{"task_type": "generation", "dataset": "semeval-2015", "input": ["Love Al Di La"], "output": "[['Al Di La', '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 recommend this place to everyone."], "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."], "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": ["One of my favorite places in Brooklyn. "], "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 pastas are incredible, the risottos (particularly the sepia) are fantastic and the braised rabbit is amazing."], "output": "[['pastas', 'food quality', 'positive'], ['risottos', 'food quality', 'positive'], ['sepia', 'food quality', 'positive'], ['braised rabbit', '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": ["Overpriced and not tasty "], "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": ["The food here was mediocre at best. "], "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 was totally overpriced- fish and chips was about $15.... "], "output": "[['NULL', 'food prices', 'negative'], ['fish and chips', '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": ["Tasty Dog!"], "output": "[['Dog', '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": ["An awesome organic dog, and a conscious eco friendly establishment."], "output": "[['dog', 'food quality', 'positive'], ['establishment', '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": ["One of the best hot dogs I have ever eaten."], "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": ["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 Cypriot restaurant has a lot going for it."], "output": "[['Cypriot 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": ["But the best pork souvlaki I ever had is the main thing."], "output": "[['pork souvlaki', '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": ["Run don't walk."], "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": ["Super YUMMY 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": ["I was visiting New York City with a friend and we discovered this really warm and inviting 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": ["I LOOOVE their eggplant pizza, as well as their pastas!"], "output": "[['eggplant pizza', 'food quality', 'positive'], ['pastas', '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 half/half pizza, mine was eggplant and my friend had the buffalo and it was sooo huge for a small size pizza!"], "output": "[['half/half pizza', '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 had fun eating in there, we were there like around 3 a.m. in the morning!"], "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": ["Will comeback for sure, wish they have it here in LA.."], "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": ["Excellent food, although the interior could use some help."], "output": "[['food', 'food quality', 'positive'], ['interior', '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 space kind of feels like an Alice in Wonderland setting, without it trying to be that."], "output": "[['space', '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 paid just about $60 for a good meal, though :)"], "output": "[['meal', 'food quality', '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": ["Great sake!"], "output": "[['sake', '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": ["Reliable, Fresh Sushi"], "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 sashimi is always fresh and the rolls are innovative and delicious."], "output": "[['sashimi', 'food quality', 'positive'], ['rolls', 'food style_options', 'positive'], ['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": ["Have never had a problem with service save a missing rice once."], "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": ["Delivery can be spot on or lacking depending on the weather and the day of the week."], "output": "[['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": ["Delivery guy sometimes get upset if you don't tip more than 10%."], "output": "[['Delivery guy', '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": ["Best. Sushi. Ever."], "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": ["This place has ruined me for neighborhood sushi."], "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": ["Creative, consistent, fresh."], "output": "[['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": ["Excellent sashimi, and the millennium roll is beyond delicious."], "output": "[['sashimi', 'food quality', 'positive'], ['millennium 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": ["Not cheap but very yummy."], "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": ["Love 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": ["Very, very nice"], "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 bit hidden away, but once you get there, it's all worth it."], "output": "[['place', 'location general', 'neutral'], ['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 only is the food"], "output": "[['food', 'food quality', '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": ["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": ["We had a very nice 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": ["The waiter was attentive, the food was delicious and the views of the city were great."], "output": "[['waiter', 'service general', 'positive'], ['food', 'food quality', 'positive'], ['views of the city', '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": ["I'd definitely 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": ["Great place to relax and enjoy your dinner"], "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": ["There is something about their atmosphere that makes me come back nearly every week."], "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": ["Place is open till late, no dress code."], "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": ["Good food: my favorite is the seafood spaghetti."], "output": "[['food', 'food quality', 'positive'], ['seafood spaghetti', '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": ["Excellent food for great prices"], "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": ["My husband and I have been sold on this from the first 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 wait staff is very courteous and accomodating."], "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 space is limited so be prepared to wait up to 45 minutes - 1 hour, but be richly rewarded when you savor the delicious indo-chinese food."], "output": "[['space', 'ambience general', 'neutral'], ['space', 'restaurant miscellaneous', 'negative'], ['indo-chinese 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 are no negatives to speak of."], "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 bestt!"], "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 favorite place lol"], "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 love their chicken pasta cant remember the name but is sooo good"], "output": "[['chicken 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": ["its alright"], "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": ["im not necessarily fanatical about this place, but it was a fun time for low pirces."], "output": "[['place', 'restaurant 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": ["lobster was good, nothing spectacular."], "output": "[['lobster', '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": ["its just a fun place to go, not a five star restaraunt."], "output": "[['restaraunt', '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": ["Way below average"], "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 the pizza is so overrated and was under cooked."], "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": ["Had no flavor and the staff is rude and not attentive."], "output": "[['staff', 'service general', '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": ["Would NEVER 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": ["I 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 wasn't here for the pizza so I can't comment on that yet but what I had was very 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": ["The service was quick 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": ["Everyone was smiling so that made me feel welcome."], "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": ["I thought the restaurant was nice and clean."], "output": "[['restaurant', 'restaurant general', '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": ["I ordered the vitello alla marsala and I was pretty impressed."], "output": "[['vitello alla marsala', '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 veal and the mushrooms were cooked perfectly."], "output": "[['veal', 'food quality', 'positive'], ['mushrooms', '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 potato balls were not dry at all... in fact it was buttery."], "output": "[['potato balls', '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 only downside... they only take cash which is OK if you know about it ahead of time."], "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'll be back for sure."], "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": ["WORST PLACE ON SMITH STREET IN BROOKLYN"], "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": ["Very immature bartender, didnt know how to make specific drinks, service was so slowwwww, the food was not fresh or warm, waitresses were busy flirting with men at the bar and werent very attentive to all the customers."], "output": "[['bartender', 'service general', 'negative'], ['service', 'service general', 'negative'], ['food', 'food quality', 'negative'], ['waitresses', '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 would never recommend this place to anybody even for a casual dinner."], "output": "[['place', 'restaurant general', 'negative'], ['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": ["awesome"], "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 always fresh ..."], "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": ["overpriced japanese food with mediocre service"], "output": "[['japanese food', 'food prices', 'negative'], ['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": ["Went here on sat 1/26 and was disappointed."], "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": ["Chicken teriyaki had tomato or pimentos on top??"], "output": "[['Chicken teriyaki', '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": ["food was luke warm."], "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 waitress was not attentive at all."], "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": ["I was looking for banana tempura for dessert and they dont have."], "output": "[['dessert', '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": ["Not because you are \"The Four Seasons\"... \u2013 you are allowed to charge an arm and a leg for a romatic dinner."], "output": "[['The Four Seasons', '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 food was excellent as well as service, however, I left The Four Seasons very dissappointed."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['The Four Seasons', '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 do not think dinner in Manhattan should cost $400.00 where I am not swept off my feet."], "output": "[['dinner', '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": ["Red Dragon Roll - my favorite thing to eat, of any food group - hands down"], "output": "[['Red Dragon 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": ["Just go to Yamato and order the Red Dragon Roll."], "output": "[['Yamato', 'restaurant general', 'positive'], ['Red Dragon 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": ["If you don't like it, I don't know what to tell you."], "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 Seafood Dynamite is also otherworldly."], "output": "[['Seafood Dynamite', '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 not even going to bother to describe it; it speaks for itself."], "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": ["Favorite Sushi in NYC"], "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": ["An unpretentious spot in Park Slope, the sushi is consistently good, the service is pleasant, effective and unassuming."], "output": "[['spot', 'ambience general', 'positive'], ['sushi', '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": ["In the summer months, the back garden area is really nice."], "output": "[['back garden 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": ["The rolls are creative and I have yet to find another sushi place that serves up more inventive yet delicious japanese food."], "output": "[['rolls', 'food style_options', 'positive'], ['japanese food', 'food style_options', 'positive'], ['japanese 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 Dancing, White River and Millenium rolls are musts."], "output": "[['Dancing, White River and Millenium 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": ["SO GOOD"], "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 CAN EAT HERE EVERY DAY OF THE WEEK REALLY LOL 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": ["Gross food \u2013 Wow-"], "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 can't remember the last time I had such gross food in New York."], "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": ["My quesadilla tasted like it had been made by a three-year old with no sense of proportion or flavor."], "output": "[['quesadilla', 'food quality', 'negative'], ['quesadilla', '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": ["And $11 for a plate of bland guacamole?"], "output": "[['guacamole', 'food quality', 'negative'], ['guacamole', '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": ["Don't get me started on the margaritas, either."], "output": "[['margaritas', 'drinks 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": ["Mine tasted like the bartender had forgotten to add the tequila."], "output": "[['NULL', 'drinks 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": ["Save your money and your time and go somewhere else."], "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": ["Oh, and I never write reviews--I just was so moved by how bad this place was, I felt it was my duty to spread the word."], "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": ["Great 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": ["When I got there the place was packed but they made sure to seat me quickly."], "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 food was good, the place was clean and affordable."], "output": "[['food', 'food quality', 'positive'], ['place', '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": ["I noticed alot of indian people eatting there which is a great sign for an indian place!"], "output": "[['indian 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": ["This is one of my favorite spot, very relaxing the food is great all the times , celebrated my engagement and my wedding here , it was very well organized ."], "output": "[['NULL', 'restaurant general', 'positive'], ['NULL', 'ambience general', 'positive'], ['food', 'food quality', '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": ["The staff is very good."], "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": ["Love their drink menu."], "output": "[['drink 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": ["I highly recommend this beautiful place."], "output": "[['place', 'ambience general', '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": ["Nice for one time special occasion."], "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": ["They honored reservation on Sunday afternoon very well. "], "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": ["We were offered water for the table but were not told the Voss bottles of water were $8 a piece."], "output": "[['Voss bottles of water', '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 OK."], "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": ["Nice view of river and NYC."], "output": "[['view of river and NYC', '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": ["I come here enjoy very much with husband."], "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": ["Remind me of 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": ["Great survice"], "output": "[['survice', '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": ["MMMMMMMMMmmmmmm so 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": ["A beautifully designed dreamy Egyptian restaurant that gets sceney at night."], "output": "[['Egyptian 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": ["Watch the talented belly dancers as you enjoy delicious baba ganoush that's more lemony than smoky."], "output": "[['baba ganoush', 'food quality', 'positive'], ['belly dancers', '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": ["Oh, and there's hookah."], "output": "[['hookah', '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": ["Raymond the bartender rocks!"], "output": "[['Raymond', '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": ["Pacifico is a great place to casually hang out."], "output": "[['Pacifico', '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 drinks are great, especially when made by Raymond."], "output": "[['drinks', 'drinks quality', 'positive'], ['Raymond', '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 omlette for brunch is great..."], "output": "[['omlette for brunch', '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 spinach is fresh, definately not frozen..."], "output": "[['spinach', '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": ["quacamole at pacifico is yummy, as are the wings with chimmichuri."], "output": "[['quacamole', 'food quality', 'positive'], ['wings with chimmichuri', '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 weakness is the chicken in the salads."], "output": "[['chicken in the salads', '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's just average, just shredded, no seasoning on it."], "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": ["Also, I personally wasn't a fan of the portobello and asparagus mole."], "output": "[['portobello and asparagus mole', '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": ["Overall, decent food at a good price, with friendly people."], "output": "[['food', 'food quality', 'neutral'], ['food', 'food prices', 'positive'], ['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": ["Best Indian Restaurant in the City"], "output": "[['Indian 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": ["Decor needs to be upgraded but the food is amazing!"], "output": "[['Decor', '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": ["This small Astoria souvlaki spot makes what many consider the best gyros in New York."], "output": "[['gyros', '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": ["What really makes it shine is the food, which is aggressively seasoned with Cyrpriot spices, and all made in-house (even the gyro meat and sausages), and made of much higher quality ingredients that might otherwise be expected."], "output": "[['food', 'food quality', 'positive'], ['gyro meat', 'food quality', 'positive'], ['sausages', 'food quality', '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": ["All the various Greek and Cypriot dishes are excellent, but the gyro is the reason to come--if you don't eat one your trip was wasted."], "output": "[['Greek and Cypriot dishes', 'food quality', 'positive'], ['gyro', '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 restaurant in Brooklyn"], "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 best!"], "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 food, amazing service, this place is a class act."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', '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": ["The veal was incredible last night."], "output": "[['veal', '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": ["Fresh, mind blowing flavors."], "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 is a must visit!"], "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": ["Delicious, creative and fun."], "output": "[['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": ["Got a date? Go here!"], "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": ["Every time I have a special occasion with my boyfriend I have a hard time going anywhere else."], "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 is so romantic."], "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": ["Its dark, and cozy.. there is always jazz music playing when we go."], "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": ["Most of the booths allow you to sit next to eachother without looking like 'that' couple."], "output": "[['booths', '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 all shared so we get to order together and eat together."], "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": ["I've enjoyed 99% of the dishes we've ordered with the only exceptions being the occasional too-authentic-for-me dish (I'm a daring eater but not THAT daring)."], "output": "[['dishes', 'food quality', 'positive'], ['dish', '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": ["Once you try it for a special occasion beware.. you can't stop!"], "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": ["You'll be ther for every anniversary, birthday, valentines day..."], "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": ["For a Fabulous Wedding!"], "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": ["My daughter's wedding reception at Water's Edge received the highest compliments from our guests."], "output": "[[\"Water's Edge\", '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": ["Everyone raved about the atmosphere (elegant rooms and absolutely incomparable views) and the fabulous food!"], "output": "[['atmosphere', 'ambience general', 'positive'], ['rooms', 'ambience general', 'positive'], ['views', '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": ["Service was wonderful;"], "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": ["everyone was cheerfully cooperative and helpful."], "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": ["Paul, the maitre d', was totally professional and always on top of things."], "output": "[['Paul', '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": ["Thank you everyone at Water's Edge."], "output": "[[\"Water's Edge\", '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": ["would NOT 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": ["Service ok but unfriendly,filthy bathroom."], "output": "[['Service', 'service general', 'negative'], ['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": ["The high prices you're going to pay is for the view not for the food."], "output": "[['view', 'location general', 'neutral'], ['food', 'food quality', '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": ["The bar drinks were Eh, ok to say the least."], "output": "[['bar drinks', 'drinks 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 stuff tilapia was horrid...tasted like cardboard."], "output": "[['stuff tilapia', '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 the dessert would be better, Wrong!"], "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": ["$170 down the toilet..."], "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": ["oh speaking of bathroom , the mens bathroom was disgusting."], "output": "[['mens 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": ["The floor was wet, the trash can filled with hand towels n all over the floor, no soap, and no hand towels left."], "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": ["Good 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 wine list was extensive - though the staff did not seem knowledgeable about wine pairings."], "output": "[['wine list', 'drinks style_options', 'positive'], ['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 bread we received was horrible - rock hard and cold - and the \"free\" appetizer of olives was disappointing."], "output": "[['bread', 'food quality', 'negative'], ['appetizer of olives', 'food quality', 'negative'], ['appetizer of olives', 'food 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": ["However, our main course was wonderful."], "output": "[['main course', '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 fish and my husband had the filet - both of which exceeded our expectations."], "output": "[['fish', 'food quality', 'positive'], ['filet', '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 dessert (we had a pear torte) was good - but, once again, the staff was unable to provide appropriate drink suggestions."], "output": "[['pear torte', 'food quality', 'positive'], ['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": ["When we inquired about ports - the waitress listed off several but did not know taste variations or cost."], "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": ["Not what I would expect for the price and prestige of this location."], "output": "[['NULL', 'service general', 'negative'], ['location', 'restaurant prices', 'neutral'], ['location', '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": ["All in all, I would return - as it was a beautiful restaurant - but I hope the staff pays more attention to the little details in the future."], "output": "[['restaurant', 'restaurant general', 'positive'], ['restaurant', 'ambience general', 'positive'], ['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": ["short and sweet \u2013 seating is great:it's romantic,cozy and private."], "output": "[['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 boths are not as small as some of the reviews make them out to look they're perfect for 2 people."], "output": "[['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": ["The service was extremely fast and attentive(thanks to the service button on your table) but I barely understood 1 word when the waiter took our order."], "output": "[['service', 'service general', 'positive'], ['service button', 'service general', 'positive'], ['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": ["The food was ok and fair nothing to go crazy."], "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": ["Over all the looks of the place exceeds the actual meals."], "output": "[['looks', 'ambience general', 'positive'], ['meals', '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": ["So what you really end up paying for is the restaurant not the food."], "output": "[['restaurant', 'restaurant prices', 'negative'], ['restaurant', 'ambience general', 'neutral'], ['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": ["Will prob. not return but it is a great dinning experience to try atleast once."], "output": "[['NULL', 'restaurant general', '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": ["Impressed..."], "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": ["Subtle food and 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": ["Noodle pudding is exactly the type of service and food I enjoy."], "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": ["Servers are all different, Greg is my favorite."], "output": "[['Greg', '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": ["Sometimes tables don't understand his sense of humor but it's refreshing to have a server who has personality, professionalism, and respects the privacy of your dinner."], "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": ["This is the first place I've been that a runner remembers my order... hope he likes his job because I have half a mind to steal him for my restaurant."], "output": "[['runner', '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": ["Prices are fair across the board for both food and bev."], "output": "[['food', 'food prices', 'positive'], ['bev', '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": ["I go out to eat and like my courses, servers are patient and never rush courses or force another drink."], "output": "[['servers', '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": ["amazing fresh dogs but best of all endless toppings!!!"], "output": "[['dogs', 'food quality', 'positive'], ['toppings', '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 place had ALL the trimmings and i mean all."], "output": "[['trimmings', '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": ["peppers, onions, relish, chilli, cheeses, you NAME it."], "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": ["amazing fun for hot dog lovers of all ages PLEASE do yourself a favor and check this place out!!!!"], "output": "[['place', 'restaurant general', 'positive'], ['hot dog', '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 DINING EXPERIENCE IN THE WEST VILLAGE!"], "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": ["Stepping into Casa La Femme last night was a true experience unlike any other in New York!"], "output": "[['Casa La Femme', '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 impressed from the decor to the food to the hospitality to the great night I had!"], "output": "[['decor', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['NULL', 'service 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": ["The have a great cocktail with Citrus Vodka and lemon and lime juice and mint leaves that is to die for!"], "output": "[['cocktail with Citrus Vodka and lemon and lime juice and mint leaves', '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": ["Food took some time to prepare, all worth waiting for."], "output": "[['Food', 'food quality', 'positive'], ['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": ["We were drawn into the belly dancing show that captivated the crowd."], "output": "[['belly dancing show', '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 never write on these sites but this restaurant is def worth commending!"], "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": ["Great find in the West Village!"], "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": ["Maggot in 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": ["The menu looked great, and the waiter was very nice, but when the food came, it was average."], "output": "[['menu', 'food style_options', 'positive'], ['waiter', 'service 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": ["Nevertheless, I finished my plate, and that's when I found a maggot in mushroom sauce at the bottom."], "output": "[['mushroom sauce', '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 showed it to the manager, and he smilingly apologized and brought us two free desserts (but did not ask us what we wanted and so brought the last two desserts we would have asked for)."], "output": "[['manager', 'service general', 'positive'], ['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": ["When the bill came, nothing was comped, so I told the manager very politely that we were willing to pay for the wine, but I didn't think I should have to pay for food with a maggot in 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": ["The manager finally said he would comp the two glasses of wine (which cost less than the food), and made it seem like a big concession."], "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 paid and left because we didn't feel like arguing any more."], "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": ["I have worked in restaurants and cook a lot, and there is no way a maggot should be able to get into well prepared 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": ["For a restaurant with such a good reputation and that is usually so packed, there was no reason for such a lack of intelligent customer service."], "output": "[['restaurant', 'restaurant miscellaneous', 'positive'], ['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": ["Unhygienic"], "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": ["I do not recommend."], "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 got hair in my food 2 times of then !"], "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": ["Great place, great value."], "output": "[['place', 'restaurant 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 food is flavorful, plentiful and reasonably priced."], "output": "[['food', 'food quality', 'positive'], ['food', 'food style_options', '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 atmosphere is relaxed and casual."], "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": ["It's a great place to order from or sit-in."], "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": ["Awesome"], "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": ["Inexpensive, unassuming, great time!"], "output": "[['NULL', 'restaurant prices', 'positive'], ['NULL', '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": ["Sushi experience was unbelievable with my fiance."], "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": ["Try 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": ["Very pleased"], "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 creative rolls!"], "output": "[['rolls', 'food quality', 'positive'], ['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": ["Yamato is an excellent place to go if youre not into sashimi, or if you have friends who doesnt like sushi much."], "output": "[['Yamato', '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": ["They have great rolls, the triple color and norwegetan rolls, are awesome and filling."], "output": "[['rolls', 'food quality', 'positive'], ['triple color and norwegetan rolls', 'food quality', 'positive'], ['triple color and norwegetan 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": ["One special roll and one regular roll is enough to fill you up, but save room for dessert!"], "output": "[['dessert', 'food quality', 'positive'], ['special roll', 'food style_options', 'positive'], ['regular roll', '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 delicious banana chocolate dessert, as well as a great green tea tempura."], "output": "[['banana chocolate dessert', 'food quality', 'positive'], ['green tea 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": ["The appetizers are also delicious!"], "output": "[['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": ["Amazing 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": ["Mazing interior."], "output": "[['interior', '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 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": ["I've had my fair share of modern Japanese and this spot delivers."], "output": "[['modern Japanese', '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 was pretty nice but had a bit lacking, which it tries to make up for with a crazy scheme of mirrors."], "output": "[['atmosphere', 'ambience general', 'negative'], ['scheme of mirrors', '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're into being lost when you're just five feet from your table then hey, that's a good thing."], "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": ["Despite the confusing mirrors this will likely be my go-to for modern Japanese food for the foreseeable future."], "output": "[['modern Japanese food', 'food quality', 'positive'], ['mirrors', '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": ["Indo Chinese food, pretty good..."], "output": "[['Indo Chinese 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": ["Not a very fancy place but very good Chinese style Indian food."], "output": "[['place', 'ambience general', 'neutral'], ['Chinese style 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": ["The chicken lollipop is my favorite, most of the dishes (I have to agree with a previous reviewer) are quite oily and very spicy, espeically the Chilli Chicken."], "output": "[['chicken lollipop', 'food quality', 'positive'], ['dishes', 'food quality', 'negative'], ['Chilli Chicken', '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": ["My mom originally introduced me to this place, but even she (being Indian) feels the food can be somewhat over the top spicy and far too 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": ["Still we keep 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": ["I was speechless by the horrible 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": ["I attended a holiday dinner at the restaurant, and the food was majorly disappointing."], "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": ["Rather than preparing vegetarian dish, the chef presented me with a plate of steamed vegetables (minus sauce, seasoning, or any form or aesthetic presentation)."], "output": "[['chef', 'service general', 'negative'], ['vegetarian dish', 'food quality', 'negative'], ['vegetarian dish', '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 was so stunned, and I left the dinner hungry and majorly disappointing."], "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 survives on reputation alone."], "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": ["I will NEVER return."], "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": ["Best In ALL of NYC"], "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 MOST wonderful restaurant in all of New York City, not just Brooklyn..."], "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": ["for 7 years they have put out the most tasty, most delicious food and kept it that way..."], "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": ["never swaying, never a bad meal, never bad service..."], "output": "[['NULL', 'restaurant general', 'positive'], ['meal', '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": ["you should travel from the Bronx to try 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": ["great food, great wine list, great service in a great neighborhood..."], "output": "[['food', 'food quality', 'positive'], ['wine list', 'drinks style_options', 'positive'], ['service', 'service general', 'positive'], ['neighborhood', '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": ["so 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": ["Patsy's Pizza = true love"], "output": "[[\"Patsy's Pizza\", '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": ["Hands down the best pizza on the planet."], "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": ["In about 12 minutes, the thing is gone."], "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 hot dogs.."], "output": "[['hot dogs', '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 hot dogs were juicy and tender inside and had plenty of crunch and snap on the outside."], "output": "[['hot dogs', '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 toppings definitely a place you need to check out for late night munchies or a mid day boost!"], "output": "[['toppings', 'food quality', 'positive'], ['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": ["great taste"], "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, original taste."], "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": ["For me dishes a little oily, but overall dining experience good."], "output": "[['dishes', 'food quality', '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": ["Helpful service and average price per dish $10."], "output": "[['service', 'service general', 'positive'], ['dish', 'food 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": ["The only thing that strikes you is the decor?(not very pleasant)."], "output": "[['decor', '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 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": ["This place has great indian chinese food."], "output": "[['indian chinese 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 flavors are amazing and the value is phenomenal."], "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": ["Be prepared to wait, because the place is pretty tiny."], "output": "[['place', 'restaurant miscellaneous', 'negative'], ['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": ["Also, they do not take credit card so come with cash!"], "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": ["Even though the place is not beautiful, the food speaks for itself."], "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": ["Best Indian Chinese in the city, by far!"], "output": "[['Indian Chinese', '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": ["AMAZING MY 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 came across Village Underground by accident, now I go there all the time."], "output": "[['Village Underground', '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 martinis are amazing and very fairly priced."], "output": "[['martinis', 'drinks quality', 'positive'], ['martinis', '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": ["THE SERVICE IS AMAZING, i've had different waiters and they were all nice, which is a rare thing in NYC."], "output": "[['SERVICE', 'service general', '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": ["The DJ is awesome, I have been there for my birthday and a bunch of other times with friends and I keep going back."], "output": "[['DJ', '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": ["You can get a table without a reservation if you get there early I they don't make you by bottles."], "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": ["Which lets face it....at times it's a good thing."], "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": ["In the end you end up with a fair tab and NOTHING BUT A GREAT TIME!!!"], "output": "[['NULL', 'restaurant prices', '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": ["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": ["One of the best, if not THE best, restaurants in Park Slope (and NY in general)"], "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": ["Everything on the menu is great. "], "output": "[['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": ["This establishment is the real deal. "], "output": "[['establishment', '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": ["Wish NY had more of these kind of places: intimate, superb food, homey, top notch all the way around, certainly worth the wait."], "output": "[['NULL', 'ambience general', 'positive'], ['food', 'food quality', '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": ["But $500 for a dinner for two that didn't include Wine?"], "output": "[['dinner for two', '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": ["Look, the appetizers were really good."], "output": "[['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": ["The entree was also very good."], "output": "[['entree', '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 argue about that, but they are clearly over priced."], "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": ["What you are paying for is the environment and the name."], "output": "[['environment', 'ambience general', 'neutral'], ['NULL', 'restaurant miscellaneous', '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": ["Yes, the place is classy and beautiful, but they most certainly target the uber whealthy Not the common joe that wants to go all out every once in a while."], "output": "[['place', 'ambience general', 'positive'], ['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": ["Which of course is not real Kobe but Wagyu beef."], "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": ["Surprised that a place of this caliber would advertise it as Kobe."], "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": ["Vanison was good but not amazing."], "output": "[['Vanison', '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": ["Bison was quite excellent however."], "output": "[['Bison', '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": ["Dessert: pure disaster."], "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": ["Just not good at all."], "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": ["Some Pineapple covered in a glaze of some kind and some pear tart thing Not impressive at all."], "output": "[['NULL', 'food style_options', '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 read reviews that called the restaurant too expensive and I thought to myself, but may be it is worth it."], "output": "[['restaurant', 'restaurant prices', 'negative'], ['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 Four Seasons has history and it is a sort of landmark of New York City restaurants, but trust me, they will charge you through the nose just so that you can say \"I've been to the four seasons restaurant\"."], "output": "[['The Four Seasons', 'restaurant miscellaneous', 'neutral'], ['The Four Seasons', '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 wanted to go there to see if it was worth it and sadly, curiousity got the best of me and I paid dearly for it."], "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": ["All in all, the food was great (except for the dessserts)."], "output": "[['food', 'food quality', 'positive'], ['dessserts', '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 environment is very upscale and you will see a lot of rich guys with trophy wives or just highly paid escorts."], "output": "[['environment', 'ambience general', 'neutral'], ['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": ["If you are going for the food, it will not be worth it."], "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": ["You would think they would make up for it with service, sadly, no."], "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": ["Service was just ok, it is not what you'd expect for $500."], "output": "[['Service', 'service 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": ["Terrible Waste of money.. scammers"], "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": ["I agree that dining at Casa La Femme is like no other dining experience!"], "output": "[['Casa La Femme', '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 am actually offended to have spent so much money on such a bad experience."], "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": ["I literally just got back home after visiting Casa La Femme and was so offended by my visit felt it necessary to try and warn other diners who value their money and time."], "output": "[['Casa La Femme', 'restaurant general', 'negative'], ['Casa La Femme', '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": ["Our visit their to say the least, was an unpleasant and costly experience!"], "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": ["And even more so unpleasant because it was so costly for such an unpleasant experience."], "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": ["We did arrive late for our reservation so I can not complain too much about the wait for a table."], "output": "[['wait', '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": ["Although we were told 10-15 minutes and it was more like 45 minutes."], "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": ["We were ushered to the bar to wait momentarily and upon arrival were so excited."], "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 beautiful!"], "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 hostess was very pleasant."], "output": "[['hostess', '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": ["However, our $14 drinks were were horrible!"], "output": "[['drinks', 'drinks quality', 'negative'], ['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": ["Once we finally got a table, despite indicating we wanted an alla carte menu we were pushed into a table that was only price fixed!"], "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": ["Our experience did not ever get any better."], "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": ["For each course we waited over 1/2 hour to 45 minutes and were never offered a drink."], "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": ["We also asked for Hooka six times and the waiter kept telling us one minute and never returning with the Hooka."], "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": ["After the 4th time i asked again and the waiter than said after our dinner."], "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": ["We asked for beverages and never received 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": ["We asked for sides which the waiter than admitted that he forgot to put in that part of our order."], "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": ["My chicken was inedible as there were so many fatty lumps which i had to keep spitting out into my napkin."], "output": "[['chicken', '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 would not expect this for a $55 dinner."], "output": "[['dinner', 'food quality', 'negative'], ['dinner', '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": ["By the time we finished our dinner we still had not received one beverage NOR hooka!"], "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": ["What we did do was waste 3 hours being trapped in a table waiting and waiting for food and drinks and hooka.. some of which we never received!"], "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 only beverage we did receive was water in dirty glasses!"], "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": ["To top it all off.. the main reason we came to your restaurant was for the belly dancers and missed the first show as we were not seated yet and the 2nd belly dancer only danced at two tables in the back of the restaurant and never made it around to the other half of the restaurant."], "output": "[['NULL', 'service 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": ["By the time we left our wallets were empy and so were our stomachs AND we missed the show we were supposed to see following our dinner, which would have been acceptable if we got to enjoy the experience of good food and belly dancers!"], "output": "[['food', 'food quality', 'negative'], ['NULL', 'restaurant prices', '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": ["If it seemed possible to do so while there I would have fought my bill since my dinner portion of my meal was inedible!"], "output": "[['meal', 'food quality', '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": ["I have never left a restaurant feeling as if i was abused, and wasted my hard earned money."], "output": "[['restaurant', 'restaurant general', 'negative'], ['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": ["MY husbands birthday and my sons was not as it was intended... and we drove two hours to spend too much money to be treated terribly!"], "output": "[['NULL', 'restaurant general', 'negative'], ['NULL', 'restaurant prices', '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": ["I wish I COULD be refunded!"], "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 go with a larger group than 4! "], "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": ["At first we were a little taken aback, as this seemed to present a problem, although the restaurant looked fairly empty, but they hastily put the table together for us."], "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 menu is fairly simple without much descriptions. "], "output": "[['menu', '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": ["There was no tap beer that evening, which was a disappointment. "], "output": "[['beer', '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": ["Not much of a selection of bottled beer either, we went with Brahma. "], "output": "[['selection of bottled beer', '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": ["The appetizers we ordered were served quickly - an order of fried oysters and clams were delicious but a tiny portion (maybe 3 of each). "], "output": "[['fried oysters and clams', 'food quality', 'positive'], ['fried oysters and clams', 'food style_options', 'negative'], ['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 lobster knuckles (special of the day) were ok, but pretty tasteless."], "output": "[['lobster knuckles', 'food style_options', 'neutral'], ['lobster knuckles', '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 believe there were 2 shrimp in the \"salt encrusted shrimp\" appetizer. "], "output": "[['\"salt encrusted shrimp\" appetizer', '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": ["She replied \"well it would be more convenient for us if you ordered now, since you are a larger party, and it might get crowded.\" "], "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 arrived in about 15 minutes. "], "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 had the Thai style Fried Sea Bass...which was very good. "], "output": "[['Thai style Fried 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": ["Everyone seemed generally happy with their food, except my brother who had the grilled Mahi Mahi, seemingly drenched in Grapfruit Juice! "], "output": "[['food', 'food quality', 'positive'], ['grilled Mahi Mahi', 'food quality', 'negative'], ['grilled Mahi Mahi', '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 heard the lobster roll was excellent. "], "output": "[['lobster 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": ["They seemed to continue to rush us along, taking plates without asking if we were done (my sister still had her fork in hand). "], "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": ["All in all the food was good - a little on the expensive side, but fresh. "], "output": "[['food', 'food quality', 'positive'], ['food', '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 not the friendliest to our \"large party\"! "], "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": ["Probably would not go back here."], "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": ["Great 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": ["Food was amazing - I love Indian food and eat it quite regularly, but I can say this is one of the best I've had."], "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": ["Very \"normal Indian food\", but done really well."], "output": "[['Indian food', 'food style_options', 'neutral'], ['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 have it a 4 instead of 5 because of the price (just chicken tikka masala - no bread of rice - is $25), which I would expect at a upscale Indian restaurant but this place doesn't have an upscale feel."], "output": "[['place', 'restaurant general', 'positive'], ['place', 'restaurant prices', 'negative'], ['chicken tikka masala', 'food prices', 'negative'], ['feel', '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": ["Also, waiters try to push more food on you, like suggest things as if they are complimentary when they actually cost $."], "output": "[['waiters', '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 don't appreciate places or people that try to drive up the bill without the patron's knowledge so that was a huge turnoff (more than the price)."], "output": "[['NULL', 'service 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": ["But if you're prepared to spend some $ and remember to ask if something they offer is complimentary, then this is the place to go for Indian food"], "output": "[['Indian food', 'food quality', 'positive'], ['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": ["One of the BEST"], "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": ["Bukhara Grill, the tagline says it all.. \"INDIAN SPICE RAVE\""], "output": "[['Bukhara 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": ["The lunch buffet is expensive but is deff worth it."], "output": "[['lunch buffet', 'food prices', 'negative'], ['lunch buffet', '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 have gone for dinner only a few times but the same great quality and service is given."], "output": "[['service', 'service general', 'positive'], ['dinner', '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": ["Bukhara is on my top 5 Indian places in NYC"], "output": "[['Bukhara', '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": ["Wretched and retching"], "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 never been so disgusted by both food an service."], "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": ["For starters they delivered us someone else's order."], "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": ["However, once I received my predictably mediocre order of what Dokebi thinks passes as Korean fair, (sometimes you have to settle when it's your only option), I got through about half my kimchee before I found a piece of random lettuce accompanied by a far more disgusting, slimy, clearly bad piece of fish skin."], "output": "[['kimchee', 'food quality', 'negative'], ['Korean fair', '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": ["My main concern was the sanity of the food that was being sent out to myself and others, but I would be lying is I said that as someone who has worked in restaurants since the age of fifteen I was expecting at least a minimal effort on the part of the restaurant to amend the situation."], "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": ["None was made so i hung up."], "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": ["Less than three minutes passed before I found myself doubled over the toilet."], "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": ["My girlfriend, being slightly more aggressive, and having been equally disgusted causing her to throw out the remainder of her barely eaten meal, called back only to be informed that I was probably wrong and that it was most likely an oyster, and that we were also blacklisted from their restaurant."], "output": "[['meal', '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": ["It wasn't as if this restaurant had any major bragging points before hand, but now it's simply repulsive."], "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": ["Eat at your own risk."], "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": ["Gorgeous place ideal for a romantic dinner"], "output": "[['place', 'ambience general', 'positive'], ['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": ["I book a gorgeous white organza tent which included a four course prix fix menu which we enjoyed a lot."], "output": "[['four course prix fix menu', 'food quality', 'positive'], ['white organza tent', '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 spectacular as the waiter knew everything about the menu and his recommendations were amazing!"], "output": "[['service', 'service general', 'positive'], ['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 completely recommend Casa La Femme for any special occasion and to REALLY impress your date."], "output": "[['Casa La Femme', '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": ["More Williamsburg Garbage"], "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 dishes came out around 5 minutes apart."], "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 bibimbap was average, but the stone bowl wasn't even close to sizzling."], "output": "[['bibimbap', 'food quality', 'neutral'], ['stone bowl', '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": ["Too bad I had paid an extra $2 for the stone bowl."], "output": "[['stone bowl', '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 nakgi-bokum was horrible."], "output": "[['nakgi-bokum', '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": ["Easily the worst stir-fried squid I've ever tasted."], "output": "[['stir-fried squid', '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 sauce tasted more like Chinese fast food than decent Korean."], "output": "[['sauce', '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 side dishes were passable, and I did get a refill upon request."], "output": "[['side dishes', 'food quality', 'neutral'], ['side dishes', '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 real problem I had with this place was the complete lack of 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": ["She just nodded and walked off."], "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": ["As to my comment about the food, no apology or acknowledgment was made."], "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": ["My wife had barely touched that mess of a dish."], "output": "[['dish', '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 charged full price."], "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": ["Lives up to the hype"], "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've tried before but it always packed and doesn't take reservations."], "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": ["It was well worth the wait."], "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 wife had the risotto which was amazing."], "output": "[['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": ["It doesn't look appetizing as it's covered in squid ink and it turns your lips and teeth black, but the taste was phenomenal."], "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": ["The farro salad and the mashed yukon potatoes were also extremely tasty."], "output": "[['farro salad', 'food quality', 'positive'], ['mashed yukon 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": ["i love margherita pizza \u2013 i looove east village pizza"], "output": "[['east village pizza', 'restaurant general', 'positive'], ['margherita 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": ["Love this place, every time we are in the city this is one of the places we always go."], "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": ["A quintessential slice of NYC pizza."], "output": "[['slice of NYC pizza', '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 crust has a great bite and a good chew, the sauce is light with a nice acidity to it, the salt from the cheese is great, really heightens the flavor of all the other components."], "output": "[['crust', 'food quality', 'positive'], ['sauce', 'food quality', 'positive'], ['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": ["Personally I like the margherita pizza better, but they are all good."], "output": "[['margherita pizza', '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": ["Possibly the Most Romantic Restaurant in the City"], "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": ["This is undoubtedly my favorite modern Japanese brasserie (that don\u2019t serve sushi), and in my opinion, one of the most romantic restaurants in the city!"], "output": "[['modern Japanese brasserie', 'restaurant general', 'positive'], ['modern Japanese brasserie', '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": ["Not only is it an adventure getting to this somewhat hidden spot, once you enter the unmarked wooden doors, the zen and intimate d\u00e9cor will make you feel like you\u2019re no longer in the city."], "output": "[['spot', 'location general', 'neutral'], ['unmarked wooden doors', 'ambience general', 'positive'], ['d\u00e9cor', '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": ["If you\u2019re planning to come here, make sure that your date is someone whom you really like since you\u2019ll be ushered to private booths where there will be no people or food watching (choose the ones on the ground level that have glass ceilings so you may see the stars in the sky!)."], "output": "[['private booths', 'ambience general', 'positive'], ['glass ceilings', '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\u2019s just you and your date and an occasional cute \u2018excuse me\u2019 before the waiter opens the little curtain to your booth!"], "output": "[['NULL', 'ambience general', 'positive'], ['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": ["My party had the BBE $29 fixe prix menu, which was such a wonderful deal since it also came with a flight of sake!"], "output": "[['BBE $29 fixe prix menu', 'food prices', 'positive'], ['BBE $29 fixe prix 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": ["We started off with a delightful sashimi amuse bouche."], "output": "[['sashimi amuse bouche', '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 picked the Grilled Black Cod as my entree, which I absolutely devoured while someone commented that the Grilled Salmon dish was better."], "output": "[['Grilled Black Cod', 'food quality', 'positive'], ['Grilled 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": ["The entrees were served with miso soup and rice."], "output": "[['entrees', '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": ["The sake\u2019s complimented the courses very well and is successfully easing me into the sake world."], "output": "[['sake\u2019s', '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": ["For desserts, we tried the frozen black sesame mousse (interesting but not extraordinary) and matcha (powdered green tea) and blueberry cheesecake, which was phenomenal."], "output": "[['frozen black sesame mousse', 'food quality', 'neutral'], ['matcha (powdered green tea) and blueberry cheesecake', '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": ["Maybe it was the great company (I had friends visiting from Philly \u2013 yes, it was not a date this time) or the super reasonable price point, but I just can\u2019t say enough good things about this brasserie."], "output": "[['brasserie', 'restaurant general', 'positive'], ['brasserie', '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 don\u2019t usually visit the same establishment more than once, what more twice, but I\u2019ll come to Zenkichi anytime for a quiet, unhurried and memorable dinner."], "output": "[['Zenkichi', 'restaurant general', 'positive'], ['Zenkichi', '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": ["Terrible would be a compliment!"], "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 service leaves much to be desired, from feeling like you are rushed the place your order, to being ignored the rest of the night."], "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": ["We paid a fixed pricce but got nothing!!"], "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": ["We never ate because by close to 2 in the monring we were not served and were too upset ad tired to start eating."], "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 are extremely rude, not even apologizing for the horrible service we got and handing us a bill well over $500 for some drinks adn their pita bread!"], "output": "[['service', 'service general', 'negative'], ['drinks', 'drinks prices', 'negative'], ['pita bread', 'food prices', '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": ["Stay away"], "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": ["Great 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": ["I love 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": ["I tried a couple other dishes but wasn't too impressed."], "output": "[['dishes', '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": ["But for the Shabu Shabu, you won't find much better in NY."], "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 meat is fresh, the sauces are great, you get kimchi and a salad free with your meal and service is good too."], "output": "[['meat', 'food quality', 'positive'], ['sauces', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['meal', 'food style_options', 'positive'], ['kimchi', 'food prices', 'positive'], ['salad', '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": ["Dokebi gives Williamsburg the right one-two punch of classic Korean food and fusion twists like pork belly tacos."], "output": "[['Korean food', 'food quality', 'positive'], ['fusion twists', 'food quality', 'positive'], ['pork belly tacos', '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 hot dogs are good, yes, but the reason to get over here is the fantastic pork croquette sandwich, perfect on its supermarket squishy bun."], "output": "[['hot dogs', 'food quality', 'positive'], ['pork croquette sandwich', 'food quality', 'positive'], ['bun', '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": ["Restaurant with a view"], "output": "[['view', 'location 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 tasted very 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 family seafood entree was very good."], "output": "[['family seafood entree', '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 main entree was also very good."], "output": "[['main entree', '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": ["Price is high but the food is good, so I would come back again."], "output": "[['food', 'food quality', 'positive'], ['food', 'food 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": ["This place doesn't make any sense"], "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": ["Just want to warn you all - don't waste your time and money."], "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 has totally weird decor, stairs going up with mirrored walls - I am surprised how no one yet broke their head or fall off the stairs - mirrored walls make you dizzy and delusional..."], "output": "[['decor', 'ambience general', 'negative'], ['mirrored walls', '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 place is not inviting and the food is totally weird."], "output": "[['place', 'ambience general', '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": ["The concept of japanese tapas is newly created and clearly doesn't work."], "output": "[['japanese tapas', '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 food they serve is not comforting, not appetizing and uncooked."], "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": ["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": ["The food was great and tasty, but the sitting space was too small, I don't like being cramp in a corner."], "output": "[['food', 'food quality', 'positive'], ['sitting space', '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": ["Over all it was a very nice romantic place ."], "output": "[['place', 'restaurant 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": ["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": ["A coworker and I tried Pacifico after work a few Fridays and loved it."], "output": "[['Pacifico', '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 was great."], "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 we ordered was excellent, although I wouldn't say the margaritas were anything to write home about."], "output": "[['food', 'food quality', 'positive'], ['margaritas', 'drinks 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": ["Our waitress wasn't mean, but not especially warm or attentive either."], "output": "[['waitress', '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 must say I am surprised by the bad reviews of the restaurant earlier in the year, though."], "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": ["Regardless, we'll be back and can't wait to visit in the summer to take advantage of the patio."], "output": "[['patio', '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": ["Dumbfoundingly Poor"], "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 was, from start to finish, a mind-bogglingly uncomfortable 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": ["Lexicographers take note: a new and fascinating definition of rudeness is alive and flourishing right here in Brooklyn."], "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 servers at Flatbush Farm appear to have perfected that ghastly technique of making you feel guilty and ashamed for deigning to attract their attention."], "output": "[['servers', '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": ["Polite acknowledgement is out;"], "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": ["supercilious scorn is in."], "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": ["And how many times can you pick up the same perfectly aligned set of napkins, inspect them vapidly and plonk them down in exactly the same place instead of venturing a glance at people who are there to help you make the rent?"], "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 different server enhanced the fun, dumping our entrees in front of us halfway through our appetizer (which was delicious)."], "output": "[['server', 'service general', 'negative'], ['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": ["Overall the food quality was pretty good, though I hear the salmon is much better when it hasn't sat cooling in front of the guest."], "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": ["The place has a nice fit-out, some attractive furnishings and, from what I could tell, a reasonable wine list (I was given the food menu when I asked for the carte des vins)"], "output": "[['fit-out', 'ambience general', 'positive'], ['furnishings', 'ambience general', 'positive'], ['wine list', 'drinks style_options', '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": ["At $120 for two people, however, this in no way represents value, unless you're looking to pay by the hour for passive-aggressive torture."], "output": "[['NULL', 'restaurant prices', 'negative'], ['NULL', 'restaurant general', '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": ["On that scale, it's a world-beater."], "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": ["How is this palce still open?"], "output": "[['palce', '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 honestly don't even know where to begin."], "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 arrived and were seated immediately, which made us both happy."], "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": ["Everything was going good until we got our meals."], "output": "[['NULL', 'restaurant general', 'positive'], ['meals', '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 took one look at the chicken and I was appalled."], "output": "[['chicken', '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 was served with skin, over a bed of extremely undercooked spinach and mashed potatoes."], "output": "[['NULL', 'food style_options', 'negative'], ['spinach', '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 took one bite from the $24 salmon, and I have never, in the 17 years I have been going to restaurants tasted salmon as fishy, as dry, and as bland as the one in Flatbush Farms."], "output": "[['salmon', 'food quality', 'negative'], ['salmon', '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": ["At this point, the waitress comes over and asks us if everything was okay, I was literally so shocked that I was speechless and didn't say anything, and guess what, the waitress WALKED away."], "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": ["So, I switch with my boyfriend again to see if maybe I could stomach the meat and spinach again, but the spinach was so undercooked that I just could not bite through it."], "output": "[['spinach', '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 couldn't even enjoy the mashed potatoes because it was hidden completely under the chicken and spinach."], "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": ["So I decide to report back to the waitress because it was completely inedible."], "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": ["Guess what, I waited for TWENTY minutes before she came over and when she finally did, she says, \"oh well, I wish you would have said something earlier\" No apology, nothing."], "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": ["After that she simply took our plates, walked away, came back another TWENTY minutes later with the bill and the chicken on 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": ["No desert menu, no apology, nothing!!!!!!"], "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": ["This is where it really really gets bad: the manager said, there is absolutely nothing we can do, it's a matter of taste that she didn't like it, and I cannot comp it."], "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": ["Again, no apology, no is there anything else I can get you, no can I get you a drink to make up for it, nothing!!!!"], "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 level of rudeness was preposterous."], "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 manager came to the table and said we can do what we want, so we paid for what we did enjoy, the drinks and appetizers, and walked out."], "output": "[['manager', 'service general', 'negative'], ['drinks', 'drinks quality', 'positive'], ['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": ["I HAVE NEVER EVER HAD SUCH AN UNPLEASANT 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": ["THIS STAFF SHOULD BE FIRED."], "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": ["cirspy crust margherita pizza"], "output": "[['margherita 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 was really good 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": ["the crust was imazingly cooked well and pizza was fully loaded:):):)"], "output": "[['crust', 'food quality', 'positive'], ['pizza', '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": ["you know what i mean all the positives things happening there made mw write this review."], "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": ["Single Worst Restaurant in Manhattan"], "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": ["I'll being with a couple of positives: cool decor, good pita and hummus, and grilled octopus that was actually pretty tasty."], "output": "[['decor', 'ambience general', 'positive'], ['pita', 'food quality', 'positive'], ['hummus', 'food quality', 'positive'], ['grilled 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": ["If I could give 0 stars I would do so for 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": ["The reason there are 4 different results on citysearch for the same place is because they keep trying to start a new thread so they can stock it with positive reviews."], "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": ["Well...they can run but they can't hide."], "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...god where do i begin."], "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": ["It is quite a spectacular scene i'll give them that."], "output": "[['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": ["The decor however seems to be the distraction so you won't notice that you just payed 300 bucks for some cold eggplant that took 2 FRICKIN HOURS TO COME!!!!"], "output": "[['decor', 'ambience general', 'neutral'], ['eggplant', 'food quality', 'negative'], ['eggplant', 'food prices', '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": ["How this place survives the competitive west village market in this economy, or any other for that matter, is beyond me."], "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": ["Great Hot Dogs!"], "output": "[['Hot Dogs', '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": ["Though it's been crowded most times I've gone here, Bark always delivers on their food."], "output": "[['food', 'food quality', 'positive'], ['Bark', '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": ["The hot dogs are top notch, and they're Slamwich is amazing!"], "output": "[['hot dogs', 'food quality', 'positive'], ['Slamwich', '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": ["Going to Bark is always worth the train ride, and will make your tongue and belly very happy!"], "output": "[['Bark', 'restaurant general', '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": ["Only complaint is the pricing--I believe it would be more reasonable to pay a dollar less on each item listed on the menu."], "output": "[['menu', '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": ["But nonetheless--great spot, great food."], "output": "[['spot', '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": ["Fabulous food - if the front of house staff don't put you off \u2013 "], "output": "[['food', 'food quality', 'positive'], ['front of house 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": ["It's a little out of our price range for dining there except on special occasions, but we've eaten there 6 times in the last 2 years. "], "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": ["Each time we've been, the front of house staff (not the waiters - they're fantastic - but the people who greet and seat you) has been so hideous to us that were it not for the exceptional fish dishes I would never return. "], "output": "[['waiters', 'service general', 'positive'], ['front of house staff', 'service general', 'negative'], ['fish 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": ["As BFC doesn't take reservations you almost always have to wait by the bar - and be abused by the front of house staff until you are seated, which can be over an hour later!"], "output": "[['BFC', 'restaurant miscellaneous', 'negative'], ['front of house staff', 'service general', '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": ["The frizzy retro girl (with winged/ Dame Edna glasses) will yell at you if you try to order a drink. "], "output": "[['girl', '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 was almost amused by the fact that she was turning away customers at 9pm on a Friday night because she \"had a BBQ to go to\" that night - WTF??"], "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": ["I'd be horrified if my staff were turning away customers so early and so rudely!"], "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": ["There's another girl who I can't describe, she is about 5'6\" with brown hair, who eavesdrops on your conversation and chimes in - except she only hears the last part of what you said, so her uninvited opinions are often out of context and nothing to do with what you're *really* talking about. "], "output": "[['girl', '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'm a friendly person, so I wouldn't mind had she not been so nasty and gotten so personal. "], "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": ["Again, I'd be super upset if that were my employee."], "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": ["Considering you will spend at least $60 a head, I expect better service. "], "output": "[['service', 'service 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": ["So, if you're walking by and thinking about dining, you might want to see who's going to be seating you first..."], "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": ["Maitre-D-\"Eat and get out\""], "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": ["The food and service were fine, however the maitre-D was incredibly unwelcoming and arrogant."], "output": "[['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['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": ["While finishing our meals which included a high-end bottle of wine, our son's fiance joined us for a glass of wine and dessert."], "output": "[['bottle 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": ["This guy refused to seat her and she left, followed shortly by the four of us, but not before I told him that in my 40 years of world travel, including Paris, that I had never seen such a display of bad behavior by a frontman in a restaurant."], "output": "[['frontman', '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": ["His response was smug, arrogant, and condescending, totally consistent with his deportment on display all evening."], "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 word to the wise: you can't dine here and disturb the maitre-D's sense of \" table turnover\", as whacked as it is, or else."], "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": ["If you go here, do it on his off-night."], "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": ["Best meal in a long time!"], "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": ["Mussles and calamari were superb Saturday evening."], "output": "[['Mussles', 'food quality', 'positive'], ['calamari', '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 the Lamb special which was perfect."], "output": "[['Lamb 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": ["My father had the flank steak which was very good, and my mother had the swordfish."], "output": "[['flank steak', '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 Four Seasons restaurant is a great experience."], "output": "[['The Four Seasons 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 is great and the environment is even better."], "output": "[['food', 'food quality', 'positive'], ['environment', '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": ["Everyone must come here at least once."], "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": ["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": ["Taking Hot Dogs to the next level"], "output": "[['Hot Dogs', '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": ["At first glance this place seems a bit pricey for a hot dog joint, but at Bark you don't just get your average hot dog."], "output": "[['Bark', 'restaurant prices', 'negative'], ['hot dog', '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": ["Here the hot dog is elevated to the level of a real entree with numerous variations available."], "output": "[['hot dog', 'food quality', 'positive'], ['hot dog', '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": ["Great Atmosphere"], "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": ["I highly recommend the fish tacos, everything else was ok."], "output": "[['fish tacos', 'food quality', 'positive'], ['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": ["Cool atmosphere, the fire place in the back really ads to it but needs a bit more heat throughout on a cold night."], "output": "[['atmosphere', 'ambience general', 'positive'], ['fire place', 'ambience general', 'positive'], ['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": ["Poor service and management"], "output": "[['service', 'service general', 'negative'], ['management', '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": ["Don\u2019t go to 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": ["Had an awful experience at Casa la Femme on a Saturday dinner."], "output": "[['Casa la Femme', '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": ["Appetizers took nearly an hour."], "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": ["When the main course finally arrived (another 45mins) half of our order was missing."], "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 got an explanation as to what was going on."], "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 manager was rude and handled the situation extremely poorly."], "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": ["When we threatened to leave, we were offered a meager discount even though half the order was missing."], "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": ["On the way out, we heard of other guests complaining about similar issues."], "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": ["Can\u2019t believe how an expensive NYC restaurant can be so disrespectful to its clients."], "output": "[['restaurant', 'restaurant prices', '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": ["What a hassle!"], "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 good, but not outstanding."], "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": ["There is no way it justifies the accolades it receives, the attitude of the staff or the wait for a table."], "output": "[['staff', 'service general', 'negative'], ['NULL', 'food quality', 'negative'], ['wait', '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": ["On our last visit, they skipped over our name on the list, leaving us waiting an extra hour for a 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": ["Mistakes happen, but they are usually accompanied by an apology, perhaps even a glass of wine...but not the grunt that we received from the Al Di La staff."], "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": ["Expensive"], "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": ["The bread was stale, the salad was overpriced and empty."], "output": "[['bread', 'food quality', 'negative'], ['salad', 'food prices', 'negative'], ['salad', '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 pasta was well cooked, didn't have enough sauce though or flavor."], "output": "[['pasta', 'food quality', 'positive'], ['pasta', 'food quality', 'negative'], ['pasta', '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": ["So 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": ["I was one of the people that went for this horrible 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 hostess was rude and I got a distinct feeling that they did not want to serve us."], "output": "[['hostess', 'service general', '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": ["The only thing that my friend left out is that when we sat down at the bar the bartender disappeared."], "output": "[['bartender', '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 a menu and the same waitress looked at my like I was insane."], "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": ["I was shocked that my friends wanted to stay after the waitress said, \"can I help you\" and \"how many are in your party.\""], "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 three of us standing in front of her should have been an indication of how many of us there were."], "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": ["We didn't look like the other patrons in there so unfortunately I think that may have been part of the problem."], "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": ["Shame on this place for the horrible rude staff and non-existent customer service."], "output": "[['staff', 'service general', 'negative'], ['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": ["bad staff"], "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": ["I generally like 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 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 design of the space is good."], "output": "[['space', '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 is HORRID!"], "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 was there for brunch recently, and we were tag teamed by a waitress and a waiter."], "output": "[['waitress', 'service general', 'negative'], ['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": ["The waiter delivered our food while holding what appeared to be a plastic bag of garbage in one hand."], "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 can't believe that it was, but please put the bag down before delivering 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": ["The waitress came to check in on us every few minutes, and began to clear the plates while half of us were still eating (a big pet peeve of mine that happens almost everywhere, so I try to ignore it)."], "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": ["I couldn't ignore the fact that she reach over the plate of one of my friends, who was in mid bite, to clear 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": ["She then put the check down without asking if we were done, and came to check on the bill every two minutes, even though we were one of three occupied tables."], "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": ["I wish I could like this place more, and I wish someone would retrain the staff."], "output": "[['place', 'restaurant general', '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": ["Room Was Acceptable"], "output": "[['Room', 'rooms 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 room was nice and the furnishings were comfortable."], "output": "[['room', 'rooms general', 'positive'], ['furnishings', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 from the restaurant was very good but pricey which was the standard for everything in this hotel."], "output": "[['food', 'food_drinks quality', 'positive'], ['food', 'food_drinks prices', 'negative'], ['hotel', 'hotel 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 internet access from the room was $9.95 for a 24 hour period."], "output": "[['internet access', 'rooms_amenities 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": ["To check in for my flight using the business center cost me $4.59 which included three minutes use of the internet and printing seven pages for my boarding pass."], "output": "[['business center', 'facilities 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": ["Staff was very pleasant and helpful."], "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": ["Great stay!"], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 wonderful choice."], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 in was fast and courteous."], "output": "[['Check in', '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": ["Rooms were clean, spacious and comforatable."], "output": "[['Rooms', 'rooms cleanliness', 'positive'], ['Rooms', 'rooms design_features', 'positive'], ['Rooms', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 outstanding, for both the conference and on my own."], "output": "[['Food', 'food_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": ["Pool was refreshing on the hot days."], "output": "[['Pool', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 for the price of this hotel it cannot be beat!"], "output": "[['hotel', 'hotel general', 'positive'], ['hotel', 'hotel 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 definitely stay here again conference or not."], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 Business Hotel"], "output": "[['Hotel', 'hotel 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": ["Very nice hotel for business travelers - very few kids."], "output": "[['hotel', 'hotel 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": ["Great rooms with very comfortable beds."], "output": "[['rooms', 'rooms general', 'positive'], ['beds', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 pool area, very good fitness center - nice lobby and common areas."], "output": "[['pool area', 'facilities design_features', 'positive'], ['fitness center', 'facilities general', 'positive'], ['lobby', 'hotel general', 'positive'], ['common areas', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 excellent shuttle service."], "output": "[['shuttle service', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 Sports Bar had good food with very reasonable prices."], "output": "[['food', 'food_drinks quality', 'positive'], ['food', 'food_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": ["The only downside was a per minute charge to use the business center computers."], "output": "[['business center computers', 'facilities 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": ["Perfectly Close to the Airport"], "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": ["I booked this because of it's proximity to the airport for our departure."], "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 staff was friendly and helpful, they upgraded our room to queen beds without us asking."], "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 rooms are lovely, and the hotel is quiet even though it is so close to the airport."], "output": "[['rooms', 'rooms general', 'positive'], ['hotel', 'hotel comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 24 hour shuttle to the airport is very, very convenient and gets you there in about 4 minutes."], "output": "[['24 hour shuttle', 'facilities comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 the restaurant and the food was good hearty and the best avocado I've ever had.....so all in all you can't beat the deal, the location, the clean rooms, and the service....."], "output": "[['food', 'food_drinks quality', 'positive'], ['avocado', 'food_drinks quality', 'positive'], ['NULL', 'hotel prices', 'positive'], ['location', 'location general', 'positive'], ['rooms', 'rooms cleanliness', '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": ["A Great Hotel"], "output": "[['Hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 stay at this hotel was wonderful."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 very courteous upon check-in."], "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": ["Our room was perfectly spotless."], "output": "[['room', 'rooms cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 use an outlet behind the headboard, and expected to see some type of dirt when I pulled the bed out, but to my surprise, not even dust!)"], "output": "[['NULL', 'rooms cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 clean and well maintained."], "output": "[['NULL', 'rooms cleanliness', 'positive'], ['NULL', 'rooms 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": ["Some nice touches of southwest decor here and there."], "output": "[['NULL', 'rooms design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 problems whatsoever, and I would recommend this hotel to anybody."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 service but rude desk clerk"], "output": "[['service', 'service general', 'positive'], ['desk clerk', '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": ["She immediately began to yell that if I wanted an upgrade I would have to pay for 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": ["The same desk clerk started to yell again stating that she had told me when I called that I could upgrade for a charge and that was her rules."], "output": "[['desk clerk', '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": ["She completely ignored me and just kept on yelling."], "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": ["I asked to speak to the manager and she told me she was the manager when in fact the manager's name was clearly displayed on the wall."], "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": ["This incident was very humiliating as other guests were present."], "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": ["I am writing this review because this kind of behavior was totally unacceptable and hopefully no other guests will be treated in this manner."], "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": ["Overall service was great and the staff as a whole were very courteous and helpful."], "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": ["Not bad for one night"], "output": "[['NULL', 'hotel 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": ["Front desk staff were friendly and helpful both with early check-in and an early check-out."], "output": "[['Front desk 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": ["Room was large and spacious, but rather bland."], "output": "[['Room', 'rooms design_features', 'positive'], ['Room', 'rooms comfort', 'positive'], ['Room', 'rooms design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 for a business traveler, or for a stayover with early departure to Phoenix Sky Harbor Airport, took 8 minutes to get to the airport via 10 freeway."], "output": "[['NULL', 'hotel miscellaneous', '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": ["Ideal location."], "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": ["Very affordable rate at low $50s."], "output": "[['NULL', 'hotel 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 pool looked nice, as did their restaurant, but didn't try either one."], "output": "[['pool', 'facilities general', 'positive'], ['restaurant', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 below average"], "output": "[['NULL', 'hotel 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": ["Unfortunately, this is below average."], "output": "[['NULL', 'hotel 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": ["Rooms are large but very plain, with furnishings and fixtures as cheap as possible."], "output": "[['Rooms', 'rooms design_features', 'positive'], ['Rooms', 'rooms design_features', 'negative'], ['fixtures', 'rooms quality', 'negative'], ['furnishings', 'rooms 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 hotel shows its age and badly needs refurbishing."], "output": "[['hotel', 'hotel 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": ["Bathroom sink was on a slight slant because it was pulling out of the wall."], "output": "[['Bathroom sink', 'rooms 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": ["Nothing is especially terrible or unacceptable about this hotel."], "output": "[['hotel', 'hotel 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": ["It is just subpar."], "output": "[['NULL', 'hotel 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 do it!!"], "output": "[['NULL', 'hotel 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 run down, dirty and loud."], "output": "[['place', 'hotel quality', 'negative'], ['place', 'hotel cleanliness', 'negative'], ['place', 'hotel comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 pictures they provide on the web do not tell the story so don't be fooled."], "output": "[['NULL', 'hotel 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": ["Great Restaurant"], "output": "[['Restaurant', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 property has really improved since our last stay."], "output": "[['property', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Room was cool, clean and comfy."], "output": "[['Room', 'rooms general', 'positive'], ['Room', 'rooms cleanliness', 'positive'], ['Room', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 downstairs is the best kept secret in the area!"], "output": "[['restaurant', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 and service was outstanding (try the seafood platter)."], "output": "[['food', 'food_drinks quality', 'positive'], ['service', 'service general', 'positive'], ['seafood platter', 'food_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": ["Staff was courteous and efficient."], "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 keep on coming back!"], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 going to this place every year and I keep on coming back to this hotel."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 breakfast is excellent!"], "output": "[['breakfast', 'food_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": ["It is rare that hotels in this class serve hot meals, yet they do!"], "output": "[['meals', 'food_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": ["Breakfast is fit for a king."], "output": "[['Breakfast', 'food_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": ["Plus, the staff at the front desk are always courteous and friendly."], "output": "[['staff at the front desk', '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": ["Though the bathrooms are a bit old, the beds are still cozy."], "output": "[['bathrooms', 'rooms quality', 'negative'], ['beds', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 hotel is right in the middle of everywhere."], "output": "[['hotel', '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": ["Above average hotel for great price !"], "output": "[['hotel', 'hotel general', 'positive'], ['hotel', 'hotel 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": ["Got a great price of $64 per night."], "output": "[['NULL', 'hotel 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 room was perfect for me, the bed was one of the most comfortable I've ever had in a hotel."], "output": "[['room', 'rooms general', 'positive'], ['bed', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 clean, great service - they gave me a complimentary bottle of wine because I missed the hotel shuttle."], "output": "[['service', 'service general', 'positive'], ['NULL', 'hotel cleanliness', '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": ["Good restaurant and bar attached."], "output": "[['restaurant', 'facilities general', 'positive'], ['bar', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Close to Scottsdale and the University."], "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": ["Price was right"], "output": "[['NULL', 'hotel 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": ["Pleasantly surprised at $69 night."], "output": "[['NULL', 'hotel 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": ["Front desk was not helpful, but who cares...for $69 you get a clean, fairly-large room, central air, refrig/micro, free (but sparse) breakfast buffet."], "output": "[['Front desk', 'service general', 'negative'], ['room', 'rooms prices', 'positive'], ['room', 'rooms cleanliness', 'positive'], ['room', 'rooms design_features', 'positive'], ['breakfast buffet', 'food_drinks prices', 'positive'], ['breakfast buffet', 'food_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": ["Stayed there because it was near Banner Hospital."], "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": ["Friendly 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": ["The staff was extremely helpful and friendly."], "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 would say they are the best part of the hotel!"], "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": ["An elevator was broken during our last stay and it was most annoying, but did not greatly impact the overall experience."], "output": "[['elevator', 'facilities quality', 'negative'], ['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 it is a nice and affordable spot for sightseeing in the area."], "output": "[['spot', 'hotel general', 'positive'], ['spot', 'hotel prices', 'positive'], ['spot', 'hotel 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": ["Administrative Issues"], "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 Best Western Executive Park Hotel is an average place to stay (though a bit far from downtown) with a substandard management team."], "output": "[['Best Western Executive Park Hotel', 'hotel general', 'neutral'], ['Best Western Executive Park Hotel', 'location general', 'negative'], ['management team', '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 tried to obtain a receipt for my stay to replace one I lost and have been ignored."], "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": ["There's never anyone to talk to from management and phone calls/e mails receive no response."], "output": "[['management', 'service general', '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": ["It's not a recipe for another stay."], "output": "[['NULL', 'hotel 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 impressed"], "output": "[['NULL', 'hotel 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 desk person was in a rude mood."], "output": "[['desk person', '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": ["There was construction being done on the street in front of the hotel; which made it very difficult driving around."], "output": "[['NULL', 'hotel 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 air conditioner was very loud."], "output": "[['air conditioner', 'rooms_amenities 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": ["Nothing told us that there was a free breakfast - the restaurant looked like it was closed."], "output": "[['restaurant', 'facilities 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": ["All in all the price was way too high for such a poor accomodations."], "output": "[['accomodations', 'hotel general', 'negative'], ['accomodations', 'hotel 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": ["Extremely reasonable for the price paid."], "output": "[['NULL', 'hotel general', 'positive'], ['NULL', 'hotel 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": ["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": ["I was there 3 nights for a conference and am giving it 5 stars, as it was quite reasonably priced for what we received."], "output": "[['NULL', 'hotel general', 'positive'], ['NULL', 'hotel 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 was friendly overall."], "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": ["Airport shuttle service was convenient as I chose not to rent a car during this trip."], "output": "[['Airport shuttle service', 'facilities comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 complaints about the room, pretty clean."], "output": "[['room', 'rooms general', 'positive'], ['room', 'rooms cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 to the lunch buffet twice and had a nice meal and again at very reasonable price."], "output": "[['lunch buffet', 'food_drinks quality', 'positive'], ['lunch buffet', 'food_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": ["There was a few restaurants within walking distance to eat at as well."], "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 conference/banquet room was great."], "output": "[['conference/banquet room', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 accomodating, good acoustics, clean."], "output": "[['NULL', 'facilities general', 'positive'], ['NULL', 'facilities quality', 'positive'], ['NULL', 'facilities cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 location was in reference to tourist spots, etc....but for a local conference, it was 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": ["Nice hotel, nice location for the valley"], "output": "[['location', 'location general', 'positive'], ['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 the hotel, it was very clean, the staff were fantastic and the rooms were great."], "output": "[['hotel', 'hotel general', 'positive'], ['hotel', 'hotel cleanliness', 'positive'], ['staff', 'service general', 'positive'], ['rooms', 'rooms general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 cant complain about this hotel stay."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 in the central valley so getting to anywhere is easy with the easy access to the local freeways."], "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": ["the only drawback was that the pool area this time of year didnt seem to get much sun during the day, but the water is heated so it didnt matter too much."], "output": "[['pool area', 'facilities design_features', 'negative'], ['pool', 'facilities design_features', 'positive'], ['pool', 'facilities comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 absolutely stay here again!!"], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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."], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 it to be a dingy motel, but to my surprise, the rooms were clean and even a little spacious."], "output": "[['rooms', 'rooms cleanliness', 'positive'], ['rooms', 'rooms design_features', 'positive'], ['rooms', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 continental breakfast was excellent."], "output": "[['continental breakfast', 'food_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": ["If all you want is a clean place to stay without the frills, and especially if you're a business traveler, stay here."], "output": "[['place', 'hotel cleanliness', 'positive'], ['place', 'hotel design_features', 'neutral'], ['place', 'hotel 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": ["They seem to have businesspeople in mind."], "output": "[['NULL', 'hotel 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": ["Loved this hotel overall"], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 loved this hotel."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 close to the airport."], "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 hotel staff was very friendly, the rooms were very clean, both times."], "output": "[['hotel staff', 'service general', 'positive'], ['rooms', 'rooms cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 rooms were quiet."], "output": "[['rooms', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 pool was great and quiet both times, loved the lighted palm trees at night."], "output": "[['pool', 'facilities general', 'positive'], ['pool', 'facilities comfort', 'positive'], ['pool', 'facilities design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 breakfast buffet was unbelievable, everything you could imagine and a wonderful lady taking care of it."], "output": "[['breakfast buffet', 'food_drinks style_options', 'positive'], ['lady', '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": ["Awesome suite, 2 bathrooms, sinks and showers seperated by french doors."], "output": "[['suite', 'rooms general', 'positive'], ['suite', 'rooms design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 2 flat sceen tvs and lots of space in each room."], "output": "[['room', 'rooms design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 complaint I had is that our suite smelled like smoke and it was a non smoking suite."], "output": "[['suite', 'rooms 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": ["We turned on both air conditioners to get rid of the smell and it wouldn't go away."], "output": "[['NULL', 'rooms 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 would highly recommend the hotel, great location, great service, good value."], "output": "[['location', 'location general', 'positive'], ['service', 'service general', 'positive'], ['hotel', 'hotel general', 'positive'], ['hotel', 'hotel 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": ["Convienient Comfortable business travel Hotel"], "output": "[['Hotel', 'hotel comfort', 'positive'], ['Hotel', 'hotel 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": ["This was my third stay in two months and I have noticed a continuing trend of upgrades and service."], "output": "[['NULL', 'hotel 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": ["Understand the property is under new management and it really shows."], "output": "[['property', 'hotel 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": ["Recommend this highly for the seasoned Pheonix road warrior or warriorette."], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Clean, decent hotel"], "output": "[['hotel', 'hotel cleanliness', 'positive'], ['hotel', 'hotel 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 hotel was clean, rooms were large and comfortable, nothing fancy."], "output": "[['hotel', 'hotel cleanliness', 'positive'], ['rooms', 'rooms design_features', 'positive'], ['rooms', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 noise, though hotel was half empty I'm extremely sensitive to noise at hotels and was not disturbed both evenings or in the mornings."], "output": "[['hotel', 'hotel comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Is an older building but appeared to be well maintained."], "output": "[['building', 'hotel 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": ["Interior corridors clean and well lit."], "output": "[['Interior corridors', 'hotel cleanliness', 'positive'], ['Interior corridors', 'hotel design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Exterior grounds well kept."], "output": "[['Exterior grounds', 'hotel 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": ["Has elevators on both sides of the building."], "output": "[['building', 'hotel design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Has a nice pool and very hot jaquizzi , was clean."], "output": "[['pool', 'facilities general', 'positive'], ['jaquizzi', 'facilities design_features', 'positive'], ['NULL', 'hotel cleanliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 pool was well heated so swimming was possible in the winter climate, even at night."], "output": "[['pool', 'facilities design_features', 'positive'], ['pool', 'facilities comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Hotel provides free pass to Golds Gym, a five minute walk from front door."], "output": "[['Hotel', 'hotel 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": ["Staff was freindly and professional for the most part."], "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": ["Has good airport shuttle, ten minutes unless heavy traffic, then at worst 20 minutes."], "output": "[['airport shuttle', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 convienently located in southeast phoenix, right next to Tempe."], "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": ["Nice neghborhood, safe."], "output": "[['neghborhood', '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": ["Would stay again."], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 conference facilities too, set up well."], "output": "[['conference facilities', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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\" Best Western"], "output": "[['Best Western', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 hotel is the best Best Western I have stayed in."], "output": "[['Best Western', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 especially attractive outside or surrounding area but convenient location and walk to small strip malls c eateries."], "output": "[['outside', 'hotel design_features', 'negative'], ['surrounding area', 'location general', 'negative'], ['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": ["Inside hotel is cool and southwestern."], "output": "[['hotel', 'hotel general', 'positive'], ['hotel', 'hotel design_features', '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": ["Hotel desk staff was friendly."], "output": "[['Hotel desk 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": ["There is a complimentary shuttle that goes anywhere in 5 mi area, including airport, and runs early am until about 10 pm."], "output": "[['shuttle', 'facilities prices', 'positive'], ['shuttle', 'facilities 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": ["Free high speed internet."], "output": "[['internet', 'facilities quality', 'positive'], ['internet', 'facilities 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 comfortable room."], "output": "[['room', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Pool area clean but not very attractive."], "output": "[['Pool area', 'facilities cleanliness', 'positive'], ['Pool area', 'facilities design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 dificulties I had were: One, the restaurant service was terrible!"], "output": "[['restaurant 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": ["It opens at 6 am which was great for the sightseeing tours and my breakfasts were all free, but once had to finally open the kitchen door and ask to be seated."], "output": "[['NULL', 'facilities miscellaneous', 'positive'], ['breakfasts', 'food_drinks prices', '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": ["Then wait to give order, then wait for the 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": ["The food selection was pretty good."], "output": "[['food selection', 'food_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": ["One time the employee stopped to pick up dirty plates as he led me to my seat!"], "output": "[['employee', '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 other problem was the hotel manager - a young woman apparently somewhat new at her job."], "output": "[['hotel 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": ["She tried to refuse my gold crown club points as payment for my stay."], "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": ["When I was persistent, she made a phone call and I heard her say well, i never heard of that."], "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": ["I would definitely stay here again when in the Phoenix area!"], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 motel, Poor location"], "output": "[['motel', 'hotel general', 'positive'], ['location', '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": ["My overall sense is that this was a good motel, comparatively inexpensive."], "output": "[['motel', 'hotel general', 'positive'], ['motel', 'hotel 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": ["- Comparatively inexpensive"], "output": "[['NULL', 'hotel 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": ["- Microwave, refrigerator, coffee maker in room"], "output": "[['room', 'rooms design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 (but repetitive) breakfast included in price (wafles, scrambled eggs, cereal, etc.)"], "output": "[['breakfast', 'food_drinks quality', 'neutral'], ['breakfast', 'food_drinks style_options', 'negative'], ['breakfast', 'food_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": ["- Free internet access (including printing) from lobby"], "output": "[['internet access', 'facilities prices', 'positive'], ['printing', 'facilities 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": ["- Nice 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": ["- Average room size."], "output": "[['room', 'rooms design_features', '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": ["- Very limited space to hang clothes"], "output": "[['space', 'rooms design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 biggest problem was the location."], "output": "[['location', '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": ["It was far away from all the sites I wanted to see."], "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": ["Great airport location"], "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": ["It was very quiet considering being so close to the airport."], "output": "[['NULL', 'hotel comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 clean and comfortable room, helpful and friendly staff."], "output": "[['room', 'rooms cleanliness', 'positive'], ['room', 'rooms comfort', '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 in the Bar and Grille was just ok."], "output": "[['food', 'food_drinks 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": ["There is a charge for internet access in the room but it works great."], "output": "[['internet access', 'rooms_amenities prices', 'negative'], ['internet access', 'rooms_amenities 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 can print boarding passes at a kiosk near the front desk but it can be busy first thing in the morning so you might want to do it the day before."], "output": "[['kiosk', 'facilities 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": ["I left on the 7:00am shuttle and the ride to the airport was quick and hassle-free."], "output": "[['shuttle', 'facilities general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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!"], "output": "[['NULL', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Wow! What a great hotel!"], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Rooms were clean, easy accessible."], "output": "[['Rooms', 'rooms cleanliness', 'positive'], ['Rooms', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Beds were so comfortable!"], "output": "[['Beds', 'rooms comfort', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Staff was friendly."], "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": ["Pool was heated, had a great atmosphere with unlimited bottled water available while swimming/laying out."], "output": "[['Pool', 'facilities design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Offered food and drink service at the pool."], "output": "[['pool', 'facilities design_features', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Room service was great!"], "output": "[['Room 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": ["Prompt delivery and wonderful food."], "output": "[['food', 'food_drinks quality', '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": ["I had the southwestern ceasar - it was one of the best salads I've ever had!"], "output": "[['southwestern ceasar', 'food_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": ["I was very impressed and would come back to the HIlton Phoenix Airport again!"], "output": "[['HIlton Phoenix Airport', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 STAY HERE"], "output": "[['NULL', 'hotel 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": ["All 4 lower rooms were 80 degrees and above."], "output": "[['rooms', 'rooms comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 the concert we had to change 4 of the rooms twice trying to find cooler floors."], "output": "[['rooms', 'rooms comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 finally gave up at 12:30 a.m. with a room that was 77 degrees - still too warm."], "output": "[['room', 'rooms comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 room did not even have a shower curtain!"], "output": "[['room', 'rooms design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 understand they are going through renovations, but they need to either do it floor by floor and close that floor or close the entire hotel until finished."], "output": "[['hotel', 'hotel 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 only nice thing was the free shuttle to America West Arena."], "output": "[['shuttle', 'facilities prices', 'positive'], ['NULL', 'hotel 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": ["Very disappointing"], "output": "[['NULL', 'hotel 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": ["Lots of services promised and not provided."], "output": "[['services', 'facilities 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 shuttle wasn't running, and the restaurant was closed down - both of those explained to me with because business is low right now around the holidays."], "output": "[['shuttle', 'facilities general', 'negative'], ['restaurant', 'facilities 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 business center has been taken apart - the front desk staff did not know if it was going to be back, since they had no idea it had been taken apart and were quite shocked to find out, when they tried to let me in to use it."], "output": "[['business center', 'facilities general', 'negative'], ['front desk 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": ["Vending machines were out of everything except in the lobby."], "output": "[['Vending machines', 'facilities 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": ["Staff was very friendly and a bit embarrassed about everything that wasn't available."], "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 room itself was fine."], "output": "[['room', 'rooms general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Pay extra and stay somewhere else"], "output": "[['NULL', 'hotel 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 has to be the worst hotel I have ever stayed in!"], "output": "[['hotel', 'hotel 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 was no HOT WATER!"], "output": "[['NULL', 'rooms comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 beds are very hard."], "output": "[['beds', 'rooms comfort', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 friendly."], "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": ["No wifi only in the hotel lobby."], "output": "[['NULL', 'rooms design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 get a suite with a stove dont except dishes, pots and pans they do not provide them you have to buy your own."], "output": "[['suite', 'rooms design_features', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}
{"task_type": "generation", "dataset": "semeval-2015", "input": ["Pay the 20 extra and stay somewhere's else"], "output": "[['NULL', 'hotel 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 hotel, great location, great price"], "output": "[['hotel', 'hotel general', 'positive'], ['location', 'location general', 'positive'], ['hotel', 'hotel 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 had a great time at this hotel and did not experience any of what the bad reviews are about."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  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 very friendly and helpful, the rooms were large and comfortable, the free breakfast was great, and the location downtown was excellent."], "output": "[['staff', 'service general', 'positive'], ['rooms', 'rooms design_features', 'positive'], ['rooms', 'rooms comfort', 'positive'], ['breakfast', 'food_drinks prices', 'positive'], ['breakfast', 'food_drinks quality', 'positive'], ['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": ["I would highly recommend this hotel to anyone wanting to stay in downtown Phoenix."], "output": "[['hotel', 'hotel general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"Delicate spices, onions, eggs and a kick-ass roti.\"  Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "}