| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Delicate spices, onions, eggs and a kick-ass roti."], "output": "[['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" 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!"], "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": ["Toons has recently been redone, so it's now a very attractive space."], "output": "[['Toons', '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's as good as ever."], "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": ["In an area sadly lacking in decent Thai food, this is one of the best spots."], "output": "[['Thai food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Went here last night - nice decor, good service, but the food was surprisingly excellent."], "output": "[['decor', 'ambience general', 'positive'], ['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The portions are HUGE, so it might be good to order three things to split (rather than one appetizer and entree per person) for two people."], "output": "[['portions', '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": ["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": ["Best drumsticks over rice and sour spicy soup in town!"], "output": "[['drumsticks over rice', 'food quality', 'positive'], ['sour spicy soup', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Beef noodle soup is good as well."], "output": "[['Beef noodle soup', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The service is good and the resturant is clean."], "output": "[['service', 'service general', 'positive'], ['resturant', '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": ["Best Taiwanese food in NY!"], "output": "[['Taiwanese 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 been to Rao's probably 15 times the past 3 years and it keeps getting better."], "output": "[[\"Rao's\", 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["For those that go once and don't enjoy it, all I can say is that they just don't get it."], "output": "[['NULL', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Rao's has the best service and atmosphere in NYC."], "output": "[['service', 'service general', 'positive'], ['atmosphere', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Good luck getting a table."], "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": ["My roommate and 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": ["We recently decided to try this location, and to our delight, they have outdoor seating, perfect since I had my yorkie with me."], "output": "[['outdoor seating', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Indoor was very cozy and cute."], "output": "[['Indoor', '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 portion sizes here are huge, and the sushi is good."], "output": "[['portion sizes', 'food style_options', 'positive'], ['sushi', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Staff is very accomodating."], "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": ["Excellent dumplings served amid clean, chic decor."], "output": "[['dumplings', 'food quality', 'positive'], ['decor', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I got the $10 10-piece dim sum combo, every bite of which was great."], "output": "[['$10 10-piece dim sum combo', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" 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 $1 for each small piece???"], "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": ["Not worth it."], "output": "[['NULL', 'food prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I won't go back unless someone else is footing the bill."], "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 decor is very simple but comfortable."], "output": "[['decor', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food was delicious but do not come here on a empty stomach."], "output": "[['food', 'food quality', 'positive'], ['food', '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 portions are small but being that the food was so good makes up for that."], "output": "[['portions', 'food style_options', '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": ["You must have the crabmeat lasagna which is out of this world and the chocolate bread pudding for dessert."], "output": "[['crabmeat lasagna', 'food quality', 'positive'], ['chocolate bread pudding', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['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 there is very attentive and down to earth."], "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 loved it and would go 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 Indian food and the service is incredible."], "output": "[['Indian food', 'food quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The owner truly caters to all your needs."], "output": "[['owner', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["When family came in he gave them apps to test their palets, and then ordered for them."], "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": ["Everyone was more then happy with his choices."], "output": "[['NULL', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Great food and the prices are very reasonable."], "output": "[['food', 'food quality', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food here does a great service to the name (Cantonese that is...)."], "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 fell in love with the egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork."], "output": "[['egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" 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 dish is my favorite and I always get it when I go there and never get tired of it."], "output": "[['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": ["Try the congee and the donut like deep fried dough they call Ow Ley Soh, a delicious and sweet tasting bread."], "output": "[['congee', 'food quality', 'positive'], ['Ow Ley Soh', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Simply some good tasting Chinese food at incredible prices..."], "output": "[['Chinese food', 'food quality', 'positive'], ['Chinese 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": ["Service is not what you are coming here for..."], "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": ["Big Wong is a great place to eat and fill your stomach."], "output": "[['Big Wong', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["whoever the jazz duo was, they were on POINT."], "output": "[['jazz duo', '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": ["good music, great food, speedy service affordable prices."], "output": "[['music', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['service', 'service general', 'positive'], ['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["even the wine by the glass was good."], "output": "[['wine by the glass', '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": ["its a little out of the way if you don't live in the neighborhood, but definitely worth the trip from wherever you are."], "output": "[['NULL', 'location 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": ["Consistently good Japanese Tapas."], "output": "[['Japanese Tapas', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Always good drinks and service is pretty good;"], "output": "[['drinks', 'drinks quality', 'positive'], ['service', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Atmosphere is nice and relaxed too..."], "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": ["A great place to meet up for some food and drinks... "], "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": ["Yakitori (bbq meats) is tasty too."], "output": "[['Yakitori (bbq meats)', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" 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 mind pre-sliced low quality fish, unfriendly staff and a sushi chef that looks like he is miserable then this is your place."], "output": "[['fish', 'food quality', 'negative'], ['staff', 'service general', 'negative'], ['sushi chef', '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": ["Price and quality of fish alone will keep us from making a return visit."], "output": "[['fish', 'food prices', 'negative'], ['fish', 'food quality', 'negative'], ['NULL', 'restaurant general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Wasn't going to share but I feel obligated...while sitting at the sushi bar dining we watched the chef accidentally drop a piece of Unagi on the floor and upon retrieving it from the floor proceed to use the piece in the delivery order he was preparing."], "output": "[['chef', '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": ["No thanks!!!"], "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, which is only a few months old, is perhaps Queens' biggest secret!"], "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": ["Fabulous decor - makes you feel like you're in a trendy Manhattan restaurant, very very good food, cheaply-priced, generally friendly staff, and if you're a Manhattanite, or spend most of your time in Manhattan, Rice Avenue will make you feel at home.....very Soho/Village/Upper West Side minus the expensive prices and pretentious clientele.....all on Roosevelt Avenue!"], "output": "[['decor', 'ambience general', 'positive'], ['food', 'food quality', 'positive'], ['food', 'food prices', 'positive'], ['staff', 'service general', 'positive'], ['Rice Avenue', 'ambience general', 'positive'], ['Rice Avenue', 'location general', 'positive'], ['Rice Avenue', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were seated outside and the waiter spilled red wine and hot tea on myself and my date."], "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 were then shooed inside."], "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": ["One would think we'd get an apology or complimentary drinks - instead, we got a snobby waiter wouldn't even take our order for 15 minutes and gave us lip when we asked him to do so."], "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 left, never to 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": ["With so many good restaurants on the UWS, I don't need overpriced food, absurdly arrogant wait-staff who don't recognize they work at a glorified diner, clumsy service, and management that doesn't care."], "output": "[['food', 'food prices', 'negative'], ['wait-staff', 'service general', 'negative'], ['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": ["I am relatively new to the area and tried Pick a bgel on 2nd and was disappointed with the service and I thought the food was overated and on the pricey side."], "output": "[['service', 'service general', 'negative'], ['food', 'food prices', '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 food is okay and the prices here are mediocre."], "output": "[['food', 'food quality', 'neutral'], ['NULL', 'restaurant prices', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Baluchi's has solid food and a nice decor at reasonable prices."], "output": "[['food', 'food quality', 'positive'], ['decor', 'ambience general', 'positive'], [\"Baluchi's\", '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 only problem is that the manager is a complete incompetent."], "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": ["He offers subpar service and has no personality."], "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": ["In fact, it appears he is going to go postal at any moment."], "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 is no excuse for such lousy 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": ["I have never before eaten 40 pieces of relatively good nigiri."], "output": "[['nigiri', '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": ["You can do it here."], "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": ["$20 for all you can eat sushi cannot be beaten."], "output": "[['all you can eat sushi', 'food prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I went to Areo on a Sunday afternoon with four of my girlfriends, and spent three enjoyable hours there."], "output": "[['Areo', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" 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 servers are very attentive, friendly and quite attractive."], "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": ["The vibe is very relaxed and cozy, service was great and the food was excellent!"], "output": "[['vibe', 'ambience general', 'positive'], ['service', 'service general', 'positive'], ['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Me and my girls will definitely go back."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Food was good and the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went."], "output": "[['Food', 'food quality', 'positive'], ['view of the new york city skiline', '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 recommand requesting a table by the window."], "output": "[['table by the window', '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": ["Although they do the typical what kind of water would you like questions the service was good and overall very relaxing to place to eat."], "output": "[['service', 'service general', 'positive'], ['place', 'ambience general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The food is great."], "output": "[['food', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Personal pans are the perfect size for those hungry nights."], "output": "[['Personal pans', '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 heartily recommend."], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["There is a downside if you're ordering in -- the delivery guys have MAJOR attitude."], "output": "[['delivery guys', '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 have I had such dramatic delivery guys (a lot of huffing and panting and muttering under breath b/c I live in a walkup) who always seem disappointed with their tips."], "output": "[['delivery guys', 'service general', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Love the scene first off- the place has a character and nice light to it..very fortunate, location wise."], "output": "[['scene', 'ambience general', 'positive'], ['place', 'ambience general', '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": ["The pizza was pretty good and huge."], "output": "[['pizza', '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": ["The price very reasonable."], "output": "[['NULL', 'restaurant prices', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["We were 4 and got the family size penne a la vodka which was tremendously gigantic portion...a bucket of food literally."], "output": "[['penne a la vodka', '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 would say that all was fine and tasty but the heaviness on my stomach someting that i can't not mention or undermine."], "output": "[['NULL', 'food quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["The pasta penne was pretty extra buttery, creamy which means a big task to diggest.. tasty at first but i would say that i was full with a slice of pizza and 7 to count, penne...got a little moody afterwards cause was stuffed...lol"], "output": "[['pasta penne', 'food quality', 'negative'], ['pasta penne', '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": ["La Rosa waltzes in, and I think they are doing it the best."], "output": "[['La Rosa', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Interesting selection, good wines, service fine, fun decor."], "output": "[['wines', 'drinks quality', 'positive'], ['service', 'service general', 'positive'], ['decor', 'ambience general', 'positive'], ['selection', '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 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 plan on stopping by next week as well."], "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 found it on a cold night, the perfect spot to warm up."], "output": "[['spot', 'restaurant miscellaneous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I recieved prompt service with a smile."], "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": ["To me it exemplifies Soho, cute, artsy, interesting."], "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": ["Definately check it out!!!"], "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 place blew me away...by far my new favorite restaurant on the uppereast side."], "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 wine list is extensive and impressive."], "output": "[['wine list', 'drinks style_options', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["LOVE the atmosphere - felt like I was in Paris."], "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 mussels were fantastic and so was the dessert...definitely going to be back very soon."], "output": "[['mussels', 'food quality', 'positive'], ['dessert', '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": ["I have been coming here for years and have nothing but good things to say about the service and the great staff at La Lanterna."], "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": ["Over the years the host, Vittorio, and his crew, have always treated me as family--although with all the business this not-so-little gem does, it amazing he's even able to remember a consistent but not-so-frequent visitor."], "output": "[['host', 'service general', 'positive'], ['crew', 'service general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I've also been amazed at all the new additions in the past few years: A new Jazz Bar, the most fantastic Dining Garden, the Best Thin Crust Pizzas, and now a Lasagna Menu which is to die for (these are not your average lasagnas)!"], "output": "[['Dining Garden', 'ambience general', 'positive'], ['Jazz Bar', 'ambience general', 'positive'], ['Thin Crust Pizzas', 'food quality', 'positive'], ['Lasagna 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": ["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": ["Keep up the good work guys!"], "output": "[['NULL', 'restaurant general', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["I have to say I have never had a disapointing meal here."], "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": ["We could have made a meal of the yummy dumplings from the dumpling menu."], "output": "[['dumplings', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |
| {"task_type": "generation", "dataset": "semeval-2015", "input": ["Luckily we saved room for the BBQ Salmon, Sea Bass and Crispy Duck."], "output": "[['BBQ Salmon', 'food quality', 'positive'], ['Sea Bass', 'food quality', 'positive'], ['Crispy Duck', 'food quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms, aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples where each tuple contains the extracted aspect term , aspect category their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"Delicate spices, onions, eggs and a kick-ass roti.\" Output: [['spices', 'food quality', 'positive'], ['onions', 'food quality', 'positive'], ['eggs', 'food quality', 'positive'], ['roti', 'food quality', 'positive']] "} | |