', 'positive'], ['food', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Faan is sooo good."], "output": "[['Faan', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The best pad thai i've ever had."], "output": "[['pad thai', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The design and atmosphere is just as good."], "output": "[['design', 'ambience general', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["bottles of wine are cheap and good."], "output": "[['bottles of wine', 'drinks prices', 'positive'], ['bottles of wine', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["What more could you want?"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was actually aweful."], "output": "[['food', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I'm not picky - but it was actually gross."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The mussles were the fishiest things I've ever tasted, the seabass was bland, the goat cheese salad was missing the goat cheese, the penne w/ chicken had bones in it... It was disgusting."], "output": "[['mussles', 'food quality', 'negative'], ['seabass', 'food quality', 'negative'], ['goat cheese salad', 'food quality', 'negative'], ['penne w/ chicken', 'food quality', 'negative'], ['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Nice atmosphere, the service was very pleasant and the desert was good."], "output": "[['atmosphere', 'ambience general', 'positive'], ['service', 'service general', 'positive'], ['desert', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wouldn't recomend it for dinner!"], "output": "[['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is the perfect date spot for Williamsburg couples."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The jukebox plays everything from Italian Opera to The Strokes."], "output": "[['jukebox', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is amazing, rich pastas and fresh doughy pizza."], "output": "[['food', 'food quality', 'positive'], ['pastas', 'food style_options', 'positive'], ['pizza', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Best of all is the warm vibe, the owner is super friendly and service is fast."], "output": "[['vibe', 'ambience general', 'positive'], ['owner', 'service general', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["If only they delivered, they'd make a mint!"], "output": "[['NULL', 'restaurant miscellaneous', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["go here for the drinks!"], "output": "[['drinks', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["the drinks are amazing and half off till 8pm."], "output": "[['drinks', 'drinks quality', 'positive'], ['drinks', 'drinks prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["Ask for Usha, the nicest bartender in manhattan."], "output": "[['Usha', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["My fav was the sassy lassi..."], "output": "[['sassy lassi', 'drinks quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["This is an amazing place to try some roti rolls."], "output": "[['roti rolls', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} {"task_type": "generation", "dataset": "semeval-2015", "input": ["I really recommend the very simple Unda (Egg) rolls."], "output": "[['Unda (Egg) rolls', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}