{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Boot time is super fast , around anywhere from 35 seconds to 1 minute ."], "output": "[['Boot time', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["tech support would not fix the problem unless I bought your plan for $ 150 plus ."], "output": "[['tech support', 'not fix', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Set up was easy ."], "output": "[['Set up', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Did not enjoy the new Windows 8 and touchscreen functions ."], "output": "[['Windows 8', 'not enjoy', 'negative'], ['touchscreen functions', 'not enjoy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Other than not being a fan of click pads ( industry standard these days ) and the lousy internal speakers , it 's hard for me to find things about this notebook I do n't like , especially considering the $ 350 price tag ."], "output": "[['internal speakers', 'lousy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's fast , light , and simple to use ."], "output": "[['use', 'fast', 'positive'], ['use', 'light', 'positive'], ['use', 'simple', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Works well , and I am extremely happy to be back to an apple OS ."], "output": "[['Works', 'well', 'positive'], ['apple OS', 'happy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sure it 's not light and slim but the features make up for it 100 % ."], "output": "[['features', 'not light and slim', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I am pleased with the fast log on , speedy WiFi connection and the long battery life ( > 6 hrs ) ."], "output": "[['log on', 'pleased', 'positive'], ['log on', 'fast', 'positive'], ['WiFi connection', 'pleased', 'positive'], ['WiFi connection', 'speedy', 'positive'], ['battery life', 'pleased', 'positive'], ['battery life', 'long', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Apple engineers have not yet discovered the delete key ."], "output": "[['delete key', 'not yet discovered', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Made interneting ( part of my business ) very difficult to maintain ."], "output": "[['interneting', 'difficult', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Luckily , for all of us contemplating the decision , the Mac Mini is priced just right ."], "output": "[['priced', 'right', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Only problem that I had was that the track pad was not very good for me , I only had a problem once or twice with it , But probably my computer was a bit defective ."], "output": "[['track pad', 'not very good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is super fast and has outstanding graphics ."], "output": "[['graphics', 'outstanding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the mountain lion is just too slow ."], "output": "[['mountain lion', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Strong build though which really adds to its durability ."], "output": "[['durability', 'Strong', 'positive'], ['build', 'Strong', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The battery life is excellent -- 6-7 hours without charging ."], "output": "[['battery life', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had my computer for 2 weeks already and it works perfectly ."], "output": "[['works', 'perfectly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And I may be the only one but I am really liking Windows 8 ."], "output": "[['Windows 8', 'liking', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The baterry is very longer ."], "output": "[['baterry', 'longer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Its size is ideal and the weight is acceptable ."], "output": "[['size', 'ideal', 'positive'], ['weight', 'acceptable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I can say that I am fully satisfied with the performance that the computer has supplied ."], "output": "[['performance', 'satisfied', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has so much more speed and the screen is very sharp ."], "output": "[['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything I wanted and everything I needed and the price was great !"], "output": "[['price', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's not inexpensive but the Hardware performance is impressive for a computer this small ."], "output": "[['Hardware performance', 'impressive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This thing is awesome , everything always works , everything is always easy to set up , everything is compatible , its literally everything I could ask for ."], "output": "[['works', 'always', 'positive'], ['set up', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Keyboard responds well to presses ."], "output": "[['Keyboard', 'responds well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Lastly , Windows 8 is annoying ."], "output": "[['Windows 8', 'annoying', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything is so easy and intuitive to setup or configure ."], "output": "[['setup', 'easy', 'positive'], ['setup', 'intuitive', 'positive'], ['configure', 'easy', 'positive'], ['configure', 'intuitive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Biggest complaint is Windows 8 ."], "output": "[['Windows 8', 'complaint', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Only 2 usb ports ... seems kind of ... limited ."], "output": "[['usb ports', 'limited', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has all the expected features and more +plus a wide screen and more than roomy keyboard ."], "output": "[['features', 'expected', 'positive'], ['screen', 'wide', 'positive'], ['keyboard', 'roomy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Amazing Performance for anything I throw at it ."], "output": "[['Performance', 'Amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The receiver was full of superlatives for the quality and performance ."], "output": "[['quality', 'superlatives', 'positive'], ['performance', 'superlatives', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was extremely happy with the OS itself ."], "output": "[['OS', 'happy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The new MBP offers great portability and gives us confidence that we are not going to need to purchase a new laptop in 18 months ."], "output": "[['portability', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The criticism has waned , and now I 'd be the first to recommend an Air for truly portable computing ."], "output": "[['portable computing', 'recommend', 'positive'], ['portable computing', 'truly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["MS Office 2011 for Mac is wonderful , well worth it ."], "output": "[['MS Office 2011 for Mac', 'wonderful', 'positive'], ['MS Office 2011 for Mac', 'well worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the performance of Mac Mini is a huge disappointment ."], "output": "[['performance', 'disappointment', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They do n't just look good ; they deliver excellent performance ."], "output": "[['look', 'good', 'positive'], ['performance', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have had it over a year now with out a Glitch of any kind..I love the lit up keys and screen display ... this thing is Fast and clear as can be ."], "output": "[['lit up keys', 'love', 'positive'], ['lit up keys', 'Fast', 'positive'], ['lit up keys', 'clear', 'positive'], ['screen display', 'love', 'positive'], ['screen display', 'Fast', 'positive'], ['screen display', 'clear', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Mountain Lion OS is not hard to figure out if you are familiar with Microsoft Windows ."], "output": "[['Mountain Lion OS', 'not hard', 'positive'], ['Microsoft Windows', 'familiar', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , I can refute that OSX is `` FAST '' ."], "output": "[['OSX', 'FAST', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Enjoy using Microsoft Office !"], "output": "[['Microsoft Office', 'Enjoy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Incredible graphics and brilliant colors ."], "output": "[['graphics', 'Incredible', 'positive'], ['colors', 'brilliant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Built-in apps are purely amazing ."], "output": "[['Built-in apps', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["From the speed to the multi touch gestures this operating system beats Windows easily ."], "output": "[['operating system', 'beats', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I really like the size and I 'm a fan of the ACERS ."], "output": "[['size', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I opted for the SquareTrade 3-Year Computer Accidental Protection Warranty ( $ 1500-2000 ) which also support `` accidents '' like drops and spills that are NOT covered by AppleCare ."], "output": "[['SquareTrade 3-Year Computer Accidental Protection Warranty', 'support', 'positive'], ['AppleCare', 'NOT covered', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's light and easy to transport ."], "output": "[['transport', 'light', 'positive'], ['transport', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Once you get past learning how to use the poorly designed Windows 8 Set-Up you may feel frustrated ."], "output": "[['Windows 8 Set-Up', 'poorly designed', 'negative'], ['Windows 8 Set-Up', 'frustrated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The aluminum body sure makes it stand out ."], "output": "[['aluminum body', 'stand out', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is very easy to integrate bluetooth devices , and USB devices are recognized almost instantly ."], "output": "[['integrate bluetooth devices', 'easy', 'positive'], ['USB devices', 'instantly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And the fact that Apple is driving the 13 '' RMBP with the Intel4000 graphic chip seems underpowered ( to me ."], "output": "[['Intel4000 graphic chip', 'underpowered', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Apple removed the DVD drive Firewire port ( will work with adapter ) and put the SDXC slot in a silly position on the back ."], "output": "[['DVD drive Firewire port', 'removed', 'neutral'], ['SDXC slot', 'silly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The durability of the laptop will make it worth the money ."], "output": "[['durability', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Well designed and fast ."], "output": "[['designed', 'Well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But I was completely wrong , this computer is UNBELIEVABLE amazing and easy to use ."], "output": "[['use', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Exactly as posted plus a great value ."], "output": "[['value', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The specs are pretty good too ."], "output": "[['specs', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Apple is unmatched in product quality , aesthetics , craftmanship , and customer service ."], "output": "[['product quality', 'unmatched', 'positive'], ['aesthetics', 'unmatched', 'positive'], ['craftmanship', 'unmatched', 'positive'], ['customer service', 'unmatched', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is a great size and amazing windows 8 included !"], "output": "[['size', 'great', 'positive'], ['windows 8', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I do not like too much Windows 8 ."], "output": "[['Windows 8', 'not like', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Startup times are incredibly long : over two minutes ."], "output": "[['Startup times', 'long', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also stunning colors and speedy"], "output": "[['colors', 'stunning', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great price free shipping what else can i ask for ! !"], "output": "[['price', 'great', 'positive'], ['shipping', 'free', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This mouse is terrific ."], "output": "[['mouse', 'terrific', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is really thick around the battery ."], "output": "[['battery', 'thick', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And windows 7 works like a charm ."], "output": "[['windows 7', 'charm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": [": ) Great product , great price , great delivery , and great service ."], "output": "[['price', 'great', 'positive'], ['delivery', 'great', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": [": ] It arrived so fast and customer service was great ."], "output": "[['customer service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["tried windows 8 and hated it ! ! !"], "output": "[['windows 8', 'hated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Set up was a breeze ."], "output": "[['Set up', 'breeze', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But I do NOT like Win8 ."], "output": "[['Win8', 'NOT like', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had the same reasons as most PC users : the price , the overbearing restrictions of OSX and lack of support for games ."], "output": "[['OSX', 'overbearing', 'negative'], ['support for games', 'lack', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I wanted it for it 's mobility and man , this little bad boy is very nice ."], "output": "[['mobility', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I found the mini to be : Exceptionally easy to set up"], "output": "[['set up', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sound is nice and loud ; I do n't have any problems with hearing anything ."], "output": "[['sound', 'nice', 'positive'], ['sound', 'loud', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is very slim , the track pad is very much impressed with me ."], "output": "[['track pad', 'slim', 'positive'], ['track pad', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The settings are not user-friendly either ."], "output": "[['settings', 'not user-friendly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Thank goodness for OpenOffice !"], "output": "[['OpenOffice', 'goodness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Awesome form factor , great battery life , wonderful UX ."], "output": "[['form factor', 'Awesome', 'positive'], ['battery life', 'great', 'positive'], ['UX', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i love the keyboard and the screen ."], "output": "[['keyboard', 'love', 'positive'], ['screen', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , there are MAJOR issues with the touchpad which render the device nearly useless ."], "output": "[['touchpad', 'issues', 'negative'], ['touchpad', 'useless', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've already upgraded o Mavericks and I am impressed with everything about this computer ."], "output": "[['Mavericks', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not as fast as I would have expect for an i5 ."], "output": "[['i5', 'Not as fast', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["thanks for great service and shipping !"], "output": "[['service', 'great', 'positive'], ['shipping', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The performance seems quite good , and built-in applications like iPhoto work great with my phone and camera ."], "output": "[['performance', 'good', 'positive'], ['built-in applications', 'great', 'positive'], ['iPhoto', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I did swap out the hard drive for a Samsung 830 SSD which I highly recommend ."], "output": "[['Samsung 830 SSD', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yes , that 's a good thing , but it 's made from aluminum that scratches easily ."], "output": "[['aluminum', 'scratches easily', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was also informed that the components of the Mac Book were dirty ."], "output": "[['components', 'dirty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the hardware problems have been so bad , i ca n't wait till it completely dies in 3 years , TOPS !"], "output": "[['hardware', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's so nice that the battery last so long and that this machine has the snow lion !"], "output": "[['battery', 'nice', 'positive'], ['battery', 'long', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it 's exactly what i wanted , and it has all the new features and whatnot ."], "output": "[['features', 'wanted', 'positive'], ['features', 'new', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It feels cheap , the keyboard is not very sensitive ."], "output": "[['keyboard', 'cheap', 'negative'], ['keyboard', 'not very sensitive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Though please note that sometimes it crashes , and the sound quality isnt superb ."], "output": "[['sound quality', 'isnt superb', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is very easy to navigate even for a novice ."], "output": "[['navigate', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Does everything I need it to , has a wonderful battery life and I could n't be happier ."], "output": "[['battery life', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Performance and Quality ."], "output": "[['Performance', 'Great', 'positive'], ['Quality', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["One more thing , this mac does NOT come with restore disks and I am not sure if you can make them direct from the mac like you can with newer PC 's , also the charging cables are made of the same cheap material as the iPhone/iPod touch cables ."], "output": "[['material', 'cheap', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The new os is great on my macbook pro !"], "output": "[['os', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have experienced no problems , works as anticipated ."], "output": "[['works', 'as anticipated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["System is running great ."], "output": "[['System', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Easy to customize setting and even create your own bookmarks ."], "output": "[['customize setting', 'Easy', 'positive'], ['create your own bookmarks', 'Easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it has all the features that we expected and the price was good , working well so far ."], "output": "[['price', 'good', 'positive'], ['working', 'well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The new operating system makes this computer into a super iPad ."], "output": "[['operating system', 'new', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Easy to set up and go !"], "output": "[['set up', 'Easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I ca n't believe how quiet the hard drive is and how quick this thing boots up ."], "output": "[['hard drive', 'quiet', 'positive'], ['boots up', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's just what we were looking for and it works great ."], "output": "[['works', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's so quick and responsive that it makes working / surfing on a computer so much more pleasurable !"], "output": "[['working', 'pleasurable', 'positive'], ['surfing', 'pleasurable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It works fine , and all the software seems to run pretty well ."], "output": "[['works', 'fine', 'positive'], ['software', 'well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I wanted a computer that was quite , fast , and that had overall great performance ."], "output": "[['performance', 'great', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Harddrive was in poor condition , had to replace it ."], "output": "[['Harddrive', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The on/off switch is a bit obscure in the rear corner ."], "output": "[['on/off switch', 'obscure', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My only complaint is the total lack of instructions that come with the mac mini ."], "output": "[['instructions', 'lack', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only task that this computer would not be good enough for would be gaming , otherwise the integrated Intel 4000 graphics work well for other tasks ."], "output": "[['gaming', 'not be good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I use it mostly for content creation ( Audio , video , photo editing ) and its reliable ."], "output": "[['Audio', 'reliable', 'positive'], ['video', 'reliable', 'positive'], ['photo editing', 'reliable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Screen is bright and gorgeous ."], "output": "[['Screen', 'bright', 'positive'], ['Screen', 'gorgeous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is robust , with a friendly use as all Apple products ."], "output": "[['use', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is fast and easy to use ."], "output": "[['use', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And the fact that it comes with an i5 processor definitely speeds things up"], "output": "[['i5 processor', 'speeds things up', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have been PC for years but this computer is intuitive and its built in features are a great help"], "output": "[['built in features', 'great help', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nice screen , keyboard works great !"], "output": "[['screen', 'Nice', 'positive'], ['keyboard', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was amazed at how fast the delivery was ."], "output": "[['delivery', 'amazed', 'positive'], ['delivery', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The memory was gone and it was not able to be used ."], "output": "[['memory', 'gone', 'negative'], ['memory', 'not able to be used', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It works great and I am so happy I bought it ."], "output": "[['works', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the design and ease of use with the keyboard , plenty of ports ."], "output": "[['design', 'like', 'positive'], ['keyboard', 'like', 'positive'], ['keyboard', 'ease of use', 'positive'], ['ports', 'plenty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it definitely beats my old mac and the service was great ."], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Web browsing is very quick with Safari browser ."], "output": "[['Web browsing', 'quick', 'positive'], ['Safari browser', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the lighted screen at night ."], "output": "[['lighted screen', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is really easy to use and it is quick to start up ."], "output": "[['use', 'easy', 'positive'], ['start up', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've lived with the crashes and slow operation and restarts ."], "output": "[['operation', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["USB3 Peripherals are noticably less expensive than the ThunderBolt ones ."], "output": "[['USB3 Peripherals', 'less expensive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's fast , light , and is perfect for media editing , which is mostly why I bought it in the first place ."], "output": "[['media editing', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The battery lasts as advertised ( give or take 15-20 minutes ) , and the entire user experience is very elegant ."], "output": "[['user experience', 'elegant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Thanks for the fast shipment and great price ."], "output": "[['shipment', 'fast', 'positive'], ['price', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["! Excellent performance , usability , presentation and time response ."], "output": "[['performance', 'Excellent', 'positive'], ['usability', 'Excellent', 'positive'], ['presentation', 'Excellent', 'positive'], ['time response', 'Excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The smaller size was a bonus because of space restrictions ."], "output": "[['size', 'smaller', 'positive'], ['size', 'bonus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I blame the Mac OS ."], "output": "[['Mac OS', 'blame', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the operating system ."], "output": "[['operating system', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the form factor ."], "output": "[['form factor', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's fast at loading the internet ."], "output": "[['loading the internet', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["So much faster and sleeker looking ."], "output": "[['looking', 'faster', 'positive'], ['looking', 'sleeker', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Unfortunately , it runs XP and Microsoft is dropping support next April ."], "output": "[['XP', 'Unfortunately', 'neutral'], ['support', 'Unfortunately', 'negative'], ['support', 'dropping', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["First off , I really do like my MBP ... once used to the OS it is pretty easy to get around , and the overall build is great ... eg the keyboard is one of the best to type on ."], "output": "[['OS', 'like', 'positive'], ['OS', 'easy', 'positive'], ['overall build', 'great', 'positive'], ['keyboard', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is made of such solid construction and since I have never had a Mac using my iPhone helped me get used to the system a bit ."], "output": "[['construction', 'solid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Very nice unibody construction ."], "output": "[['unibody construction', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This Macbook Pro is fast , powerful , and runs super quiet and cool ."], "output": "[['runs', 'quiet', 'positive'], ['runs', 'cool', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's ok but does n't have a disk drive which I did n't know until after I bought it ."], "output": "[['disk drive', \"does n't have\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There is no HDMI receptacle , nor is there an SD card slot located anywhere on the device ."], "output": "[['HDMI receptacle', 'no', 'neutral'], ['SD card slot', 'nor', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It came in brand new and works perfectly ."], "output": "[['works', 'perfectly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It should n't happen like that , I do n't have any design app open or anything ."], "output": "[['design app', \"do n't have\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["MY TRACKPAD IS NOT WORKING ."], "output": "[['TRACKPAD', 'NOT WORKING', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It looks and feels solid , with a flawless finish ."], "output": "[['finish', 'flawless', 'positive'], ['looks', 'solid', 'positive'], ['feels', 'solid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Price was higher when purchased on MAC when compared to price showing on PC when I bought this product ."], "output": "[['Price', 'higher', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Then the system would many times not power down without a forced power-off ."], "output": "[['system', 'not power down', 'negative'], ['power down', 'not', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The configuration is perfect for my needs ."], "output": "[['configuration', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["and the speakers is the worst ever ."], "output": "[['speakers', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Its the best , its got the looks , super easy to use and love all you can do with the trackpad ! .."], "output": "[['use', 'easy', 'positive'], ['trackpad', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Web surfuring is smooth and seamless ."], "output": "[['Web surfuring', 'smooth', 'positive'], ['Web surfuring', 'seamless', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 'm overall pleased with the interface and the portability of this product ."], "output": "[['interface', 'pleased', 'positive'], ['portability', 'pleased', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This item is a beautiful piece , it works well , it is easy to carry and handle ."], "output": "[['works', 'well', 'positive'], ['carry', 'easy', 'positive'], ['handle', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was also suffering from hardware ( keyboard ) issues , relatively slow performance and shortening battery lifetime ."], "output": "[['performance', 'slow', 'negative'], ['battery lifetime', 'shortening', 'negative'], ['hardware ( keyboard )', 'suffering', 'negative'], ['hardware ( keyboard )', 'issues', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Runs good and does the job , ca n't complain about that !"], "output": "[['Runs', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's silent and has a very small footprint on my desk ."], "output": "[['footprint', 'small', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The exterior is absolutely gorgeous ."], "output": "[['exterior', 'gorgeous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has a very high performance , just for what I needed for ."], "output": "[['performance', 'high', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Apple is aware of this issue and this is either old stock or a defective design involving the intel 4000 graphics chipset ."], "output": "[['intel 4000 graphics chipset', 'defective', 'neutral'], ['design', 'defective', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I just bought the new MacBook Pro , the 13 '' model , and I ca n't believe Apple keeps making the same mistake with regard to USB ports ."], "output": "[['USB ports', 'mistake', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is the perfect size and speed for me ."], "output": "[['size', 'perfect', 'positive'], ['speed', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE CUSTOMER SERVICE IS TERRIFIC ! !"], "output": "[['CUSTOMER SERVICE', 'TERRIFIC', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My last laptop was a 17 '' ASUS gaming machine , which performed admirably , but having since built my own desktop and really settling into the college life , I found myself wanting something smaller and less cumbersome , not to mention that the ASUS had been slowly developing problems ever since I bought it about 4 years ago ."], "output": "[['performed', 'admirably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , it did not have any scratches , ZERO battery cycle count ( pretty surprised ) , and all the hardware seemed to be working perfectly ."], "output": "[['battery cycle count', 'ZERO', 'positive'], ['battery cycle count', 'surprised', 'positive'], ['hardware', 'perfectly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And as for all the fancy finger swipes -- I just gave up and attached a mouse ."], "output": "[['finger swipes', 'fancy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I needed a laptop with big storage , a nice screen and fast so I can photoshop without any problem ."], "output": "[['storage', 'big', 'neutral'], ['screen', 'nice', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like coming back to Mac OS but this laptop is lacking in speaker quality compared to my $ 400 old HP laptop ."], "output": "[['Mac OS', 'like', 'positive'], ['speaker quality', 'lacking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Shipped very quickly and safely ."], "output": "[['Shipped', 'quickly', 'positive'], ['Shipped', 'safely', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The thunderbolt port is awesome !"], "output": "[['thunderbolt port', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The performance is definitely superior to any computer I 've ever put my hands on ."], "output": "[['performance', 'superior', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's great for streaming video and other entertainment uses ."], "output": "[['streaming video', 'great', 'positive'], ['entertainment uses', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the design and its features but there are somethings I think needs to be improved ."], "output": "[['design', 'like', 'positive'], ['features', 'needs to be improved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There were small problems with Mac office ."], "output": "[['Mac office', 'problems', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I ordered my 2012 mac mini after being disappointed with spec of the new 27 '' Imacs ."], "output": "[['spec', 'disappointed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Its fast , easy to use and it looks great ."], "output": "[['use', 'easy', 'positive'], ['looks', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Performance is much much better on the Pro , especially if you install an SSD on it ."], "output": "[['Performance', 'better', 'positive'], ['SSD', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Note , however , that any existing MagSafe accessories you have will not work with the MagSafe 2 connection ."], "output": "[['MagSafe accessories', 'not work', 'neutral'], ['MagSafe 2 connection', 'not work', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only thing I dislike is the touchpad , alot of the times its unresponsive and does things I dont want it too , I would recommend using a mouse with it ."], "output": "[['touchpad', 'dislike', 'negative'], ['touchpad', 'unresponsive', 'negative'], ['mouse', 'recommend', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Mac mini is about 8x smaller than my old computer which is a huge bonus and runs very quiet , actually the fans are n't audible unlike my old pc"], "output": "[['runs', 'quiet', 'positive'], ['fans', \"are n't audible\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I thought the transition would be difficult at best and would take some time to fully familiarize myself with the new Mac ecosystem ."], "output": "[['Mac ecosystem', 'take some time', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's absolutely wonderful and worth the price !"], "output": "[['price', 'wonderful', 'positive'], ['price', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I am please with the products ease of use ; out of the box ready ; appearance and functionality ."], "output": "[['use', 'please', 'positive'], ['use', 'ease', 'positive'], ['appearance', 'please', 'positive'], ['functionality', 'please', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Perfect for all my graphic design classes I 'm taking this year in college : - )"], "output": "[['graphic design', 'Perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I will not be using that slot again ."], "output": "[['slot', 'not be using', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The OS is fast and fluid , everything is organized and it 's just beautiful ."], "output": "[['OS', 'fast', 'positive'], ['OS', 'fluid', 'positive'], ['OS', 'organized', 'positive'], ['OS', 'beautiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They are simpler to use ."], "output": "[['use', 'simpler', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["! so nice .. stable .. fast .. now i got my SSD !"], "output": "[['SSD', 'nice', 'positive'], ['SSD', 'stable', 'positive'], ['SSD', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the quick start up ."], "output": "[['start up', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You just can not beat the functionality of an Apple device ."], "output": "[['functionality', 'can not beat', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yet my mac continues to function properly ."], "output": "[['function', 'properly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Graphics are much improved ."], "output": "[['Graphics', 'improved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Here are the things that made me confident with my purchase : Build Quality - Seriously , you ca n't beat a unibody construction ."], "output": "[['Build Quality', 'confident', 'positive'], ['unibody construction', \"ca n't beat\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It provides much more flexibility for connectivity ."], "output": "[['flexibility for connectivity', 'more', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mac tutorials do help ."], "output": "[['Mac tutorials', 'help', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The technical support was not helpful as well ."], "output": "[['technical support', 'not helpful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I got the new adapter and there was no change ."], "output": "[['adapter', 'new', 'neutral'], ['adapter', 'no change', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Logic board utterly fried , cried , and laid down and died ."], "output": "[['Logic board', 'utterly fried', 'positive'], ['Logic board', 'cried', 'positive'], ['Logic board', 'laid down', 'positive'], ['Logic board', 'died', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sound was crappy even when you turn up the volume still the same results ."], "output": "[['sound', 'crappy', 'negative'], ['volume', 'crappy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["OSX Lion is a great performer..extremely fast and reliable ."], "output": "[['OSX Lion', 'great', 'positive'], ['OSX Lion', 'fast', 'positive'], ['OSX Lion', 'reliable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Having heard from friends and family about how reliable a Mac product is , I never expected to have an application crash within the first month , but I did ."], "output": "[['application', 'crash', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Macbook pro 's physical form is wonderful ."], "output": "[['physical form', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Mini 's body has n't changed since late 2010- and for a good reason ."], "output": "[['body', \"has n't changed\", 'positive'], ['body', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The unibody construction really does feel lot more solid than Apple 's previous laptops ."], "output": "[['unibody construction', 'solid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["3D rendering slows it down considerably ."], "output": "[['3D rendering', 'slows it down', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["fast , great screen , beautiful apps for a laptop ; priced at 1100 on the apple website ; amazon had it for 1098+ tax - plus i had a 10 % off coupon from amazon-cost me 998 plus tax- 1070- OTD !"], "output": "[['screen', 'fast', 'positive'], ['screen', 'great', 'positive'], ['apps', 'beautiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All the ports are much needed since this is my main computer ."], "output": "[['ports', 'much needed', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Like New condition of the iMac MC309LL/A on Amazon is at $ 900+ level only , and it is a Quad-Core 2.5 GHz CPU ( similar to the $ 799 Mini ) , with Radeon HD 6750M 512MB graphic card ( this mini is integrated Intel 4000 card ) , and it even comes with wireless Apple Keyboard and Mouse , all put together in neat and nice package ."], "output": "[['package', 'neat', 'positive'], ['package', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Put a cover on it and is a little better but that is my only complaint ."], "output": "[['cover', 'a little better', 'neutral'], ['cover', 'complaint', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Within a few hours I was using the gestures unconsciously ."], "output": "[['gestures', 'unconsciously', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This mac does come with an extender cable and I 'm using mine right now hoping the cable will stay nice for the many years I plan on using this mac ."], "output": "[['cable', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The 2.9ghz dual-core i7 chip really out does itself ."], "output": "[['2.9ghz dual-core i7 chip', 'really', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is pretty snappy and starts up in about 30 seconds which is good enough for me ."], "output": "[['starts up', 'snappy', 'positive'], ['starts up', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not sure on Windows 8 ."], "output": "[['Windows 8', 'Not sure', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My one complaint is that there was no internal CD drive ."], "output": "[['internal CD drive', 'complaint', 'negative'], ['internal CD drive', 'no', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This newer netbook has no hard drive or network lights ."], "output": "[['hard drive', 'no', 'neutral'], ['network lights', 'no', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not too expense and has enough storage for most users and many ports ."], "output": "[['storage', 'enough', 'positive'], ['ports', 'enough', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The audio volume is quite low and virtually unusable in a room with any background activity ."], "output": "[['audio volume', 'low', 'negative'], ['audio volume', 'unusable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is lightweight and the perfect size to carry to class ."], "output": "[['size', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The MBP is beautiful has many wonderful capabilities ."], "output": "[['capabilities', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I thought that it will be fine , if i do some settings ."], "output": "[['settings', 'fine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Runs very smoothly ."], "output": "[['Runs', 'smoothly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Boot-up slowed significantly after all Windows updates were installed ."], "output": "[['Boot-up', 'slowed', 'negative'], ['Windows updates', 'slowed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was important that it was powerful enough to do all of the tasks he needed on the internet , word processing , graphic design and gaming ."], "output": "[['internet', 'powerful', 'positive'], ['word processing', 'powerful', 'positive'], ['graphic design', 'powerful', 'positive'], ['gaming', 'powerful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the Mini Mac it was easy to setup and install , but I am learning as I go and could use a tutorial to learn how to use some of the features I was use to on the PC especially the right mouse click menu ."], "output": "[['setup', 'like', 'positive'], ['setup', 'easy', 'positive'], ['install', 'like', 'positive'], ['install', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Runs real quick ."], "output": "[['Runs', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Since the machine 's slim profile is critical to me , that was a problem ."], "output": "[['profile', 'slim', 'negative'], ['profile', 'critical', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["WiFi capability , disk drive and multiple USB ports to connect scale and printers was all that was required ."], "output": "[['disk drive', 'required', 'positive'], ['USB ports', 'required', 'positive'], ['WiFi capability', 'required', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The SD card reader is slightly recessed and upside down ( the nail slot on the card can not be accessed ) , if this was a self ejecting slot this would not be an issue , but its not ."], "output": "[['SD card reader', 'recessed', 'negative'], ['SD card reader', 'upside down', 'negative'], ['nail slot on the card', 'can not be accessed', 'negative'], ['slot', 'issue', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Soft touch , anodized aluminum with laser cut precision and no flaws ."], "output": "[['touch', 'Soft', 'positive'], ['anodized aluminum', 'precision', 'positive'], ['anodized aluminum', 'no flaws', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Simple details , crafted aluminium and real glass make this laptop blow away the other plastic ridden , bulky sticker filled laptops ."], "output": "[['aluminium', 'crafted', 'positive'], ['glass', 'blow away', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["First of all yes this is a mac and it has that nice brushed aluminum ."], "output": "[['aluminum', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["No HDMI port ."], "output": "[['HDMI port', 'No', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Customization on mac is impossible ."], "output": "[['Customization', 'impossible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Plus two finger clicking as a replacement for the right click button is surprisingly intuitive ."], "output": "[['two finger clicking', 'surprisingly', 'positive'], ['right click button', 'intuitive', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The SuperDrive is quiet ."], "output": "[['SuperDrive', 'quiet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The battery was completely dead , in fact it had grown about a quarter inch thick lump on the underside ."], "output": "[['battery', 'dead', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["if yo like practicality this is the laptop for you ."], "output": "[['practicality', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The OS is great ."], "output": "[['OS', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["CONS : Price is a bit ridiculous , kinda heavy ."], "output": "[['Price', 'ridiculous', 'negative'], ['Price', 'heavy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Which it did not have , only 3 USB 2 ports ."], "output": "[['USB 2 ports', 'not have', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["No startup disk was not included but that may be my fault ."], "output": "[['startup disk', 'No', 'neutral'], ['startup disk', 'not included', 'neutral'], ['startup disk', 'fault', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is very fast and has everything that I need except for a word program ."], "output": "[['word program', 'except for', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Needs a CD/DVD drive and a bigger power switch ."], "output": "[['power switch', 'bigger', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My laptop with Windows 7 crashed and I did not want Windows 8 ."], "output": "[['Windows 7', 'crashed', 'negative'], ['Windows 8', 'not want', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Easy to install also small to leave anywhere at your bedroom also very easy to configure for ADSl cable or wifi ."], "output": "[['install', 'Easy', 'positive'], ['configure for ADSl cable or wifi', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nice packing ."], "output": "[['packing', 'Nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I switched to this because I wanted something different , even though I miss windows ."], "output": "[['windows', 'miss', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Apple no longer includes iDVD with the computer and furthermore , Apple does n't even offer it anymore !"], "output": "[['iDVD', 'no longer includes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I also wanted Windows 7 , which this one has ."], "output": "[['Windows 7', 'wanted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["At first , I feel a little bit uncomfortable in using the Mac system ."], "output": "[['Mac system', 'uncomfortable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It just works out of the box and you have a lot of cool software included with the OS ."], "output": "[['works', 'out of the box', 'positive'], ['software', 'cool', 'positive'], ['OS', 'cool', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["its as advertised on here ... .. it works great and is not a waste of money !"], "output": "[['works', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Premium price for the OS more than anything else ."], "output": "[['price', 'Premium', 'positive'], ['OS', 'Premium', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was a little concerned about the touch pad based on reviews , but I 've found it fine to work with ."], "output": "[['touch pad', 'concerned', 'positive'], ['touch pad', 'fine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , the experience was great since the OS does not become unstable and the application will simply shutdown and reopen ."], "output": "[['OS', 'great', 'positive'], ['OS', 'not become unstable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The battery is not as shown in the product photos ."], "output": "[['battery', 'not as shown', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Shipping was quick and product described was the product sent and so much more ..."], "output": "[['Shipping', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the retina display display make pictures i took years ago jaw dropping ."], "output": "[['retina display display', 'dropping', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Mac Mini is probably the simplest example of compact computing out there ."], "output": "[['compact computing', 'simplest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Additionally , there is barely a ventilation system in the computer , and even the simple activity of watching videos let alone playing steam games causes the laptop to get very very hot , and in fact impossible to keep on lap ."], "output": "[['ventilation system', 'barely', 'negative'], ['ventilation system', 'hot', 'negative'], ['watching videos', 'simple', 'neutral'], ['watching videos', 'hot', 'neutral'], ['playing steam games', 'hot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Chatting with Acer support , I was advised the problem was corrupted operating system files ."], "output": "[['operating system files', 'corrupted', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's been a couple weeks since the purchase and I 'm struggle with finding the correct keys ( but that was expected ) ."], "output": "[['keys', 'struggle', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Many people complain about the new OS , and it 's urgent for Apple to fix it asap !"], "output": "[['OS', 'complain', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Now that I have upgraded to Lion I am much happier about MAC OS and have just bought an iMac for office ."], "output": "[['Lion', 'upgraded', 'positive'], ['MAC OS', 'happier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["User upgradeable RAM and HDD ."], "output": "[['RAM', 'upgradeable', 'positive'], ['HDD', 'upgradeable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But I wanted the Pro for the CD/DVD player ."], "output": "[['CD/DVD player', 'wanted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was a little worry at first because I do n't have a lot of experience with os.x and windows has always been second nature to me after many years of using windows ."], "output": "[['os.x', 'worry', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["With the softwares supporting the use of other OS makes it much better ."], "output": "[['OS', 'better', 'neutral'], ['softwares', 'better', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was considering buying the Air , but in reality , this one has a more powerful performance and seems much more convenient , even though it 's about .20 inch thicker and 2 lbs heavier ."], "output": "[['performance', 'powerful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["At home and the office it gets plugged into an external 24 '' LCD screen , so built in screen size is not terribly important ."], "output": "[['built in screen size', 'not terribly important', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Just beware no DVD slot so when I went to install software I had on CD I could n't ."], "output": "[['DVD slot', 'no', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["No Cd Rom in the new version there 's no way I 'm spending that kind of money on something has less features than the older version ."], "output": "[['Cd Rom', 'No', 'neutral'], ['features', 'less', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the volume is really low to low for a laptopwas not expectin t volume to be so lowan i hate that about this computer"], "output": "[['volume', 'low', 'negative'], ['volume', 'hate', 'negative'], ['volume', 'low', 'negative'], ['volume', 'hate', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["and its not hard to accidentally bang it against something so i recommend getting a case to protect it ."], "output": "[['case', 'recommend', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I got this at an amazing price from Amazon and it arrived just in time ."], "output": "[['price', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Every time I log into the system after a few hours , there is this endlessly frustrating process that I have to go through ."], "output": "[['log into the system', 'frustrating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Put a SSD and use a 21 '' LED screen , this set up is silky smooth !"], "output": "[['set up', 'silky smooth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The case is now slightly larger than the previous generation , but the lack of an external power supply justifies the small increase in size ."], "output": "[['case', 'larger', 'negative'], ['external power supply', 'lack', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had to buy a wireless mouse to go with it , as I am old school and hate the pad , but knew that before I bought it , now it works great , need to get adjusted to the key board , as I am used to a bigger one and pounding ."], "output": "[['pad', 'hate', 'negative'], ['works', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Has all the other features I wanted including a VGA port , HDMI , ethernet and 3 USB ports ."], "output": "[['features', 'wanted', 'positive'], ['VGA port', 'wanted', 'neutral'], ['HDMI', 'wanted', 'neutral'], ['ethernet', 'wanted', 'neutral'], ['USB ports', 'wanted', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only thing I dislike about this laptop are the rubber pads found on the bottom of the computer for grip ."], "output": "[['rubber pads', 'dislike', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a decent computer for the price and hopefully it will last a long time ."], "output": "[['price', 'decent', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The nicest part is the low heat output and ultra quiet operation ."], "output": "[['heat output', 'nicest', 'positive'], ['heat output', 'low', 'positive'], ['operation', 'nicest', 'positive'], ['operation', 'quiet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["this Mac Mini does not have a built-in mic , and it would seem that its Mac OS 10.9 does not handle external microphones properly ."], "output": "[['built-in mic', 'not have', 'neutral'], ['Mac OS 10.9', 'not handle', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A lot of features and shortcuts on the MBP that I was never exposed to on a normal PC ."], "output": "[['features', 'lot of', 'neutral'], ['shortcuts', 'lot of', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Was n't sure if I was going to like it much less love it so I went to a local best buy and played around with the IOS system on a Mac Pro and it was totally unique and different ."], "output": "[['IOS system', 'unique', 'positive'], ['IOS system', 'different', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["air has higher resolution but the fonts are small ."], "output": "[['resolution', 'higher', 'positive'], ['fonts', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["working with Mac is so much easier , so many cool features ."], "output": "[['working', 'easier', 'positive'], ['features', 'cool', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like the brightness and adjustments ."], "output": "[['brightness', 'like', 'positive'], ['adjustments', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I only wish this mac had a CD/DVD player built in ."], "output": "[['CD/DVD player', 'wish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only thing I miss is that my old Alienware laptop had backlit keys ."], "output": "[['backlit keys', 'miss', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["So happy with this purchase , I just wish it came with Microsoft Word ."], "output": "[['Microsoft Word', 'wish', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has enough memory and speed to run my business with all the flexibility that comes with a laptop ."], "output": "[['memory', 'enough', 'positive'], ['speed', 'enough', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The battery life is excellent , the display is excellent , and downloading apps is a breeze ."], "output": "[['battery life', 'excellent', 'positive'], ['display', 'excellent', 'positive'], ['downloading apps', 'breeze', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The screen , the software and the smoothness of the operating system ."], "output": "[['operating system', 'smoothness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But with this laptop , the bass is very weak and the sound comes out sounding tinny ."], "output": "[['bass', 'weak', 'negative'], ['sound', 'tinny', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The built quality is really good , I was so Happy and excited about this Product ."], "output": "[['built quality', 'good', 'positive'], ['built quality', 'Happy', 'positive'], ['built quality', 'excited', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I am loving the fast performance also ."], "output": "[['performance', 'loving', 'positive'], ['performance', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Further , this Mac Mini has a sloppy Bluetooth interface ( courtesy of the Mac OS ) and the range is poor ."], "output": "[['Bluetooth interface', 'sloppy', 'negative'], ['Mac OS', 'courtesy', 'negative'], ['range', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My only gripe would be the need to add more RAM ."], "output": "[['RAM', 'gripe', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fine if you have a touch screen ."], "output": "[['touch screen', 'Fine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This by far beats any computer out on the market today built well , battery life AMAZING ."], "output": "[['built', 'well', 'positive'], ['battery life', 'AMAZING', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The OS is easy , and offers all kinds of surprises ."], "output": "[['OS', 'easy', 'positive'], ['OS', 'surprises', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A veryimportant feature is Firewire 800 which in my experience works better then USB3 ( in PC enabled with USB3 ) I was not originally sold on the MAC OS I felt it was inferior in many ways To Windows 7 ."], "output": "[['Firewire 800', 'veryimportant', 'positive'], ['Firewire 800', 'better', 'positive'], ['MAC OS', 'inferior', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I like iTunes , the apparent security , the Mini form factor , all the nice graphics stuff ."], "output": "[['iTunes', 'like', 'positive'], ['security', 'apparent', 'positive'], ['graphics stuff', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["After replacing the spinning hard disk with an ssd drive , my mac is just flying ."], "output": "[['ssd drive', 'flying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I know some people complained about HDMI issues but they released a firmware patch to address that issue ."], "output": "[['HDMI', 'complained', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["With the needs of a professional photographer I generally need to keep up with the best specs ."], "output": "[['specs', 'best', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["packing and everything was perfect"], "output": "[['packing', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I called Toshiba where I gave them the serial number and they informed me that they were having issues with the mother boards ."], "output": "[['mother boards', 'issues', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I seem to be having repeat problems as the Mother Board in this one is diagnosed as faulty , related to the graphics card ."], "output": "[['Mother Board', 'faulty', 'negative'], ['graphics card', 'faulty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It also comes with 4G of RAM but if you 're like me you want to max that out so I immediately put 8G of RAM in her and I 've never used a computer that performs better ."], "output": "[['performs', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This computer is also awesome for my sons virtual home schooling ."], "output": "[['virtual home schooling', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cost is more as compared to other brands ."], "output": "[['Cost', 'more', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["also ... - excellent operating system -- size and weight for optimal mobility -- excellent durability of the battery -- the functions provided by the trackpad is unmatched by any other brand-"], "output": "[['operating system', 'excellent', 'positive'], ['size', 'excellent', 'positive'], ['weight', 'excellent', 'positive'], ['mobility', 'optimal', 'positive'], ['durability of the battery', 'excellent', 'positive'], ['functions provided by the trackpad', 'unmatched', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This hardware seems to be better than the iMac in that it is n't $ 1400 and smaller ."], "output": "[['hardware', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had it for about 2 months now and found no issues with software or updates ."], "output": "[['software', 'no issues', 'neutral'], ['updates', 'no issues', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the latest version does not have a disc drive ."], "output": "[['disc drive', 'not have', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Screen - although some people might complain about low res which I think is ridiculous ."], "output": "[['Screen', 'complain', 'positive'], ['Screen', 'ridiculous', 'positive'], ['res', 'low', 'positive'], ['res', 'ridiculous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bread is top notch as well ."], "output": "[['bread', 'top notch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have to say they have one of the fastest delivery times in the city ."], "output": "[['delivery times', 'fastest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food is always fresh and hot ready to eat !"], "output": "[['Food', 'fresh', 'positive'], ['Food', 'hot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Did I mention that the coffee is OUTSTANDING ?"], "output": "[['coffee', 'OUTSTANDING', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Certainly not the best sushi in New York , however , it is always fresh , and the place is very clean , sterile ."], "output": "[['place', 'clean', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I trust the people at Go Sushi , it never disappoints ."], "output": "[['people', 'trust', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Straight-forward , no surprises , very decent Japanese food ."], "output": "[['Japanese food', 'decent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["BEST spicy tuna roll , great asian salad ."], "output": "[['asian salad', 'great', 'positive'], ['spicy tuna roll', 'BEST', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the rose roll ( not on menu ) ."], "output": "[['rose roll', 'Try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the drinks , esp lychee martini , and the food is also VERY good ."], "output": "[['drinks', 'love', 'positive'], ['lychee martini', 'love', 'positive'], ['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While there 's a decent menu , it should n't take ten minutes to get your drinks and 45 for a dessert pizza ."], "output": "[['menu', 'decent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Once we sailed , the top-notch food and live entertainment sold us on a unforgettable evening ."], "output": "[['food', 'top-notch', 'positive'], ['live entertainment', 'top-notch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our waiter was horrible ; so rude and disinterested ."], "output": "[['waiter', 'horrible', 'negative'], ['waiter', 'rude', 'negative'], ['waiter', 'disinterested', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sangria 's - watered down ."], "output": "[['sangria', 'watered down', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["menu - uneventful , small ."], "output": "[['menu', 'uneventful', 'negative'], ['menu', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Anytime and everytime I find myself in the neighborhood I will go to Sushi Rose for fresh sushi and great portions all at a reasonable price ."], "output": "[['sushi', 'fresh', 'positive'], ['portions', 'great', 'positive'], ['price', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food but the service was dreadful !"], "output": "[['food', 'Great', 'positive'], ['service', 'dreadful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The portions of the food that came out were mediocre ."], "output": "[['portions of the food', 'mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["From the beginning , we were met by friendly staff memebers , and the convenient parking at Chelsea Piers made it easy for us to get to the boat ."], "output": "[['staff memebers', 'friendly', 'positive'], ['parking', 'convenient', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Desserts are almost incredible : my personal favorite is their Tart of the Day ."], "output": "[['Desserts', 'incredible', 'positive'], ['Tart of the Day', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was extremely tasty , creatively presented and the wine excellent ."], "output": "[['food', 'tasty', 'positive'], ['food', 'creatively presented', 'positive'], ['wine', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE LASAGNA WAS PROBABLY THE BEST I HAVE TASTED ."], "output": "[['LASAGNA', 'BEST', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Harumi Sushi has the freshest and most delicious array of sushi in NYC ."], "output": "[['array of sushi', 'freshest', 'positive'], ['array of sushi', 'most delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I highly recommend it for not just its superb cuisine , but also for its friendly owners and staff ."], "output": "[['cuisine', 'superb', 'positive'], ['owners', 'friendly', 'positive'], ['staff', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you 're craving some serious indian food and desire a cozy ambiance , this is quiet and exquisite choice ."], "output": "[['indian food', 'serious', 'positive'], ['ambiance', 'cozy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I definitely enjoyed the food as well ."], "output": "[['food', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was pleasantly uncrowded , the service was delightful , the garden adorable , the food ( from appetizers to entrees ) was delectable ."], "output": "[['service', 'delightful', 'positive'], ['garden', 'adorable', 'positive'], ['food', 'delectable', 'positive'], ['appetizers', 'delectable', 'positive'], ['entrees', 'delectable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is surprisingly good , and the decor is nice ."], "output": "[['food', 'good', 'positive'], ['decor', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["How pretentious and inappropriate for MJ Grill to claim that it provides power lunch and dinners !"], "output": "[['lunch', 'power', 'negative'], ['dinners', 'power', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Two wasted steaks -- what a crime !"], "output": "[['steaks', 'wasted', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff should be a bit more friendly ."], "output": "[['staff', 'friendly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I think the meatball parm is good ."], "output": "[['meatball parm', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you want good tasting , well seasoned latin food eat at Cabana and you ca n't go wrong ."], "output": "[['latin food', 'good tasting', 'positive'], ['latin food', 'well seasoned', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Definitely try the taglierini with truffles - it was incredible ."], "output": "[['taglierini with truffles', 'try', 'positive'], ['taglierini with truffles', 'incredible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also , the staff is very attentive and really personable ."], "output": "[['staff', 'attentive', 'positive'], ['staff', 'personable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The gnocchi literally melts in your mouth !"], "output": "[['gnocchi', 'melts', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had a great experience at Trio ... staff was pleasant ; food was tasty and large in portion size - I would highly recommend the portobello/gorgonzola/sausage appetizer and the lobster risotto ."], "output": "[['staff', 'pleasant', 'positive'], ['food', 'tasty', 'positive'], ['portion size', 'large', 'positive'], ['portobello/gorgonzola/sausage appetizer', 'recommend', 'positive'], ['lobster risotto', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is good , the teriyaki I recommend ."], "output": "[['food', 'good', 'positive'], ['teriyaki', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Meal was very expensive for what you get ."], "output": "[['Meal', 'expensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the Peanut Butter Sorbet and the pizza with soy cheese !"], "output": "[['Peanut Butter Sorbet', 'Try', 'positive'], ['pizza with soy cheese', 'Try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good food at the right price , what more can you ask for ."], "output": "[['food', 'Good', 'positive'], ['price', 'right', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is top notch , the service is attentive , and the atmosphere is great ."], "output": "[['food', 'top notch', 'positive'], ['service', 'attentive', 'positive'], ['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , great waitstaff , great atmosphere , and best of all GREAT beer !"], "output": "[['food', 'Great', 'positive'], ['waitstaff', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['beer', 'best', 'positive'], ['beer', 'GREAT', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["this is still one of my most favorite restaurants in the area the food is inexpensive but very good ( kimono shrimp special was excellent ) and has a great atmosphere ."], "output": "[['food', 'inexpensive', 'positive'], ['food', 'good', 'positive'], ['kimono shrimp special', 'excellent', 'positive'], ['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu is interesting and quite reasonably priced ."], "output": "[['menu', 'interesting', 'positive'], ['menu', 'reasonably priced', 'positive'], ['priced', 'reasonably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was delicious and clearly fresh ingredients were used ."], "output": "[['food', 'delicious', 'positive'], ['ingredients', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This made it obvious that the food was n't cooked fresh ; it was obviously made before hand and then reheated ."], "output": "[['food', \"was n't cooked fresh\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Appetizer are excellent here ; you can make a great ( and inexpensive ) meal out of them ."], "output": "[['Appetizer', 'excellent', 'positive'], ['meal', 'great', 'positive'], ['meal', 'inexpensive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The spicy mussels are a highlight ."], "output": "[['spicy mussels', 'highlight', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also get the Onion Rings -- best we 've ever had ."], "output": "[['Onion Rings', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , being foodies , we were utterly disappointed with the food ."], "output": "[['food', 'utterly disappointed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Huge portions , great and attentive service , and pretty good prices ."], "output": "[['portions', 'Huge', 'positive'], ['service', 'great', 'positive'], ['service', 'attentive', 'positive'], ['prices', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was highly disappointed by their service and food ."], "output": "[['service', 'disappointed', 'negative'], ['food', 'disappointed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I complained to the waiter and then to the manager , but the intensity of rudeness from them just went up ."], "output": "[['waiter', 'rudeness', 'negative'], ['manager', 'rudeness', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great and the milkshakes are even better !"], "output": "[['food', 'great', 'positive'], ['milkshakes', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the mushroom barley soup is amazing ."], "output": "[['mushroom barley soup', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 'm glad I did as the food was very good and the staff was friendly , courteous and efficient ."], "output": "[['food', 'good', 'positive'], ['staff', 'friendly', 'positive'], ['staff', 'courteous', 'positive'], ['staff', 'efficient', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Their duck here is also absolutely delicious ."], "output": "[['duck', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While it was large and a bit noisy , the drinks were fantastic , and the food was superb ."], "output": "[['drinks', 'fantastic', 'positive'], ['food', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["One caveat : Some of the curried casseroles can be a trifle harsh ."], "output": "[['curried casseroles', 'harsh', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was almost always EXCELLENT ."], "output": "[['food', 'EXCELLENT', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was pleasantly surprised at the taste ."], "output": "[['taste', 'pleasantly surprised', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A nice space , as long as it does n't get too crowded and a singleminded devotion to its chosen cuisine make Mare a great choice for seafood lovers ."], "output": "[['seafood', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["they really provide a relaxing , laid-back atmosphere ."], "output": "[['atmosphere', 'relaxing', 'positive'], ['atmosphere', 'laid-back', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This particular location certainly uses substandard meats ."], "output": "[['meats', 'substandard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Management was less than accomodating ."], "output": "[['Management', 'less than accomodating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The ambience is also more laid-back and relaxed ."], "output": "[['ambience', 'laid-back', 'positive'], ['ambience', 'relaxed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the teas are great and all the sweets are homemade ."], "output": "[['teas', 'great', 'positive'], ['sweets', 'homemade', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["mojitos and the service are the best part in there"], "output": "[['mojitos', 'best', 'positive'], ['service', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sandwiches , burgers and salads , like the lemon-dressed cobb , are classic successes ."], "output": "[['Sandwiches', 'classic successes', 'positive'], ['burgers', 'classic successes', 'positive'], ['salads', 'classic successes', 'positive'], ['lemon-dressed cobb', 'classic successes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The design is very intimate and romantic ."], "output": "[['design', 'intimate', 'positive'], ['design', 'romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was wonderful and imaginative ."], "output": "[['food', 'wonderful', 'positive'], ['food', 'imaginative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is very sharp and they look good too ."], "output": "[['staff', 'sharp', 'positive'], ['staff', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The worst though was the taste ."], "output": "[['taste', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The fajita we tried was tasteless and burned and the mole sauce was way too sweet ."], "output": "[['fajita', 'tasteless', 'negative'], ['fajita', 'burned', 'negative'], ['mole sauce', 'too sweet', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere is warm , comfortable , artsy and sexy ."], "output": "[['atmosphere', 'warm', 'positive'], ['atmosphere', 'artsy', 'positive'], ['atmosphere', 'sexy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great ( big selection , reasonable prices ) and the drinks are really good ."], "output": "[['food', 'great', 'positive'], ['selection', 'big', 'positive'], ['prices', 'reasonable', 'positive'], ['drinks', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food did take a few extra minutes to come , but the cute waiters ' jokes and friendliness made up for it ."], "output": "[['waiters', 'cute', 'positive'], ['waiters', 'friendliness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Most importantly , it is reasonably priced ."], "output": "[['priced', 'reasonably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The selection of food is excellent ( I 'm not used to having much choice at restaurants ) , and the atmosphere is great ."], "output": "[['selection of food', 'excellent', 'positive'], ['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Only suggestion is that you skip the dessert , it was overpriced and fell short on taste ."], "output": "[['dessert', 'overpriced', 'negative'], ['taste', 'short', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food was decent , but not great ."], "output": "[['Food', 'decent', 'positive'], ['Food', 'not great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it is a hidden delight complete with a quaint bar and good food ."], "output": "[['bar', 'quaint', 'positive'], ['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiters ALWAYS look angry and even ignore their high-tipping regulars ."], "output": "[['waiters', 'angry', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the atmosphere is very nice , and a welcome escape from the rest of the SI mall ."], "output": "[['atmosphere', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yes , they 're a bit more expensive then typical , but then again , so is their food ."], "output": "[['food', 'more expensive then typical', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I can say that the wraps , burgers and salads were all fresh , tasty and the mango margareta at $ 9 was WELL WORTH the money ."], "output": "[['wraps', 'fresh', 'positive'], ['wraps', 'tasty', 'positive'], ['burgers', 'fresh', 'positive'], ['burgers', 'tasty', 'positive'], ['salads', 'fresh', 'positive'], ['salads', 'tasty', 'positive'], ['mango margareta', 'WELL WORTH', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service we experienced was friendly and good ."], "output": "[['service', 'friendly', 'positive'], ['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our waiter was friendly and it is a shame that he didnt have a supportive staff to work with ."], "output": "[['waiter', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The folding chair I was seated at was uncomfortable ."], "output": "[['folding chair', 'uncomfortable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was among the best I have ever had in NYC ."], "output": "[['Service', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The fettucino alfredo was amazing ."], "output": "[['fettucino alfredo', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was very good and I was pleasantly surprised to see so many vegan options ."], "output": "[['food', 'good', 'positive'], ['vegan options', 'many', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Be sure to try the Smoked Trout ... Lamb Chops , Veal Chops , Rabbit , the potato gratin , on and on and on ..."], "output": "[['Smoked Trout', 'try', 'positive'], ['Lamb Chops', 'try', 'positive'], ['Veal Chops', 'try', 'positive'], ['Rabbit', 'try', 'positive'], ['potato gratin', 'try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Even when the chef is not in the house , the food and service are right on target ."], "output": "[['food', 'right on target', 'positive'], ['service', 'right on target', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything from the eggs benedict to the mussels and even the hamburger were done well and very tasty ."], "output": "[['eggs benedict', 'well', 'positive'], ['eggs benedict', 'tasty', 'positive'], ['mussels', 'well', 'positive'], ['mussels', 'tasty', 'positive'], ['hamburger', 'well', 'positive'], ['hamburger', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiters were very professional , courteous and attentive ."], "output": "[['waiters', 'professional', 'positive'], ['waiters', 'courteous', 'positive'], ['waiters', 'attentive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The falafal was rather over cooked and dried but the chicken was fine ."], "output": "[['falafal', 'over cooked', 'negative'], ['falafal', 'dried', 'negative'], ['chicken', 'fine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I highly recommend the grand marnier shrimp , it 's insanely good ."], "output": "[['grand marnier shrimp', 'recommend', 'positive'], ['grand marnier shrimp', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We been there and we really enjoy the food , was areally great food , and the service was really good ."], "output": "[['food', 'enjoy', 'positive'], ['food', 'great', 'positive'], ['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was starving and the small portions were driving me crazy !"], "output": "[['portions', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wait staff was loud and inconsiderate ."], "output": "[['wait staff', 'loud', 'negative'], ['wait staff', 'inconsiderate', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , the food and service and dramatically lacking ."], "output": "[['food', 'lacking', 'negative'], ['service', 'lacking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi is cut in blocks bigger than my cell phone ."], "output": "[['sushi', 'bigger', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is great , my soup always arrives nice and hot ."], "output": "[['service', 'great', 'positive'], ['soup', 'great', 'positive'], ['soup', 'hot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It had been awhile and I forgot just how delicious crepes can be ."], "output": "[['crepes', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Montparnasse 's desserts -- especially the silken creme brulee and paper -- thin apple tart -- are good enough on their own to make the restaurant worth the trip ."], "output": "[['desserts', 'good', 'positive'], ['creme brulee', 'silken', 'positive'], ['apple tart', 'thin', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i had a delicious shrimp creole ."], "output": "[['shrimp creole', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chicken dinner was real good ."], "output": "[['chicken dinner', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["but the food was delicious ."], "output": "[['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the ribs , sizzling beef and couple it with coconut rice ."], "output": "[['ribs', 'Try', 'positive'], ['beef', 'Try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The avocado salad is a personal fave ."], "output": "[['avocado salad', 'fave', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And , the honey BBQ rib tips are yummy !"], "output": "[['honey BBQ rib tips', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The BEST Chinese food Uptown !"], "output": "[['Chinese food', 'BEST', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service is known for bending over backwards to make everyone happy ."], "output": "[['Service', 'happy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is very friendly ."], "output": "[['staff', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Waiters are very friendly and the pasta is out of this world ."], "output": "[['Waiters', 'friendly', 'positive'], ['pasta', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great wine list and great cocktail menu ."], "output": "[['wine list', 'Great', 'positive'], ['cocktail menu', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The crab cakes are delicious and the BBQ rib was perfect ."], "output": "[['crab cakes', 'delicious', 'positive'], ['BBQ rib', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is wonderful , artfully done and simply delicious ."], "output": "[['food', 'wonderful', 'positive'], ['food', 'artfully', 'positive'], ['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Tiny restaurant with very fast service ."], "output": "[['service', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My husband and I have been there at least 6 times and we 've always been given the highest service and often free desserts ."], "output": "[['service', 'highest', 'positive'], ['desserts', 'free', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A beautiful atmosphere , perfect for drinks and/or appetizers ."], "output": "[['atmosphere', 'beautiful', 'positive'], ['drinks', 'perfect', 'neutral'], ['appetizers', 'perfect', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They make the best pizza in New Jersey ."], "output": "[['pizza', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["What a difference , the service was very comforting and the food was better than average , but what really standed out was such a dynamic and extensive beer list ."], "output": "[['service', 'comforting', 'positive'], ['food', 'better than average', 'positive'], ['beer list', 'extensive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not to be overlooked , the service is excellent ."], "output": "[['service', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["this without question is one of the worst hotdogs i have ever had ."], "output": "[['hotdogs', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is unbelievably friendly , and I dream about their Saag gosht ... so good ."], "output": "[['staff', 'friendly', 'positive'], ['Saag gosht', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I also recommend the garlic knots ."], "output": "[['garlic knots', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Indian food I have ever eaten ."], "output": "[['Indian food', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has the best pizza ."], "output": "[['pizza', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The music which is sometimes a little too heavy for my taste ."], "output": "[['music', 'too heavy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is excellent and always informative without an air ."], "output": "[['service', 'excellent', 'positive'], ['service', 'informative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi is always fresh and yummy and the menu is pretty varied ."], "output": "[['sushi', 'fresh', 'positive'], ['sushi', 'yummy', 'positive'], ['menu', 'varied', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was great - sushi was good , but the cooked food amazed us ."], "output": "[['food', 'great', 'positive'], ['sushi', 'good', 'positive'], ['cooked food', 'amazed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["their dinner specials are fantastic ."], "output": "[['dinner specials', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , great drinks , nice dining atmosphere ."], "output": "[['food', 'Great', 'positive'], ['drinks', 'great', 'positive'], ['dining atmosphere', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food portion was SMALL and below average ."], "output": "[['Food portion', 'SMALL', 'negative'], ['Food portion', 'below average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sit back in one of those comfortable chairs ."], "output": "[['chairs', 'comfortable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My favs here are the Tacos Pastor and the Tostada de Tinga ..."], "output": "[['Tacos Pastor', 'favs', 'positive'], ['Tostada de Tinga', 'favs', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bartenders and the managers are really nice and the decor is very comfy and laid-back , all the while being trendy ."], "output": "[['bartenders', 'nice', 'positive'], ['managers', 'nice', 'positive'], ['decor', 'comfy', 'positive'], ['decor', 'laid-back', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For a savory take on the soup and sandwich meal , try the hot and sour soup ."], "output": "[['hot and sour soup', 'try', 'positive'], ['soup and sandwich meal', 'savory', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This bar has it all - great drinks , cool atmosphere , excellent service and delicious food ."], "output": "[['drinks', 'great', 'positive'], ['atmosphere', 'cool', 'positive'], ['service', 'excellent', 'positive'], ['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also , the chick peas with shrimp ( appetizer ) is divine ."], "output": "[['chick peas with shrimp ( appetizer )', 'divine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Finally , I got sick of the bad service , obnoxious smirks , and snotty back talk ."], "output": "[['service', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We ordered lamb which was perfectly cooked and tasted awesome ."], "output": "[['lamb', 'perfectly cooked', 'positive'], ['lamb', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i especially like their soft shell crab sandwich with fries ."], "output": "[['soft shell crab sandwich with fries', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["if you 're looking for authentic hong kong-style food , look no further ."], "output": "[['hong kong-style food', 'authentic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["good food good wine that 's it ."], "output": "[['food', 'good', 'positive'], ['wine', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff was extremely friendly and pleasant ."], "output": "[['staff', 'friendly', 'positive'], ['staff', 'pleasant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While their kitchen food is delicious , their Sushi is out of this world ."], "output": "[['kitchen food', 'delicious', 'positive'], ['Sushi', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["everything is scrumptious , from the excellent service by cute waitresses , to the extremely lush atmosphere ."], "output": "[['service', 'excellent', 'positive'], ['waitresses', 'cute', 'positive'], ['atmosphere', 'lush', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's traditional , simple italian food ."], "output": "[['italian food', 'traditional', 'positive'], ['italian food', 'simple', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is all-around good , with the rolls usually excellent and the sushi/sashimi not quite on the same level ."], "output": "[['food', 'good', 'positive'], ['rolls', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["( The sashimi is cut a little thinly ."], "output": "[['sashimi', 'thinly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In addition to great hot dogs , DOTP has wonderful breakfast sandwiches that feature , in addition to great things like tator tots and English muffins , a delicious NJ-based pork product know to us Jersey girls and boys as Taylor ham ."], "output": "[['hot dogs', 'great', 'positive'], ['breakfast sandwiches', 'wonderful', 'positive'], ['tator tots', 'great', 'positive'], ['English muffins', 'great', 'positive'], ['pork product', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Well , it happened because of a graceless manager and a rude bartender who had us waiting 20 minutes for drinks , and then tells us to chill out ."], "output": "[['manager', 'graceless', 'negative'], ['bartender', 'rude', 'negative'], ['drinks', 'waiting', 'neutral'], ['waiting', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only is the service great , but forming conversation around a table is so easy beacuse the atmosphere can be both romantic and comfortable ."], "output": "[['service', 'great', 'positive'], ['atmosphere', 'romantic', 'positive'], ['atmosphere', 'comfortable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["When the dish arrived it was blazing with green chillis , definitely not edible by a human ."], "output": "[['green chillis', 'not edible', 'negative'], ['dish', 'edible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The absolute worst service I 've ever experienced and the food was below average ( when they actually gave people the meals they ordered ) ."], "output": "[['service', 'worst', 'negative'], ['food', 'below average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Be sure to accompany your food with one of their fresh juice concoctions ."], "output": "[['fresh juice concoctions', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great and the prices are reasonable ."], "output": "[['food', 'great', 'positive'], ['prices', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place is clean , and if you like soul food , then this is the place to be !"], "output": "[['place', 'clean', 'positive'], ['soul food', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have a very good chicken with avocado and good tuna as well ."], "output": "[['chicken with avocado', 'good', 'positive'], ['tuna', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the meals were terrible ."], "output": "[['meals', 'terrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My chicken was completely dried out and on the cold side and the sauce was not very flavorful ."], "output": "[['chicken', 'dried out', 'negative'], ['sauce', 'not very flavorful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Malted Milk Ball Gelato - have you ever in your life heard of anything so ridiculously wonderful ?"], "output": "[['Malted Milk Ball Gelato', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Way too much money for such a terrible meal ."], "output": "[['meal', 'terrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , the service is absolutely horrible ."], "output": "[['service', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A con was the slow bar service ."], "output": "[['bar service', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Dessert was also to die for !"], "output": "[['Dessert', 'die for', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["BTW , the service is very good ."], "output": "[['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The unattractive lighting made me want to gag , the food was overpriced , there was the most awful disco pop duo performing-and my escargot looked like it might crawl off the plate ."], "output": "[['lighting', 'unattractive', 'negative'], ['food', 'overpriced', 'negative'], ['disco pop duo', 'awful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it is a cozy place to go with a couple of friends ."], "output": "[['place', 'cozy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is always great , and the owner walks around to make sure you enjoy ."], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the food is delicious and highly recommended ."], "output": "[['food', 'delicious', 'positive'], ['food', 'recommended', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["So for a filling and healthy meal give it a go ."], "output": "[['meal', 'filling', 'positive'], ['meal', 'healthy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Since I cook for a living , I 'm very fussy about the food I eat in restaurants ."], "output": "[['food', 'fussy', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was outstanding ."], "output": "[['service', 'outstanding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We always enjoy the pizza ."], "output": "[['pizza', 'enjoy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is pretty good ."], "output": "[['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yum , the chicken is great here ."], "output": "[['chicken', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food here was great , a treat from beginning to end ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The host ( owner ) and servers are personable and caring ."], "output": "[['host ( owner )', 'personable', 'positive'], ['host ( owner )', 'caring', 'positive'], ['servers', 'personable', 'positive'], ['servers', 'caring', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's just everything ... the food , the atmosphere ... the incrediby kind and gracious hostess ."], "output": "[['hostess', 'kind', 'positive'], ['hostess', 'gracious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is very good and the service is great ."], "output": "[['food', 'good', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We were wondering why they were there to make our dining experience miserable ?"], "output": "[['dining experience', 'miserable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has the best Indian food in New York , hands down ."], "output": "[['Indian food', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiters are very friendly and helpful and if you frequent they will remember you ."], "output": "[['waiters', 'friendly', 'positive'], ['waiters', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Intimate but charming interior with extremely friendly and attentive service ."], "output": "[['interior', 'charming', 'positive'], ['service', 'friendly', 'positive'], ['service', 'attentive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was as creative as the decor and both worked ."], "output": "[['food', 'creative', 'positive'], ['decor', 'creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu is great , with a good selection , and everything that I have tried is absolutely delicious ."], "output": "[['menu', 'great', 'positive'], ['selection', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sauce is zesty and flavorful and the crust is nice and crispy ."], "output": "[['sauce', 'zesty', 'positive'], ['sauce', 'flavorful', 'positive'], ['crust', 'nice', 'positive'], ['crust', 'crispy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has the best sushi in the city ."], "output": "[['sushi', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have an excellent selection ( the rolls with crab are really great ) ."], "output": "[['selection', 'excellent', 'positive'], ['rolls with crab', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everyone who works there ( the host , the bartender , the servers ) is so helpful ."], "output": "[['host', 'helpful', 'positive'], ['bartender', 'helpful', 'positive'], ['servers', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And the food is fantastic ."], "output": "[['food', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Favourites include : potato spinach gnocchi and the lamb ."], "output": "[['potato spinach gnocchi', 'Favourites', 'positive'], ['lamb', 'Favourites', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But regulars know that the sandwiches are the real star here ."], "output": "[['sandwiches', 'star', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The skillfully chosen Portuguese cheese cart paired with quality port provides the perfect Iberian ending ."], "output": "[['port', 'quality', 'positive'], ['Portuguese cheese cart', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My friend had a burger and I had these wonderful blueberry pancakes ."], "output": "[['blueberry pancakes', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We were so happy with our food and were even more thrilled when we saw the bill ."], "output": "[['food', 'happy', 'positive'], ['bill', 'thrilled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All toppings are so fresh you 'd think they had their own vegetable garden and the crust is so perfect , that one actually thinks of how it was made ."], "output": "[['toppings', 'fresh', 'positive'], ['crust', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We 've always gotten amazing service and we love the food ."], "output": "[['service', 'amazing', 'positive'], ['food', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waitstaff is solicitous and friendly and always seems glad to see us , and the food is wonderful , if not stunningly creative ."], "output": "[['waitstaff', 'solicitous', 'positive'], ['waitstaff', 'friendly', 'positive'], ['food', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 'm in love with the lobster ravioli !"], "output": "[['lobster ravioli', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We came across this restaurant by accident while at a DUMBO art festival and thoroughly enjoyed our meal ."], "output": "[['meal', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service is excellent , no wait , and you get a lot for the price ."], "output": "[['Service', 'excellent', 'positive'], ['wait', 'no', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I thought the food is n't cheap at all compared to Chinatown ."], "output": "[['food', \"is n't cheap\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Coffee is a better deal than overpriced Cosi sandwiches ."], "output": "[['Coffee', 'better', 'positive'], ['Cosi sandwiches', 'overpriced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": [") It 's not the best Japanese restaurant in the East Village , but it 's a pretty solid one for its modest prices , and worth repeat visits ."], "output": "[['prices', 'modest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is so good and so popular that waiting can really be a nightmare ."], "output": "[['food', 'good', 'positive'], ['food', 'popular', 'positive'], ['waiting', 'nightmare', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["First walking in the place seemed to have great ambience ."], "output": "[['ambience', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Even for two very hungry people there is plenty of food left to be taken home ( it reheats really well also ) ."], "output": "[['food', 'plenty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Then they somehow made a dry and burnt crust , around a raw and cold inside ."], "output": "[['crust', 'dry', 'negative'], ['crust', 'burnt', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's just good food , nothing more and that 's all we want !"], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Average cake thats been courted by a LOT of hype ."], "output": "[['cake', 'Average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My wife and I recently visited the bistro for dinner and had a wonderful experience ."], "output": "[['dinner', 'wonderful', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE SERVICE IS PERFECT TOO NOTHING WRONG IN THIS ITALIAN/FRENCH RESTAURANT"], "output": "[['SERVICE', 'PERFECT', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The $ 72 Delmonico steak had to be sent back because it was not cooked to order ."], "output": "[['Delmonico steak', 'not cooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is really fast and friendly , and the value is great ."], "output": "[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['value', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We were very impressed with the food and value ."], "output": "[['food', 'impressed', 'positive'], ['value', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You must try the garlic soup !"], "output": "[['garlic soup', 'try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Casablanca servces delicious falafel , tabouleh , humus and other Mediterranean delights , which are all very inexpensive ."], "output": "[['falafel', 'delicious', 'positive'], ['tabouleh', 'delicious', 'positive'], ['humus', 'delicious', 'positive'], ['Mediterranean delights', 'delicious', 'positive'], ['Mediterranean delights', 'inexpensive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pizza 's are made fresh , crispy , and ready to serve ."], "output": "[[\"pizza 's\", 'fresh', 'positive'], [\"pizza 's\", 'crispy', 'positive'], [\"pizza 's\", 'ready to serve', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Staff is accomodating make sure you are satified ."], "output": "[['Staff', 'accomodating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Reasonably priced with very fresh sushi ."], "output": "[['sushi', 'fresh', 'positive'], ['priced', 'Reasonably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All of the apetizers are good and the Sangria is very good ."], "output": "[['apetizers', 'good', 'positive'], ['Sangria', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The one positive thing I can say is that the service was prompt , we got seated right away and the server was very friendly ."], "output": "[['service', 'prompt', 'positive'], ['server', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff greeted me warmly at the door and I was seated promptly and the food was excellent ."], "output": "[['staff', 'warmly', 'positive'], ['food', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service is usually pretty good ."], "output": "[['Service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Host and Hostess was quite rude ."], "output": "[['Host', 'rude', 'negative'], ['Hostess', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the wait staff is very friendly , if your not rude or picky ... ... .our meal at Leon last weekend was great - ."], "output": "[['wait staff', 'friendly', 'positive'], ['meal', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I recommend any of their salmon dishes ... ..."], "output": "[['salmon dishes', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The foie gras was sweet and luscious ."], "output": "[['foie gras', 'sweet', 'positive'], ['foie gras', 'luscious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu , which changes seasonally , shows both regional and international influences ."], "output": "[['menu', 'changes', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["but their mac cheese was YUMMY !"], "output": "[['mac cheese', 'YUMMY', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["jazz singer had a nice voice + she made us all get up to dance to shake some cals to eat some more ."], "output": "[['jazz singer', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have very quick service which is great when you do n't have much time ."], "output": "[['service', 'quick', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is average : breakfast food , soups , salads , sandwiches , etc ."], "output": "[['food', 'average', 'neutral'], ['breakfast food', 'average', 'neutral'], ['soups', 'average', 'neutral'], ['salads', 'average', 'neutral'], ['sandwiches', 'average', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I WAS HIGHLY DISAPPOINTED BY THE FOOD ."], "output": "[['FOOD', 'DISAPPOINTED', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE BANANA PUDDING THEY SERVE HAS NEVER SEEN AN OVEN , THE CRABCAKES ARE WAY OVER SALTED AND DO N'T GET ME STARTED ON THE VERY GREASY MAC AND CHEESE ."], "output": "[['CRABCAKES', 'OVER SALTED', 'negative'], ['MAC AND CHEESE', 'GREASY', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is arrogant , the prices are way high for Brooklyn ."], "output": "[['staff', 'arrogant', 'negative'], ['prices', 'high', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the service is prompt friendly ."], "output": "[['service', 'prompt friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is literally a hot spot when it comes to the food ."], "output": "[['food', 'hot spot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The downstairs bar scene is very cool and chill ..."], "output": "[['downstairs bar scene', 'cool', 'positive'], ['downstairs bar scene', 'chill', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was definitely good , but when all was said and done , I just could n't justify it for the price ( including 2 drinks , $ 100/person ) ..."], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you are a Tequila fan you will not be disappointed ."], "output": "[['Tequila', 'not be disappointed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great beer selection too , something like 50 beers ."], "output": "[['beer selection', 'Great', 'positive'], ['beers', 'Great', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not to sound too negative but be wary of the delivary ."], "output": "[['delivary', 'wary', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I found the food to be just as good as its owner , Da Silvano , just much less expensive ."], "output": "[['food', 'good', 'positive'], ['food', 'much less expensive', 'positive'], ['owner', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have homemade pastas of all kinds -- I recommend the gnocchi -- yum !"], "output": "[['gnocchi', 'recommend', 'positive'], ['gnocchi', 'yum', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My vegetable risotto was burnt , and infused totally in a burnt flavor ."], "output": "[['vegetable risotto', 'burnt', 'negative'], ['flavor', 'burnt', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The main draw of this place is the price ."], "output": "[['price', 'draw', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But dinner here is never disappointing , even if the prices are a bit over the top ."], "output": "[['dinner', 'never disappointing', 'positive'], ['prices', 'over the top', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only did they have amazing , sandwiches , soup , pizza etc , but their homemade sorbets are out of this world !"], "output": "[['sandwiches', 'amazing', 'positive'], ['soup', 'amazing', 'positive'], ['pizza', 'amazing', 'positive'], ['homemade sorbets', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the homemade Guacamole , the unbelievable entree , and thee most amazing deserts ."], "output": "[['homemade Guacamole', 'unbelievable', 'positive'], ['homemade Guacamole', 'amazing', 'positive'], ['entree', 'unbelievable', 'positive'], ['deserts', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi is reasonably priced and fresh ."], "output": "[['sushi', 'reasonably priced', 'positive'], ['sushi', 'fresh', 'positive'], ['priced', 'reasonably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Save room for deserts - they 're to die for ."], "output": "[['deserts', 'die for', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The traditional Italian items are great - cheap and served in a cozy setting ."], "output": "[['traditional Italian items', 'great', 'positive'], ['traditional Italian items', 'cheap', 'positive'], ['setting', 'cozy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was a bit slow and the portions are a bit small so if you are hungry and in a rush , this is not the place for you ."], "output": "[['service', 'slow', 'negative'], ['portions', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["El Nidos one of the best restaurants in New York which I 've ever been to , has a great variety of tasty , mouth watering pizza 's ."], "output": "[[\"pizza 's\", 'great', 'positive'], [\"pizza 's\", 'tasty', 'positive'], [\"pizza 's\", 'mouth watering', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was pretty poor all around , the food was well below average relative to the cost , and outside there is a crazy bum who harasses every customer who leaves the place ."], "output": "[['service', 'poor', 'negative'], ['food', 'below average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Although I moved uptown I try to stop in as often as possible for the GREAT cheap food and to pay the friendly staff a visit ."], "output": "[['food', 'GREAT cheap', 'positive'], ['staff', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Chef Vincenzo , always there if you need him , is a real talent and a real Roman ."], "output": "[['Chef', 'talent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you 're looking to taste some great Indian food and want good service , definitely visit Curry Leaf ."], "output": "[['Indian food', 'great', 'positive'], ['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You must try Odessa stew or Rabbit stew ; salads -all good ; and kompot is soo refreshing during the hot summer day ( they make it the way my mom does , reminds me of home a lot ) ."], "output": "[['Odessa stew', 'good', 'positive'], ['Rabbit stew', 'good', 'positive'], ['salads', 'good', 'positive'], ['kompot', 'refreshing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My daughter and I left feeling satisfied ( not stuffed ) and it felt good to know we had a healthy lunch ."], "output": "[['lunch', 'healthy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The quality of the meat was on par with your local grocery store ."], "output": "[['quality of the meat', 'on par', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I recommend the black roasted codfish , it was the best dish of the evening ."], "output": "[['black roasted codfish', 'recommend', 'positive'], ['black roasted codfish', 'best', 'positive'], ['dish', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The manager then told us we could order from whatever menu we wanted but by that time we were so annoyed with the waiter and the resturant that we let and went some place else ."], "output": "[['waiter', 'annoyed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In mi burrito , here was nothing but dark chicken that had that cooked last week and just warmed up in a microwave taste ."], "output": "[['taste', 'microwave', 'negative'], ['chicken', 'dark', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["during busy hrs , i recommend that you make a reservation ."], "output": "[['reservation', 'recommend', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I went to Common Stock for brunch and I was so impressed ."], "output": "[['brunch', 'impressed', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["now called nikki sushi , sushi is OK ."], "output": "[['sushi', 'OK', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is also outstanding and is served quite quickly ."], "output": "[['food', 'outstanding', 'positive'], ['served', 'quickly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is delicious and the bar has a great vibe ."], "output": "[['food', 'delicious', 'positive'], ['bar', 'great', 'positive'], ['vibe', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Simple healthy unglamorous food cheap ."], "output": "[['food', 'Simple healthy unglamorous', 'positive'], ['food', 'cheap', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was such a fantastic dining experience , that I returned again the same week ."], "output": "[['dining experience', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["To be fair , the food still is good and the service is quick and attentative even though its usually very busy ."], "output": "[['food', 'good', 'positive'], ['service', 'quick', 'positive'], ['service', 'attentative', 'positive'], ['service', 'busy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place is absolutely adorable and the food is delicious ."], "output": "[['place', 'adorable', 'positive'], ['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had better Japanese food at a mall food court ."], "output": "[['Japanese food', 'better', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff members are extremely friendly and even replaced my drink once when I dropped it outside ."], "output": "[['staff members', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cool atmosphere but such a let down ."], "output": "[['atmosphere', 'Cool', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Sashimi portion are big enough to appease most people , but I did n't like the fact they used artifical lobster meat ."], "output": "[['Sashimi portion', 'big', 'positive'], ['artifical lobster meat', \"did n't like\", 'negative'], ['artifical lobster meat', 'artifical', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have wheat crusted pizza made with really fresh and yummy ingredients ."], "output": "[['ingredients', 'fresh', 'positive'], ['ingredients', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had a lovely dinner in this dedicated seafood joint , food was well-prepared and -presented and the service was pleasant and prompt ."], "output": "[['dinner', 'lovely', 'positive'], ['food', 'well-prepared and -presented', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'prompt', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the icing MADE this cake , it was fluffy , not ultra sweet , creamy and light ."], "output": "[['cake', 'fluffy', 'positive'], ['cake', 'not ultra sweet', 'positive'], ['cake', 'creamy', 'positive'], ['cake', 'light', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Finally let into the store 5 at a time , to buy expensive slices from a harried staff ."], "output": "[['staff', 'harried', 'negative'], ['slices', 'expensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We ended up having to just leave because we were essentially being ignored by the wait staff -- even though the rest of the restaurant was largely empty ."], "output": "[['wait staff', 'ignored', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine list is extensive , well priced and covers alot of regions ."], "output": "[['wine list', 'extensive', 'positive'], ['priced', 'well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Go here if you want fresh and tasty salads of any type you can imagine ."], "output": "[['salads', 'fresh', 'positive'], ['salads', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything about this place is adorable - even the bathroom !"], "output": "[['bathroom', 'adorable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Speedy delivers , great food , decent prices , and friendly service combine to ensure an enjoyable repast ."], "output": "[['delivers', 'Speedy', 'positive'], ['food', 'great', 'positive'], ['prices', 'decent', 'positive'], ['service', 'friendly', 'positive'], ['repast', 'enjoyable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["IT WAS OUR ONLY OPPORTUNITY TO VISIT AND WANTED AN AUTHENTIC ITALIAN MEAL ."], "output": "[['ITALIAN MEAL', 'AUTHENTIC', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It took 100 years for Parisi to get around to making pizza ( at least I do n't think they ever made it before this year ) ... but it was worth the wait ."], "output": "[['pizza', 'worth the wait', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I asked for a simple medium rare steak ."], "output": "[['steak', 'simple medium rare', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Generously garnished , organic grilled burgers are the most popular dish , but the Jerusalem market-style falafel wraps and Mediterranean salads -- layered with beets , goat cheese and walnuts -- are equally scrumptious ."], "output": "[['organic grilled burgers', 'Generously garnished', 'positive'], ['organic grilled burgers', 'popular', 'positive'], ['dish', 'popular', 'positive'], ['Jerusalem market-style falafel wraps', 'equally scrumptious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Probably my worst dining experience in new york , and I 'm a former waiter so I know what I 'm talking about ."], "output": "[['dining experience', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Result ( red velvet ) : Great texture , soft and velvety , nice hint of cocoa ."], "output": "[['texture', 'Great', 'positive'], ['texture', 'soft', 'positive'], ['texture', 'velvety', 'positive'], ['hint of cocoa', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Their twist on pizza is healthy , but full of flavor ."], "output": "[['flavor', 'full', 'positive'], ['twist on pizza', 'healthy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lack of AC and the fact that there are a million swarming bodies ( although everyone is polite and no one is pushing ) is a slight turn off ."], "output": "[['AC', 'lack', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the Little Pie Company as much as anyone else who has written reviews , but must discourage anyone from visiting the Grand Central location due to their RUDE service from two sales people ."], "output": "[['service', 'RUDE', 'negative'], ['sales people', 'RUDE', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Unfortunately , unless you live in the neighborhood , it 's not in a convenient location but is more like a hidden treasure ."], "output": "[['location', 'convenient', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food -- though mostly deep-fried -- is simple and satisfying ."], "output": "[['food', 'simple', 'positive'], ['food', 'satisfying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Glechik might be way too tiny for a restaurant by Russian standards , but it is cozy and the food is simply GREAT ."], "output": "[['food', 'GREAT', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was excellent - authentic Italian cuisine made absolutely fresh ."], "output": "[['food', 'excellent', 'positive'], ['Italian cuisine', 'authentic', 'positive'], ['Italian cuisine', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["At night the atmoshere changes turning into this hidden jewel that is waiting to be discovered ."], "output": "[['atmoshere', 'changes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The other times I 've gone it 's romantic date heaven , you can walk in get a booth by the windows , be treated like a VIP in a not-crowded place , with great food and service ."], "output": "[['place', 'not-crowded', 'positive'], ['food', 'great', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I would only go for the coffee which is way better than Starbucks or the like ."], "output": "[['coffee', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Somewhat disappointing wine list ( only new vintages ."], "output": "[['wine list', 'disappointing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If your looking for nasty high priced food with a dash of ghetto scenery cheap BX A $ $ this is the place to be ! !"], "output": "[['priced', 'high', 'negative'], ['food', 'nasty high priced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["new hamburger with special sauce is ok - at least better than big mac !"], "output": "[['new hamburger with special sauce', 'ok', 'positive'], ['big mac', 'better than', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Perfectly al dente pasta , not drowned in sauce -- generous portions ."], "output": "[['pasta', 'Perfectly', 'positive'], ['sauce', 'not drowned in', 'neutral'], ['portions', 'generous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was awful - mostly because staff were overwhelmed on a Saturday night ."], "output": "[['Service', 'awful', 'negative'], ['staff', 'overwhelmed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["To the owners ; good job guys , this place is a keeper !"], "output": "[['owners', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["and the owner is simply lovely and friendly ."], "output": "[['owner', 'lovely', 'positive'], ['owner', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This little place is wonderfully warm welcoming ."], "output": "[['place', 'wonderfully warm welcoming', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["perfect for a quick meal ."], "output": "[['meal', 'perfect', 'positive'], ['meal', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Has the warmth of a family local yet it is a great place to watch sporting events ."], "output": "[['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was great , and they have a whole great deal for birthdays ."], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is 100 % Italian and the food is as authentic as it gets ."], "output": "[['food', 'authentic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My only complaint might be the fortune cookies - I 've never had a cookie predict bad luck for me before I visited Kar ."], "output": "[['fortune cookies', 'complaint', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good for a quick sushi lunch ."], "output": "[['sushi lunch', 'Good', 'positive'], ['sushi lunch', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was dreadfully slow ( the place was only half full ) and a smile would have been nice ..."], "output": "[['service', 'dreadfully slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I went this past Saturday and had a excellent meal of consisting of a braised lamb shank with mashed potatoes ."], "output": "[['meal', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I reccomend the fried pork dumplings , the orange chicken/beef , and the fried rice ."], "output": "[['fried pork dumplings', 'reccomend', 'positive'], ['orange chicken/beef', 'reccomend', 'positive'], ['fried rice', 'reccomend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You will not be dissapointed by any of the choices in the menu ."], "output": "[['menu', 'not be dissapointed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The french fries -- with the kalmata dip were terrific !"], "output": "[['french fries -- with the kalmata dip', 'terrific', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The boutique selection of wines covers a wide variety without being imposeing ."], "output": "[['boutique selection of wines', 'wide', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They also have a great assortment of wraps if your not in the mood for traditional Mediterranean fare ."], "output": "[['assortment of wraps', 'great', 'positive'], ['traditional Mediterranean fare', 'great', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fresh veggies , all sorts of middle eastern spreads , cheese and falafel , soup , fish , rice , root vegetables , a rice medley , some spinach thing , lamb kebabs , cheese baclava ... soooo much fooood , and all of it delicious ."], "output": "[['Fresh veggies', 'Fresh', 'positive'], ['Fresh veggies', 'delicious', 'positive'], ['middle eastern spreads', 'delicious', 'positive'], ['cheese', 'delicious', 'positive'], ['falafel', 'delicious', 'positive'], ['soup', 'delicious', 'positive'], ['fish', 'delicious', 'positive'], ['rice', 'delicious', 'positive'], ['root vegetables', 'delicious', 'positive'], ['rice medley', 'delicious', 'positive'], ['spinach thing', 'delicious', 'positive'], ['lamb kebabs', 'delicious', 'positive'], ['cheese baclava', 'delicious', 'positive'], ['fooood', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Disappointingly , their wonderful Saketini has been taken off the bar menu ."], "output": "[['Saketini', 'wonderful', 'positive'], ['bar menu', 'Disappointingly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I would definitely go back -- if only for some of those exotic martinis on the blackboard ."], "output": "[['martinis', 'exotic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The happy hour is so cheap , but that does not reflect the service or the atmosphere ."], "output": "[['happy hour', 'cheap', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["After waiting for almost an hour , the waiter brusquely told us he 'd forgotten to give the kitchen our order ."], "output": "[['waiter', 'brusquely', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["With all the mundane or mediocre places on 8th avenue it is nice to have one that is a step above in quaility and atmosphere ."], "output": "[['quaility', 'above', 'positive'], ['atmosphere', 'above', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A mix of students and area residents crowd into this narrow , barely there space for its quick , tasty treats at dirt-cheap prices ."], "output": "[['space', 'quick', 'negative'], ['space', 'tasty', 'negative'], ['prices', 'dirt-cheap', 'positive'], ['treats', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Give it a try , menu is typical French but varied ."], "output": "[['menu', 'typical French', 'neutral'], ['menu', 'varied', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It gets crowded at lunchtime but there are lots of seats in back and everyone who works there is so nice ."], "output": "[['seats', 'lots', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the negative reviews on city search are probably from jealous competing restaurants who realize they ca n't compete with Temple 's entire positive attitude about the proper way to treat their customers and deliver top quality food ."], "output": "[['food', 'top quality', 'positive'], ['attitude', 'positive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Overall , this is a nice place to take a few friends to hang out at and the service is excellent ."], "output": "[['place', 'nice', 'positive'], ['service', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food is excellent quality for a good restaurant price ."], "output": "[['Food', 'excellent', 'positive'], ['price', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["for about eleven bucks you get a gigantic burrito ( or tacos ) , margarita , and dessert ."], "output": "[['burrito', 'gigantic', 'positive'], ['tacos', 'gigantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The space is traditional in feel ."], "output": "[['space', 'traditional', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the food was mediocre to be kind - the interior is small and average - the owners are a tag-team of unpleasantries - so rude and snotty i actually let out a hearty guffaw whilst dining ."], "output": "[['food', 'mediocre', 'negative'], ['interior', 'small', 'negative'], ['interior', 'average', 'negative'], ['owners', 'unpleasantries', 'negative'], ['owners', 'rude', 'negative'], ['owners', 'snotty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good service , great food , good value , and never have to wait in line !"], "output": "[['service', 'Good', 'positive'], ['food', 'great', 'positive'], ['value', 'good', 'positive'], ['wait', 'never', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Offerings like hot cakes and the Egg McMuffin sandwich are available for breakfast ."], "output": "[['Egg McMuffin sandwich', 'available', 'neutral'], ['hot cakes', 'available', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have been going to this restaurant for years , in the past the service was average and the food inconsistant ."], "output": "[['service', 'average', 'neutral'], ['food', 'inconsistant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The music was fascinating , but left room for conversation , and the bartender made superb drinks ."], "output": "[['music', 'fascinating', 'positive'], ['bartender', 'superb', 'positive'], ['drinks', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["rice dishes and noodle dishes rarely exceed $ 5 and add on a refreshing ice drink for $ 2 and you 're set for the night !"], "output": "[['ice drink', 'refreshing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Creative dishes like king crab salad with passion fruit vinaigrette and fettuccine with grilled seafood in a rosemary-orange sauce are unexpected elements on an otherwise predictable bistro menu ."], "output": "[['dishes', 'Creative', 'positive'], ['king crab salad with passion fruit vinaigrette', 'Creative', 'positive'], ['fettuccine with grilled seafood in a rosemary-orange sauce', 'unexpected', 'positive'], ['bistro menu', 'unexpected', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Dishes denoted as `` Roy 's Classics '' ( marked on the menu with asterisks ) are tried-and-true recipes , such as macadamia-crusted mahi mahi , or subtly sweet honey-mustard beef short ribs ."], "output": "[['Dishes', 'tried-and-true', 'positive'], ['recipes', 'tried-and-true', 'positive'], ['macadamia-crusted mahi mahi', 'tried-and-true', 'positive'], ['sweet honey-mustard beef short ribs', 'tried-and-true', 'positive'], ['sweet honey-mustard beef short ribs', 'sweet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The cold sesame noodles , which are a freebie when you order $ 10+ , are delectable ."], "output": "[['cold sesame noodles', 'delectable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I came to fresh expecting a great meal , and all I got was marginally so-so food served in a restaurant that was just so freezing we could n't enjoy eating ."], "output": "[['food', 'marginally so-so', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lone argentine chorizo appetizer at $ 8.95 was a heavy fennel flavored Italian sausage like the ones that sell for $ 2.99/lb at the store ."], "output": "[['fennel flavored Italian sausage', 'heavy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I went to Swiftys with some friends of the family and we had a very nice dinner , but nothing amazing ."], "output": "[['dinner', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Chinese on the Upper East , prompt delivery , good value ."], "output": "[['delivery', 'prompt', 'positive'], ['value', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Most of the sandwiches are made with soy mayonaise which is actually pretty good ."], "output": "[['sandwiches', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i went in one day asking for a table for a group and was greeted by a very rude hostess ."], "output": "[['hostess', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's worthwhile to take a cab to Chelsea just for an awesome dinner at My Chelsea ."], "output": "[['dinner', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only is the food authentic , but the staff here are practically off-the-boat , they are young and hip and know what they are doing when it comes to food and wine ."], "output": "[['food', 'authentic', 'positive'], ['staff', 'off-the-boat', 'positive'], ['staff', 'young', 'positive'], ['staff', 'hip', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has good music , nice tapas , an interesting selection of wines ( primarily Spanish ) and a lowkey hip neighborhood clientele ."], "output": "[['music', 'good', 'positive'], ['tapas', 'nice', 'positive'], ['selection of wines ( primarily Spanish )', 'interesting', 'positive'], ['clientele', 'lowkey hip', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great , I love their dumplings , cold sesame noodles , chicken and shrimp dishs ."], "output": "[['food', 'great', 'positive'], ['dumplings', 'love', 'positive'], ['cold sesame noodles', 'love', 'positive'], ['chicken', 'love', 'positive'], ['shrimp dishs', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's the conversations that make this a fun place to be ."], "output": "[['place', 'fun', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My gf 's duck confitte was very solid as well , although i have little base of reference ."], "output": "[['duck confitte', 'solid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine list was superb , our tapas delightful , and the quiet atmosphere perfect for good conversation ."], "output": "[['wine list', 'superb', 'positive'], ['tapas', 'delightful', 'positive'], ['atmosphere', 'quiet', 'positive'], ['atmosphere', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You can eat gourmet food at a fast food price ."], "output": "[['food', 'gourmet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've eaten at all three locations and I always love , love the food , the service is always wonderful and the prices are really reasonable ."], "output": "[['food', 'love', 'positive'], ['service', 'wonderful', 'positive'], ['prices', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not because I was pregnant , but the food here is always delicious ."], "output": "[['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had a great meal there this weekend before heading to the movies !"], "output": "[['meal', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We had a birthday party here recently and the food and service was amazing ."], "output": "[['food', 'amazing', 'positive'], ['service', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the dinner menu offers a variety of great entrees , including fresh seafood and huge steaks , there 's also a couple of non-meat alternatives ."], "output": "[['dinner menu', 'variety', 'positive'], ['dinner menu', 'great', 'positive'], ['entrees', 'great', 'positive'], ['seafood', 'fresh', 'positive'], ['steaks', 'huge', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has the strangest menu and the restaurants tries too hard to make fancy food ."], "output": "[['menu', 'strangest', 'negative'], ['food', 'fancy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The appetizers are ok , but the service is slow ."], "output": "[['appetizers', 'ok', 'neutral'], ['service', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the food - not worth the price ."], "output": "[['food', 'not worth', 'negative'], ['price', 'not worth', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["What can you say about a place where the waitress brings out the wrong entree , then verbally assaults your 80 year old grandmother and gives her lip about sending it back ( which she did politely , by the way ) ."], "output": "[['entree', 'wrong', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The prices are not terrible ."], "output": "[['prices', 'not terrible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The halibut cheek appetizer came with a generous portion of foie gras , but that 's about the only positive thing I can say about the meal ."], "output": "[['halibut cheek appetizer', 'positive', 'neutral'], ['portion of foie gras', 'generous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food is excellent and they also have empenadas and plaintains which are good for an afternoon snack ."], "output": "[['Food', 'excellent', 'positive'], ['empenadas', 'excellent', 'positive'], ['plaintains', 'good', 'positive'], ['afternoon snack', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Both a number of the appetizer and pasta specials were amazing ."], "output": "[['pasta specials', 'amazing', 'positive'], ['appetizer', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All-time favorites include the Big Mac , Chicken McNuggets , Filet-O-Fish sandwich and McDonald 's famous french fries ; lighter options like entree-sized salads are also available ."], "output": "[['Big Mac', 'favorites', 'positive'], ['Chicken McNuggets', 'favorites', 'positive'], ['Filet-O-Fish sandwich', 'favorites', 'positive'], [\"McDonald 's famous french fries\", 'favorites', 'positive'], ['entree-sized salads', 'lighter options', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a basic pizza joint , not much to look at , but the pizza is what I go for ."], "output": "[['pizza', 'go for', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Tables are close , so you better be comfortable bumping elbows with other patrons ."], "output": "[['Tables', 'close', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not too much so , but enough that there 's a great scene ."], "output": "[['scene', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Meat-phobes are in luck with the extraordinary veggie burger , made from a distinctive blend of chickpeas , carrots and other vegetables and spices ."], "output": "[['veggie burger', 'extraordinary', 'positive'], ['chickpeas', 'distinctive', 'positive'], ['carrots', 'distinctive', 'positive'], ['vegetables', 'distinctive', 'positive'], ['spices', 'distinctive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["At peak times , the restaurant is overcrowded and tables are uncomfortably close ."], "output": "[['tables', 'uncomfortably close', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was on point - what else you would expect from a Ritz ?"], "output": "[['service', 'on point', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Menus feature seasonal picks , like sweet corn-foie gras brulee ."], "output": "[['Menus', 'seasonal', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Innovations are just as assured , from the simple Carinthia cheese ravioli with wild mushrooms to the caviar-topped sturgeon , beautifully matched with a bright green spinach-vodka sauce ."], "output": "[['Carinthia cheese ravioli with wild mushrooms', 'simple', 'positive'], ['green spinach-vodka sauce', 'bright', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And these are not small , wimpy fast food type burgers - these are real , full sized patties ."], "output": "[['burgers', 'small', 'positive'], ['burgers', 'wimpy fast food type', 'positive'], ['patties', 'real', 'positive'], ['patties', 'full sized', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There restaurant is very casual , but perfect for lunch , and their delivery service is always very fast ."], "output": "[['lunch', 'perfect', 'neutral'], ['delivery service', 'fast', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Chinatown definitely has better quality with cheaper prices ."], "output": "[['quality', 'better', 'positive'], ['prices', 'cheaper', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Go with the specials , and stay away from the salmon ."], "output": "[['specials', 'Go with', 'positive'], ['salmon', 'stay away', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pastas were pretty good ."], "output": "[['pastas', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Atmosphere is a bore ."], "output": "[['Atmosphere', 'bore', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wait staff was very attentive and polite ."], "output": "[['wait staff', 'attentive', 'positive'], ['wait staff', 'polite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great restaurant , and even greater food !"], "output": "[['food', 'greater', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The dishes are remarkably tasty and such a cozy and intimate place !"], "output": "[['dishes', 'tasty', 'positive'], ['place', 'cozy', 'positive'], ['place', 'intimate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the simplicity and respect which was given to the food , as well the staff was freindly and knowledgable ."], "output": "[['food', 'love', 'positive'], ['food', 'simplicity', 'positive'], ['food', 'respect', 'positive'], ['staff', 'love', 'positive'], ['staff', 'freindly', 'positive'], ['staff', 'knowledgable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was good and so was the atmosphere ."], "output": "[['Service', 'good', 'positive'], ['atmosphere', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["MY date and I both ordered the Branzini and both felt the fish was very average ."], "output": "[['Branzini', 'average', 'neutral'], ['fish', 'average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was good , the service prompt , and the price very reasonable ."], "output": "[['food', 'good', 'positive'], ['service', 'prompt', 'positive'], ['price', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wonderful menu , warm inviting ambiance , great service the FOOD keeps me coming back !"], "output": "[['menu', 'Wonderful', 'positive'], ['ambiance', 'warm inviting', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , good wine and an excellent host ."], "output": "[['food', 'Great', 'positive'], ['wine', 'good', 'positive'], ['host', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Pizzas were excellent in addition to appetizers and main courses ."], "output": "[['Pizzas', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Definitely try the calamari , any pasta , or even the Sliced steak entree ."], "output": "[['calamari', 'try', 'positive'], ['pasta', 'try', 'positive'], ['Sliced steak entree', 'try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The caeser salad was great ."], "output": "[['caeser salad', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The fried calamari was even better !"], "output": "[['fried calamari', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was good overall ."], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was outstanding and the service was tops ."], "output": "[['food', 'outstanding', 'positive'], ['service', 'tops', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The portions are very large and the service is fantastic ! !"], "output": "[['portions', 'large', 'positive'], ['service', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I recomend the chicken milanese ."], "output": "[['chicken milanese', 'recomend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["excellent tapas at great prices , romantic , small but not overly crowed , excellent"], "output": "[['tapas', 'excellent', 'positive'], ['prices', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chocolate raspberry cake is heavenly -- not too sweet , but full of flavor ."], "output": "[['chocolate raspberry cake', 'heavenly', 'positive'], ['chocolate raspberry cake', 'not too sweet', 'positive'], ['chocolate raspberry cake', 'full of flavor', 'positive'], ['flavor', 'full', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our waiter was helpful and charming , the food was perfect , and the wine was good , too ."], "output": "[['waiter', 'helpful', 'positive'], ['waiter', 'charming', 'positive'], ['food', 'perfect', 'positive'], ['wine', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best hot dogs in the tri-state area ."], "output": "[['hot dogs', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was very attentive and very generous ."], "output": "[['service', 'attentive', 'positive'], ['service', 'generous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We had tons of great food , wine , and desserts ."], "output": "[['food', 'great', 'positive'], ['wine', 'great', 'positive'], ['desserts', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Really Lovely dining experience in the midst of buzzing midtown area ."], "output": "[['dining experience', 'Lovely', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food really is n't very good and the service is terrible ."], "output": "[['food', \"is n't very good\", 'negative'], ['service', 'terrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only do they have the best escargot in town , they always try to accomodate our toddler ."], "output": "[['escargot', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Deco and ambiance was really romantic ."], "output": "[['Deco', 'romantic', 'positive'], ['ambiance', 'romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Just go in and sample the greatest french food west of Daniel ."], "output": "[['french food', 'greatest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Finally a curry that I can eat , enjoy and not suffer from gastritis from 3 hours later ."], "output": "[['curry', 'enjoy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All are GREAT - poori , naan , paratha all FRESH ."], "output": "[['poori', 'GREAT', 'positive'], ['naan', 'GREAT', 'positive'], ['paratha', 'FRESH', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the homemade breads ."], "output": "[['homemade breads', 'Try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has beautiful sushi , and it 's delicious CHEAP ."], "output": "[['sushi', 'beautiful', 'positive'], ['sushi', 'delicious CHEAP', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It also has lots of other Korean dishes that are affordable and just as yummy ."], "output": "[['Korean dishes', 'affordable', 'positive'], ['Korean dishes', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only was the waiter efficient and courteous , but also extremely helpful ."], "output": "[['waiter', 'efficient', 'positive'], ['waiter', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place is classy , chic , the service is warm and hospitable , and the food is outstanding ."], "output": "[['place', 'classy', 'positive'], ['place', 'chic', 'positive'], ['service', 'warm', 'positive'], ['service', 'hospitable', 'positive'], ['food', 'outstanding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great burgers , grilled cheeses and french fries ."], "output": "[['burgers', 'Great', 'positive'], ['grilled cheeses', 'Great', 'positive'], ['french fries', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Yellowfin Tuna and Calf 's liver are my favorites !"], "output": "[['Yellowfin Tuna', 'favorites', 'positive'], [\"Calf 's liver\", 'favorites', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sushi so fresh that it crunches in your mouth ."], "output": "[['Sushi', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But make sure you have enough room on your credit card as the bill will leave a big dent in your wallet ."], "output": "[['bill', 'big', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only was the sushi fresh , they also served other entrees allowed each guest something to choose from and we all left happy ( try the duck !"], "output": "[['sushi', 'fresh', 'positive'], ['duck', 'try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["good variety but nothing surprising ."], "output": "[['variety', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["No green beans , no egg , no anchovy dressing , no nicoise olives , no red onion ."], "output": "[['green beans', 'No', 'neutral'], ['egg', 'no', 'neutral'], ['anchovy dressing', 'no', 'neutral'], ['nicoise olives', 'no', 'neutral'], ['red onion', 'no', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Thick fries , meaty chili and stuffed baked potatoes round out a menu that includes a cool , ultra-thick chocolate Frosty ."], "output": "[['fries', 'Thick', 'neutral'], ['chocolate Frosty', 'cool', 'positive'], ['chocolate Frosty', 'ultra-thick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The homage to India is most evident in the delectable roti canai appetizer , a fried pancake served with pungent curry dipping sauce , while the mango chicken offers a surprisingly sophisticated , fresh take on sweet-and-sour ."], "output": "[['roti canai appetizer', 'delectable', 'positive'], ['mango chicken', 'surprisingly sophisticated', 'positive'], ['mango chicken', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The ground chickpea soup we sampled as a starter tasted somewhat thin ."], "output": "[['ground chickpea soup', 'thin', 'negative'], ['starter', 'thin', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service , however , is a peg or two below the quality of food ( horrible bartenders ) , and the clientele , for the most part , are rowdy , loud-mouthed commuters ( this could explain the bad attitudes from the staff ) getting loaded for an AC/DC concert or a Knicks game ."], "output": "[['service', 'below', 'negative'], ['bartenders', 'horrible', 'negative'], ['clientele', 'rowdy', 'negative'], ['clientele', 'loud-mouthed', 'negative'], ['staff', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you 're in the neighborhood , definitely stop by for a great meal ."], "output": "[['meal', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Although small , it has beautiful ambience , excellent food ( the catfish is delicious - if ya do n't mind it a lil salty ) and attentive service ."], "output": "[['ambience', 'beautiful', 'positive'], ['food', 'excellent', 'positive'], ['catfish', 'delicious', 'positive'], ['catfish', 'salty', 'positive'], ['service', 'attentive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Stick to the items the place does best , brisket , ribs , wings , cajun shrimp is good , not great ."], "output": "[['brisket', 'good', 'positive'], ['ribs', 'good', 'positive'], ['wings', 'good', 'positive'], ['cajun shrimp', 'good', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Hip boutiques and bars on Ludlow add to the artsy , laid-back atmosphere at this Israeli-style takeout and eat-in burger joint ."], "output": "[['atmosphere', 'artsy', 'positive'], ['atmosphere', 'laid-back', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My Chelsea 's impressive and creative menu includes modern , Westernized Japanese dishes such as Foie Gras Unagi Napolean , Jap style hamburger steak , spicy cod roe spaghetti , black cod with miso base , and rack of lamb in black truffle sauce , to name a few ."], "output": "[['menu', 'impressive', 'positive'], ['menu', 'creative', 'positive'], ['Japanese dishes', 'modern', 'neutral'], ['Japanese dishes', 'Westernized', 'neutral'], ['Foie Gras Unagi Napolean', 'modern', 'neutral'], ['Foie Gras Unagi Napolean', 'Westernized', 'neutral'], ['Jap style hamburger steak', 'modern', 'neutral'], ['Jap style hamburger steak', 'Westernized', 'neutral'], ['spicy cod roe spaghetti', 'modern', 'neutral'], ['spicy cod roe spaghetti', 'Westernized', 'neutral'], ['black cod with miso base', 'modern', 'neutral'], ['black cod with miso base', 'Westernized', 'neutral'], ['rack of lamb in black truffle sauce', 'modern', 'neutral'], ['rack of lamb in black truffle sauce', 'Westernized', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["His food is excellent ( and not expensive by NYC standards- no entrees over $ 30 , most appetizers $ 12 to 14 ) ."], "output": "[['food', 'excellent', 'positive'], ['appetizers', 'not expensive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is consistant and good but how it got name Best Diner In Manhattan is beyond me ."], "output": "[['food', 'consistant', 'positive'], ['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pasta primavera was outstanding as well , lots of fresh veggies ."], "output": "[['pasta primavera', 'outstanding', 'positive'], ['fresh veggies', 'lots', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["do n't get me wrong - sushi was good , just not fantastic ."], "output": "[['sushi', 'good', 'positive'], ['sushi', 'not fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Been to the one in Brooklyn for over 25 years , now I dont have to go over the bridge for the best pizza ... .Hanx"], "output": "[['pizza', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had dinner here on a Friday and the food was great ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We recently spent New Year 's Eve at the restaurant , and had a great experience , from the wine to the dessert menu ."], "output": "[['wine', 'great', 'positive'], ['dessert menu', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Highly recommended ... As stated , I have n't dined *in* the restaurant but stopped by there to pick up takeout and it seems a very relaxing place ; also , the bar looks nice ."], "output": "[['place', 'relaxing', 'positive'], ['bar', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The ambiance was fine , a little loud but still nice and romantic ."], "output": "[['ambiance', 'fine', 'positive'], ['ambiance', 'loud', 'positive'], ['ambiance', 'nice', 'positive'], ['ambiance', 'romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["but , the filet mignon was not very good at all cocktail hour includes free appetizers ( nice non-sushi selection ) ."], "output": "[['filet mignon', 'not very good', 'negative'], ['non-sushi selection', 'nice', 'positive'], ['appetizers', 'free', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Can be a bit busy around peak times because of the size ."], "output": "[['size', 'busy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was on jury duty , rode my bike up Centre Street on my lunch break and came across this great little place with awesome chicken tacos and Hibiscus lemonade ."], "output": "[['chicken tacos', 'awesome', 'positive'], ['Hibiscus lemonade', 'awesome', 'positive'], ['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["good place to hang out during the day after shopping or to grab a simple soup or classic french dish over a glass of wine ."], "output": "[['place', 'good', 'positive'], ['soup', 'simple', 'neutral'], ['french dish', 'classic', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Very nice touch that very much fits the place ."], "output": "[['place', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , there is just something so great about being outdoors , in great landscaping , enjoying a casual drink that makes going to this place worthwhile ."], "output": "[['casual drink', 'enjoying', 'positive'], ['outdoors', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The comments about fried foods is correct ( below ) but the other dishes , including the lamb entree and many of the salads ( avocado shrimp ) were quite good ."], "output": "[['dishes', 'good', 'positive'], ['lamb entree', 'good', 'positive'], ['salads ( avocado shrimp )', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Slow service , but when you 're hanging around with groups of 10 or 20 , who really notices ?"], "output": "[['service', 'Slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sauce is excellent ( very fresh ) with dabs of real mozzarella ."], "output": "[['sauce', 'excellent', 'positive'], ['sauce', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Do n't ever bother - the drinks were awful , but it was the people who work there that really made this the worst experience at dining ."], "output": "[['drinks', 'awful', 'negative'], ['people', 'worst', 'negative'], ['dining', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The room is a little plain , but it 's difficult to make such a small place exciting and I would not suggest that as a reason not to go ."], "output": "[['room', 'plain', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Prices even outside of restaurant week were great ."], "output": "[['Prices', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A small , outdoor eating area makes for a private , comfortable space to study alone or meet up with friends ."], "output": "[['space', 'private', 'positive'], ['space', 'comfortable', 'positive'], ['outdoor eating area', 'small', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The best dessert , a chocolate and peanut butter tart , is n't particularly Hawaiian , but it 's a small world when it comes to sweets ."], "output": "[['dessert', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["for an appetizer , their calamari is a winner ."], "output": "[['appetizer', 'winner', 'neutral'], ['calamari', 'winner', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The room is a gorgeous , bi-level space and the long bar perfect for a drink ."], "output": "[['room', 'gorgeous', 'positive'], ['bi-level space', 'gorgeous', 'positive'], ['long bar', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Two complaints- their appetizer selection stinks , it would be nice to get some mozzarella sticks on the menu ."], "output": "[['appetizer selection', 'stinks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was especially impressed during the bday party when the waitstaff went above and beyond in helping me decorate and bring out a bday cake as well as offering prompt and friendly service to a 15 person party ."], "output": "[['service', 'prompt', 'positive'], ['service', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chicken and falafel platters were nondescript combinations with fresh leaf salad ."], "output": "[['chicken and falafel platters', 'nondescript', 'neutral'], ['fresh leaf salad', 'fresh', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["several times and put up with the waiters ' bad manners , knowing that their job is n't easy ."], "output": "[['waiters', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is great ( maybe even borderline nagging but at least you get attention ) , the desserts are excellent and the coffee is so very good ..."], "output": "[['desserts', 'excellent', 'positive'], ['coffee', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They are served on Focacchia bread and are to die for ."], "output": "[['Focacchia bread', 'die for', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While the smoothies are a little big for me , the fresh juices are the best I have ever had !"], "output": "[['smoothies', 'big', 'negative'], ['fresh juices', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is just OKAY , and it 's almost not worth going unless you 're getting the pialla , which is the only dish that 's really good ."], "output": "[['pialla', 'good', 'positive'], ['dish', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The guac is fresh , yet lacking flavor , we like to add our fresh salsa into it ."], "output": "[['flavor', 'lacking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The new menu has a few creative items , they were smart enough to keep some of the old favorites ( but they raised the prices ) , the staff is friendly most of the time , but I must agree with the person that wrote about their favorite words : No , ca n't , sorry ... , boy , they wo n't bend the rules for anyone ."], "output": "[['prices', 'raised', 'negative'], ['new menu', 'creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It ' only open for lunch but the food is so good !"], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["How can they survive serving mediocre food at exorbitant prices ? !"], "output": "[['food', 'mediocre', 'neutral'], ['prices', 'exorbitant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was mediocre and the service was severely slow ."], "output": "[['service', 'severely slow', 'negative'], ['food', 'mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i have eaten here on a different occasion - the food is mediocre for the prices ."], "output": "[['food', 'mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I asked repeatedly what the status of the meal was and was pretty much grunted at by the unbelievably rude waiter ."], "output": "[['waiter', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sweet Irish bartender is always happy and able to bring a smile to my friends a my face ."], "output": "[['bartender', 'Sweet', 'positive'], ['bartender', 'happy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Its good to go there for drinks if you do n't want to get drunk because you 'll be lucky if you can get one drink an hour the service is so bad ."], "output": "[['service', 'bad', 'negative'], ['drinks', 'good', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Anyway , the owner was fake ."], "output": "[['owner', 'fake', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Owner is pleasant and entertaining ."], "output": "[['Owner', 'pleasant', 'positive'], ['Owner', 'entertaining', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Creamy appetizers -- taramasalata , eggplant salad , and Greek yogurt ( with cuccumber , dill , and garlic ) taste excellent when on warm pitas ."], "output": "[['Creamy appetizers', 'Creamy', 'positive'], ['Creamy appetizers', 'excellent', 'positive'], ['warm pitas', 'warm', 'neutral'], ['taramasalata', 'Creamy', 'positive'], ['eggplant salad', 'excellent', 'positive'], ['Greek yogurt ( with cuccumber , dill , and garlic )', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Love Al Di La"], "output": "[['Al Di La', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I recommend this place to everyone ."], "output": "[['place', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food ."], "output": "[['food', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pastas are incredible , the risottos ( particularly the sepia ) are fantastic and the braised rabbit is amazing ."], "output": "[['pastas', 'incredible', 'positive'], ['risottos', 'fantastic', 'positive'], ['sepia', 'fantastic', 'positive'], ['braised rabbit', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food here was mediocre at best ."], "output": "[['food', 'mediocre', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was totally overpriced - fish and chips was about $ 15 ... ."], "output": "[['fish and chips', 'overpriced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Tasty Dog !"], "output": "[['Dog', 'Tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["An awesome organic dog , and a conscious eco friendly establishment ."], "output": "[['dog', 'organic', 'positive'], ['establishment', 'eco friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the best pork souvlaki I ever had is the main thing ."], "output": "[['pork souvlaki', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Super YUMMY Pizza !"], "output": "[['Pizza', 'YUMMY', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was visiting New York City with a friend and we discovered this really warm and inviting restaurant ."], "output": "[['restaurant', 'inviting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I LOOOVE their eggplant pizza , as well as their pastas !"], "output": "[['eggplant pizza', 'LOOOVE', 'positive'], ['pastas', 'LOOOVE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We had half/half pizza , mine was eggplant and my friend had the buffalo and it was sooo huge for a small size pizza !"], "output": "[['half/half pizza', 'huge', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Excellent food , although the interior could use some help ."], "output": "[['food', 'Excellent', 'positive'], ['interior', 'help', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I paid just about $ 60 for a good meal , though : )"], "output": "[['meal', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great sake !"], "output": "[['sake', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Reliable , Fresh Sushi"], "output": "[['Sushi', 'Reliable', 'positive'], ['Sushi', 'Fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sashimi is always fresh and the rolls are innovative and delicious ."], "output": "[['sashimi', 'fresh', 'positive'], ['rolls', 'innovative', 'positive'], ['rolls', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Have never had a problem with service save a missing rice once ."], "output": "[['service', 'problem', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delivery can be spot on or lacking depending on the weather and the day of the week ."], "output": "[['Delivery', 'lacking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delivery guy sometimes get upset if you do n't tip more than 10 % ."], "output": "[['Delivery guy', 'upset', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best . Sushi . Ever ."], "output": "[['Sushi', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has ruined me for neighborhood sushi ."], "output": "[['sushi', 'ruined', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Excellent sashimi , and the millennium roll is beyond delicious ."], "output": "[['sashimi', 'Excellent', 'positive'], ['millennium roll', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place is a bit hidden away , but once you get there , it 's all worth it ."], "output": "[['place', 'hidden away', 'positive'], ['place', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiter was attentive , the food was delicious and the views of the city were great ."], "output": "[['waiter', 'attentive', 'positive'], ['food', 'delicious', 'positive'], ['views of the city', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great place to relax and enjoy your dinner"], "output": "[['place', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good food : my favorite is the seafood spaghetti ."], "output": "[['food', 'Good', 'positive'], ['seafood spaghetti', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Excellent food for great prices"], "output": "[['food', 'Excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wait staff is very courteous and accomodating ."], "output": "[['wait staff', 'courteous', 'positive'], ['wait staff', 'accomodating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The space is limited so be prepared to wait up to 45 minutes - 1 hour , but be richly rewarded when you savor the delicious indo-chinese food ."], "output": "[['space', 'limited', 'negative'], ['indo-chinese food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["my favorite place lol"], "output": "[['place', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i love their chicken pasta cant remember the name but is sooo good"], "output": "[['chicken pasta', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["im not necessarily fanatical about this place , but it was a fun time for low pirces ."], "output": "[['place', 'fanatical', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["lobster was good , nothing spectacular ."], "output": "[['lobster', 'good', 'neutral'], ['lobster', 'nothing spectacular', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["its just a fun place to go , not a five star restaraunt ."], "output": "[['restaraunt', 'five star', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I think the pizza is so overrated and was under cooked ."], "output": "[['pizza', 'overrated', 'negative'], ['pizza', 'under cooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had no flavor and the staff is rude and not attentive ."], "output": "[['staff', 'rude', 'negative'], ['staff', 'not attentive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love this place"], "output": "[['place', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was quick and friendly ."], "output": "[['service', 'quick', 'positive'], ['service', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I thought the restaurant was nice and clean ."], "output": "[['restaurant', 'nice', 'positive'], ['restaurant', 'clean', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I ordered the vitello alla marsala and I was pretty impressed ."], "output": "[['vitello alla marsala', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The veal and the mushrooms were cooked perfectly ."], "output": "[['veal', 'perfectly', 'positive'], ['mushrooms', 'perfectly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The potato balls were not dry at all ... in fact it was buttery ."], "output": "[['potato balls', 'not dry', 'positive'], ['potato balls', 'buttery', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["WORST PLACE ON SMITH STREET IN BROOKLYN"], "output": "[['PLACE', 'WORST', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Very immature bartender , didnt know how to make specific drinks , service was so slowwwww , the food was not fresh or warm , waitresses were busy flirting with men at the bar and werent very attentive to all the customers ."], "output": "[['bartender', 'immature', 'negative'], ['service', 'slowwwww', 'negative'], ['food', 'not fresh or warm', 'negative'], ['waitresses', 'werent very attentive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I would never recommend this place to anybody even for a casual dinner ."], "output": "[['place', 'never recommend', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the food is always fresh ..."], "output": "[['food', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["overpriced japanese food with mediocre service"], "output": "[['japanese food', 'overpriced', 'negative'], ['service', 'mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["food was luke warm ."], "output": "[['food', 'luke warm', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waitress was not attentive at all ."], "output": "[['waitress', 'not attentive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was excellent as well as service , however , I left The Four Seasons very dissappointed ."], "output": "[['food', 'excellent', 'positive'], ['service', 'excellent', 'positive'], ['The Four Seasons', 'dissappointed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Red Dragon Roll - my favorite thing to eat , of any food group - hands down"], "output": "[['Red Dragon Roll', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Seafood Dynamite is also otherworldly ."], "output": "[['Seafood Dynamite', 'otherworldly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Favorite Sushi in NYC"], "output": "[['Sushi', 'Favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["An unpretentious spot in Park Slope , the sushi is consistently good , the service is pleasant , effective and unassuming ."], "output": "[['spot', 'unpretentious', 'positive'], ['sushi', 'good', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'effective', 'positive'], ['service', 'unassuming', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In the summer months , the back garden area is really nice ."], "output": "[['back garden area', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The rolls are creative and I have yet to find another sushi place that serves up more inventive yet delicious japanese food ."], "output": "[['rolls', 'creative', 'positive'], ['japanese food', 'inventive', 'positive'], ['japanese food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Dancing , White River and Millenium rolls are musts ."], "output": "[['Dancing , White River and Millenium rolls', 'musts', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I CAN EAT HERE EVERY DAY OF THE WEEK REALLY LOL LOVE THIS PLACE ... )"], "output": "[['PLACE', 'LOVE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Gross food \u2013 Wow-"], "output": "[['food', 'Gross', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And $ 11 for a plate of bland guacamole ?"], "output": "[['guacamole', 'bland', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Oh , and I never write reviews -- I just was so moved by how bad this place was , I felt it was my duty to spread the word ."], "output": "[['place', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Indian Food !"], "output": "[['Indian Food', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was good , the place was clean and affordable ."], "output": "[['food', 'good', 'positive'], ['place', 'clean', 'positive'], ['place', 'affordable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I noticed alot of indian people eatting there which is a great sign for an indian place !"], "output": "[['indian place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is one of my favorite spot , very relaxing the food is great all the times , celebrated my engagement and my wedding here , it was very well organized ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is very good ."], "output": "[['staff', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Love their drink menu ."], "output": "[['drink menu', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I highly recommend this beautiful place ."], "output": "[['place', 'recommend', 'positive'], ['place', 'beautiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nice view of river and NYC ."], "output": "[['view of river and NYC', 'Nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great survice"], "output": "[['survice', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A beautifully designed dreamy Egyptian restaurant that gets sceney at night ."], "output": "[['Egyptian restaurant', 'dreamy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Watch the talented belly dancers as you enjoy delicious baba ganoush that 's more lemony than smoky ."], "output": "[['baba ganoush', 'enjoy delicious', 'positive'], ['belly dancers', 'talented', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Raymond the bartender rocks !"], "output": "[['Raymond', 'rocks', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Pacifico is a great place to casually hang out ."], "output": "[['Pacifico', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The drinks are great , especially when made by Raymond ."], "output": "[['drinks', 'great', 'positive'], ['Raymond', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The omlette for brunch is great ..."], "output": "[['omlette for brunch', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the spinach is fresh , definately not frozen ..."], "output": "[['spinach', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["quacamole at pacifico is yummy , as are the wings with chimmichuri ."], "output": "[['quacamole', 'yummy', 'positive'], ['wings with chimmichuri', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A weakness is the chicken in the salads ."], "output": "[['chicken in the salads', 'weakness', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also , I personally was n't a fan of the portobello and asparagus mole ."], "output": "[['portobello and asparagus mole', 'fan', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Overall , decent food at a good price , with friendly people ."], "output": "[['food', 'decent', 'positive'], ['people', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Indian Restaurant in the City"], "output": "[['Indian Restaurant', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Decor needs to be upgraded but the food is amazing !"], "output": "[['Decor', 'upgraded', 'negative'], ['food', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This small Astoria souvlaki spot makes what many consider the best gyros in New York ."], "output": "[['gyros', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["What really makes it shine is the food , which is aggressively seasoned with Cyrpriot spices , and all made in-house ( even the gyro meat and sausages ) , and made of much higher quality ingredients that might otherwise be expected ."], "output": "[['food', 'shine', 'positive'], ['gyro meat', 'in-house', 'positive'], ['sausages', 'in-house', 'positive'], ['ingredients', 'higher quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All the various Greek and Cypriot dishes are excellent , but the gyro is the reason to come -- if you do n't eat one your trip was wasted ."], "output": "[['Greek and Cypriot dishes', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best restaurant in Brooklyn"], "output": "[['restaurant', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , amazing service , this place is a class act ."], "output": "[['food', 'Great', 'positive'], ['service', 'amazing', 'positive'], ['place', 'class act', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The veal was incredible last night ."], "output": "[['veal', 'incredible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place is a must visit !"], "output": "[['place', 'must visit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is all shared so we get to order together and eat together ."], "output": "[['food', 'shared', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've enjoyed 99 % of the dishes we 've ordered with the only exceptions being the occasional too-authentic-for-me dish ( I 'm a daring eater but not THAT daring ) ."], "output": "[['dishes', 'enjoyed', 'positive'], ['dish', 'too-authentic-for-me', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My daughter 's wedding reception at Water 's Edge received the highest compliments from our guests ."], "output": "[[\"Water 's Edge\", 'highest compliments', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everyone raved about the atmosphere ( elegant rooms and absolutely incomparable views ) and the fabulous food !"], "output": "[['atmosphere', 'raved', 'positive'], ['rooms', 'elegant', 'positive'], ['views', 'incomparable', 'positive'], ['food', 'fabulous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was wonderful ;"], "output": "[['Service', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Paul , the maitre d ' , was totally professional and always on top of things ."], "output": "[['Paul', 'professional', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service ok but unfriendly , filthy bathroom ."], "output": "[['Service', 'ok', 'negative'], ['Service', 'unfriendly', 'negative'], ['bathroom', 'filthy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bar drinks were Eh , ok to say the least ."], "output": "[['bar drinks', 'ok', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The stuff tilapia was horrid ... tasted like cardboard ."], "output": "[['stuff tilapia', 'horrid', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["oh speaking of bathroom , the mens bathroom was disgusting ."], "output": "[['mens bathroom', 'disgusting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine list was extensive - though the staff did not seem knowledgeable about wine pairings ."], "output": "[['wine list', 'extensive', 'positive'], ['staff', 'not seem knowledgeable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bread we received was horrible - rock hard and cold - and the `` free '' appetizer of olives was disappointing ."], "output": "[['bread', 'horrible', 'negative'], ['bread', 'rock hard', 'negative'], ['bread', 'cold', 'negative'], ['appetizer of olives', 'disappointing', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , our main course was wonderful ."], "output": "[['main course', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had fish and my husband had the filet - both of which exceeded our expectations ."], "output": "[['fish', 'exceeded our expectations', 'positive'], ['filet', 'exceeded our expectations', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The dessert ( we had a pear torte ) was good - but , once again , the staff was unable to provide appropriate drink suggestions ."], "output": "[['pear torte', 'good', 'positive'], ['staff', 'unable to provide', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not what I would expect for the price and prestige of this location ."], "output": "[['location', 'expect', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All in all , I would return - as it was a beautiful restaurant - but I hope the staff pays more attention to the little details in the future ."], "output": "[['restaurant', 'beautiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["short and sweet \u2013 seating is great : it 's romantic , cozy and private ."], "output": "[['seating', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The boths are not as small as some of the reviews make them out to look they 're perfect for 2 people ."], "output": "[['boths', 'not as small', 'positive'], ['boths', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was extremely fast and attentive ( thanks to the service button on your table ) but I barely understood 1 word when the waiter took our order ."], "output": "[['service', 'fast', 'positive'], ['service', 'attentive', 'positive'], ['service button', 'thanks to', 'positive'], ['waiter', 'barely understood', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was ok and fair nothing to go crazy ."], "output": "[['food', 'ok', 'neutral'], ['food', 'fair', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Over all the looks of the place exceeds the actual meals ."], "output": "[['looks', 'exceeds', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Subtle food and service"], "output": "[['food', 'Subtle', 'positive'], ['service', 'Subtle', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Noodle pudding is exactly the type of service and food I enjoy ."], "output": "[['service', 'enjoy', 'positive'], ['food', 'enjoy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Servers are all different , Greg is my favorite ."], "output": "[['Greg', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I go out to eat and like my courses , servers are patient and never rush courses or force another drink ."], "output": "[['servers', 'patient', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["amazing fresh dogs but best of all endless toppings ! ! !"], "output": "[['dogs', 'amazing fresh', 'positive'], ['toppings', 'best', 'positive'], ['toppings', 'endless', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["amazing fun for hot dog lovers of all ages PLEASE do yourself a favor and check this place out ! ! ! !"], "output": "[['hot dog', 'amazing fun', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Stepping into Casa La Femme last night was a true experience unlike any other in New York !"], "output": "[['Casa La Femme', 'true', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Highly impressed from the decor to the food to the hospitality to the great night I had !"], "output": "[['decor', 'impressed', 'positive'], ['food', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The have a great cocktail with Citrus Vodka and lemon and lime juice and mint leaves that is to die for !"], "output": "[['cocktail with Citrus Vodka and lemon and lime juice and mint leaves', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food took some time to prepare , all worth waiting for ."], "output": "[['Food', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We were drawn into the belly dancing show that captivated the crowd ."], "output": "[['belly dancing show', 'captivated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I never write on these sites but this restaurant is def worth commending !"], "output": "[['restaurant', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu looked great , and the waiter was very nice , but when the food came , it was average ."], "output": "[['waiter', 'nice', 'positive'], ['food', 'average', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have worked in restaurants and cook a lot , and there is no way a maggot should be able to get into well prepared food ."], "output": "[['food', 'well prepared', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For a restaurant with such a good reputation and that is usually so packed , there was no reason for such a lack of intelligent customer service ."], "output": "[['restaurant', 'good reputation', 'positive'], ['customer service', 'intelligent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great place , great value ."], "output": "[['place', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is flavorful , plentiful and reasonably priced ."], "output": "[['food', 'flavorful', 'positive'], ['food', 'plentiful', 'positive'], ['food', 'reasonably priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere is relaxed and casual ."], "output": "[['atmosphere', 'relaxed', 'positive'], ['atmosphere', 'casual', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a great place to order from or sit-in ."], "output": "[['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sushi experience was unbelievable with my fiance ."], "output": "[['Sushi', 'unbelievable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good creative rolls !"], "output": "[['rolls', 'Good creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yamato is an excellent place to go if youre not into sashimi , or if you have friends who doesnt like sushi much ."], "output": "[['Yamato', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have great rolls , the triple color and norwegetan rolls , are awesome and filling ."], "output": "[['rolls', 'great', 'positive'], ['triple color and norwegetan rolls', 'awesome', 'positive'], ['triple color and norwegetan rolls', 'filling', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["One special roll and one regular roll is enough to fill you up , but save room for dessert !"], "output": "[['dessert', 'save room', 'positive'], ['special roll', 'enough', 'positive'], ['regular roll', 'enough', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have a delicious banana chocolate dessert , as well as a great green tea tempura ."], "output": "[['banana chocolate dessert', 'delicious', 'positive'], ['green tea tempura', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The appetizers are also delicious !"], "output": "[['appetizers', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Amazing food ."], "output": "[['food', 'Amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mazing interior ."], "output": "[['interior', 'Mazing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food !"], "output": "[['food', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had my fair share of modern Japanese and this spot delivers ."], "output": "[['modern Japanese', 'delivers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere was pretty nice but had a bit lacking , which it tries to make up for with a crazy scheme of mirrors ."], "output": "[['atmosphere', 'nice', 'negative'], ['scheme of mirrors', 'crazy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Despite the confusing mirrors this will likely be my go-to for modern Japanese food for the foreseeable future ."], "output": "[['modern Japanese food', 'go-to for', 'positive'], ['mirrors', 'confusing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Indo Chinese food , pretty good ..."], "output": "[['Indo Chinese food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not a very fancy place but very good Chinese style Indian food ."], "output": "[['place', 'fancy', 'neutral'], ['Chinese style Indian food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chicken lollipop is my favorite , most of the dishes ( I have to agree with a previous reviewer ) are quite oily and very spicy , espeically the Chilli Chicken ."], "output": "[['chicken lollipop', 'favorite', 'positive'], ['dishes', 'oily', 'negative'], ['dishes', 'spicy', 'negative'], ['Chilli Chicken', 'oily', 'negative'], ['Chilli Chicken', 'spicy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My mom originally introduced me to this place , but even she ( being Indian ) feels the food can be somewhat over the top spicy and far too oily ."], "output": "[['food', 'spicy', 'negative'], ['food', 'oily', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was speechless by the horrible food ."], "output": "[['food', 'speechless', 'negative'], ['food', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I attended a holiday dinner at the restaurant , and the food was majorly disappointing ."], "output": "[['food', 'disappointing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is the MOST wonderful restaurant in all of New York City , not just Brooklyn ..."], "output": "[['restaurant', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["for 7 years they have put out the most tasty , most delicious food and kept it that way ..."], "output": "[['food', 'tasty', 'positive'], ['food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["never swaying , never a bad meal , never bad service ..."], "output": "[['meal', 'never a bad', 'positive'], ['service', 'never bad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great food , great wine list , great service in a great neighborhood ..."], "output": "[['food', 'great', 'positive'], ['wine list', 'great', 'positive'], ['service', 'great', 'positive'], ['neighborhood', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Patsy 's Pizza - true love"], "output": "[[\"Patsy 's Pizza\", 'true love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Hands down the best pizza on the planet ."], "output": "[['pizza', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great hot dogs ."], "output": "[['hot dogs', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the hot dogs were juicy and tender inside and had plenty of crunch and snap on the outside ."], "output": "[['hot dogs', 'juicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great toppings definitely a place you need to check out for late night munchies or a mid day boost !"], "output": "[['toppings', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For me dishes a little oily , but overall dining experience good ."], "output": "[['dishes', 'oily', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Helpful service and average price per dish $ 10 ."], "output": "[['service', 'Helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only thing that strikes you is the decor ? ( not very pleasant ) ."], "output": "[['decor', 'not very pleasant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great food"], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has great indian chinese food ."], "output": "[['indian chinese food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Be prepared to wait , because the place is pretty tiny ."], "output": "[['place', 'tiny', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Even though the place is not beautiful , the food speaks for itself ."], "output": "[['place', 'not beautiful', 'negative'], ['food', 'speaks for itself', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Indian Chinese in the city , by far !"], "output": "[['Indian Chinese', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The martinis are amazing and very fairly priced ."], "output": "[['martinis', 'amazing', 'positive'], ['martinis', 'fairly priced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE SERVICE IS AMAZING , i 've had different waiters and they were all nice , which is a rare thing in NYC ."], "output": "[['SERVICE', 'AMAZING', 'positive'], ['waiters', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The DJ is awesome , I have been there for my birthday and a bunch of other times with friends and I keep going back ."], "output": "[['DJ', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything on the menu is great ."], "output": "[['menu', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This establishment is the real deal ."], "output": "[['establishment', 'real deal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wish NY had more of these kind of places : intimate , superb food , homey , top notch all the way around , certainly worth the wait ."], "output": "[['food', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Look , the appetizers were really good ."], "output": "[['appetizers', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The entree was also very good ."], "output": "[['entree', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yes , the place is classy and beautiful , but they most certainly target the uber whealthy Not the common joe that wants to go all out every once in a while ."], "output": "[['place', 'classy', 'negative'], ['place', 'beautiful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Vanison was good but not amazing ."], "output": "[['Vanison', 'good', 'neutral'], ['Vanison', 'not amazing', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Bison was quite excellent however ."], "output": "[['Bison', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Dessert : pure disaster ."], "output": "[['Dessert', 'disaster', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I read reviews that called the restaurant too expensive and I thought to myself , but may be it is worth it ."], "output": "[['restaurant', 'expensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All in all , the food was great ( except for the dessserts ) ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The environment is very upscale and you will see a lot of rich guys with trophy wives or just highly paid escorts ."], "output": "[['environment', 'upscale', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you are going for the food , it will not be worth it ."], "output": "[['food', 'worth', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You would think they would make up for it with service , sadly , no ."], "output": "[['service', 'sadly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was just ok , it is not what you 'd expect for $ 500 ."], "output": "[['Service', 'ok', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I literally just got back home after visiting Casa La Femme and was so offended by my visit felt it necessary to try and warn other diners who value their money and time ."], "output": "[['Casa La Femme', 'offended', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place is beautiful !"], "output": "[['place', 'beautiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hostess was very pleasant ."], "output": "[['hostess', 'pleasant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , our $ 14 drinks were were horrible !"], "output": "[['drinks', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We asked for sides which the waiter than admitted that he forgot to put in that part of our order ."], "output": "[['waiter', 'forgot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My chicken was inedible as there were so many fatty lumps which i had to keep spitting out into my napkin ."], "output": "[['chicken', 'inedible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["By the time we left our wallets were empy and so were our stomachs AND we missed the show we were supposed to see following our dinner , which would have been acceptable if we got to enjoy the experience of good food and belly dancers !"], "output": "[['food', 'good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If it seemed possible to do so while there I would have fought my bill since my dinner portion of my meal was inedible !"], "output": "[['meal', 'inedible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have never left a restaurant feeling as if i was abused , and wasted my hard earned money ."], "output": "[['restaurant', 'abused', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu is fairly simple without much descriptions ."], "output": "[['menu', 'simple', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There was no tap beer that evening , which was a disappointment ."], "output": "[['beer', 'disappointment', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not much of a selection of bottled beer either , we went with Brahma ."], "output": "[['selection of bottled beer', 'Not much', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The appetizers we ordered were served quickly - an order of fried oysters and clams were delicious but a tiny portion ( maybe 3 of each ) ."], "output": "[['fried oysters and clams', 'delicious', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lobster knuckles ( special of the day ) were ok , but pretty tasteless ."], "output": "[['lobster knuckles', 'ok', 'negative'], ['lobster knuckles', 'tasteless', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had the Thai style Fried Sea Bass ... which was very good ."], "output": "[['Thai style Fried Sea Bass', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everyone seemed generally happy with their food , except my brother who had the grilled Mahi Mahi , seemingly drenched in Grapfruit Juice !"], "output": "[['food', 'happy', 'positive'], ['grilled Mahi Mahi', 'drenched', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I heard the lobster roll was excellent ."], "output": "[['lobster roll', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All in all the food was good - a little on the expensive side , but fresh ."], "output": "[['food', 'good', 'negative'], ['food', 'expensive', 'negative'], ['food', 'fresh', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service not the friendliest to our `` large party '' !"], "output": "[['Service', 'not the friendliest', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Indian food"], "output": "[['Indian food', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food was amazing - I love Indian food and eat it quite regularly , but I can say this is one of the best I 've had ."], "output": "[['Food', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Very `` normal Indian food '' , but done really well ."], "output": "[['Indian food', 'normal', 'positive'], ['Indian food', 'well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lunch buffet is expensive but is deff worth it ."], "output": "[['lunch buffet', 'expensive', 'positive'], ['lunch buffet', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We have gone for dinner only a few times but the same great quality and service is given ."], "output": "[['service', 'great', 'positive'], ['dinner', 'great quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Bukhara is on my top 5 Indian places in NYC"], "output": "[['Bukhara', 'top', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have never been so disgusted by both food an service ."], "output": "[['food', 'disgusted', 'negative'], ['service', 'disgusted', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , once I received my predictably mediocre order of what Dokebi thinks passes as Korean fair , ( sometimes you have to settle when it 's your only option ) , I got through about half my kimchee before I found a piece of random lettuce accompanied by a far more disgusting , slimy , clearly bad piece of fish skin ."], "output": "[['kimchee', 'disgusting', 'negative'], ['Korean fair', 'mediocre', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My girlfriend , being slightly more aggressive , and having been equally disgusted causing her to throw out the remainder of her barely eaten meal , called back only to be informed that I was probably wrong and that it was most likely an oyster , and that we were also blacklisted from their restaurant ."], "output": "[['meal', 'disgusted', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was n't as if this restaurant had any major bragging points before hand , but now it 's simply repulsive ."], "output": "[['restaurant', 'repulsive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Gorgeous place ideal for a romantic dinner"], "output": "[['place', 'Gorgeous', 'positive'], ['place', 'ideal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I book a gorgeous white organza tent which included a four course prix fix menu which we enjoyed a lot ."], "output": "[['four course prix fix menu', 'enjoyed', 'positive'], ['white organza tent', 'gorgeous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was spectacular as the waiter knew everything about the menu and his recommendations were amazing !"], "output": "[['service', 'spectacular', 'positive'], ['waiter', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I completely recommend Casa La Femme for any special occasion and to REALLY impress your date ."], "output": "[['Casa La Femme', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bibimbap was average , but the stone bowl was n't even close to sizzling ."], "output": "[['bibimbap', 'average', 'neutral'], ['stone bowl', \"was n't even close to sizzling\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Too bad I had paid an extra $ 2 for the stone bowl ."], "output": "[['stone bowl', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The nakgi-bokum was horrible ."], "output": "[['nakgi-bokum', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Easily the worst stir-fried squid I 've ever tasted ."], "output": "[['stir-fried squid', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The side dishes were passable , and I did get a refill upon request ."], "output": "[['side dishes', 'passable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The real problem I had with this place was the complete lack of service ."], "output": "[['service', 'lack of', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My wife had barely touched that mess of a dish ."], "output": "[['dish', 'mess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wife had the risotto which was amazing ."], "output": "[['risotto', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The farro salad and the mashed yukon potatoes were also extremely tasty ."], "output": "[['farro salad', 'tasty', 'positive'], ['mashed yukon potatoes', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i love margherita pizza \u2013 i looove east village pizza"], "output": "[['east village pizza', 'love', 'positive'], ['margherita pizza', 'looove', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Love this place , every time we are in the city this is one of the places we always go ."], "output": "[['place', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A quintessential slice of NYC pizza ."], "output": "[['slice of NYC pizza', 'quintessential', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The crust has a great bite and a good chew , the sauce is light with a nice acidity to it , the salt from the cheese is great , really heightens the flavor of all the other components ."], "output": "[['crust', 'great', 'positive'], ['crust', 'good', 'positive'], ['sauce', 'light', 'positive'], ['cheese', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Personally I like the margherita pizza better , but they are all good ."], "output": "[['margherita pizza', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Possibly the Most Romantic Restaurant in the City"], "output": "[['Restaurant', 'Romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is undoubtedly my favorite modern Japanese brasserie ( that don \u2019 t serve sushi ) , and in my opinion , one of the most romantic restaurants in the city !"], "output": "[['modern Japanese brasserie', 'favorite', 'positive'], ['modern Japanese brasserie', 'romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only is it an adventure getting to this somewhat hidden spot , once you enter the unmarked wooden doors , the zen and intimate d\u00e9cor will make you feel like you \u2019 re no longer in the city ."], "output": "[['spot', 'hidden', 'neutral'], ['d\u00e9cor', 'intimate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you \u2019 re planning to come here , make sure that your date is someone whom you really like since you \u2019 ll be ushered to private booths where there will be no people or food watching ( choose the ones on the ground level that have glass ceilings so you may see the stars in the sky ! ) ."], "output": "[['private booths', 'ushered', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We started off with a delightful sashimi amuse bouche ."], "output": "[['sashimi amuse bouche', 'delightful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I picked the Grilled Black Cod as my entree , which I absolutely devoured while someone commented that the Grilled Salmon dish was better ."], "output": "[['Grilled Black Cod', 'devoured', 'positive'], ['Grilled Salmon dish', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For desserts , we tried the frozen black sesame mousse ( interesting but not extraordinary ) and matcha ( powdered green tea ) and blueberry cheesecake , which was phenomenal ."], "output": "[['frozen black sesame mousse', 'interesting', 'neutral'], ['frozen black sesame mousse', 'extraordinary', 'neutral'], ['matcha ( powdered green tea ) and blueberry cheesecake', 'phenomenal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Maybe it was the great company ( I had friends visiting from Philly \u2013 yes , it was not a date this time ) or the super reasonable price point , but I just can \u2019 t say enough good things about this brasserie ."], "output": "[['brasserie', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service leaves much to be desired , from feeling like you are rushed the place your order , to being ignored the rest of the night ."], "output": "[['service', 'leaves much to be desired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They are extremely rude , not even apologizing for the horrible service we got and handing us a bill well over $ 500 for some drinks adn their pita bread !"], "output": "[['service', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Shabu Shabu"], "output": "[['Shabu Shabu', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I tried a couple other dishes but was n't too impressed ."], "output": "[['dishes', \"was n't too impressed\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The meat is fresh , the sauces are great , you get kimchi and a salad free with your meal and service is good too ."], "output": "[['meat', 'fresh', 'positive'], ['sauces', 'great', 'positive'], ['service', 'good', 'positive'], ['kimchi', 'free', 'positive'], ['salad', 'free', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Dokebi gives Williamsburg the right one-two punch of classic Korean food and fusion twists like pork belly tacos ."], "output": "[['Korean food', 'classic', 'positive'], ['fusion twists', 'classic', 'positive'], ['pork belly tacos', 'classic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hot dogs are good , yes , but the reason to get over here is the fantastic pork croquette sandwich , perfect on its supermarket squishy bun ."], "output": "[['hot dogs', 'good', 'positive'], ['pork croquette sandwich', 'fantastic', 'positive'], ['bun', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food tasted very good ."], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The family seafood entree was very good ."], "output": "[['family seafood entree', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The main entree was also very good ."], "output": "[['main entree', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Price is high but the food is good , so I would come back again ."], "output": "[['food', 'good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place has totally weird decor , stairs going up with mirrored walls - I am surprised how no one yet broke their head or fall off the stairs - mirrored walls make you dizzy and delusional ..."], "output": "[['decor', 'weird', 'negative'], ['mirrored walls', 'dizzy', 'negative'], ['mirrored walls', 'delusional', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place is not inviting and the food is totally weird ."], "output": "[['place', 'not inviting', 'negative'], ['food', 'weird', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The concept of japanese tapas is newly created and clearly does n't work ."], "output": "[['japanese tapas', \"does n't work\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food they serve is not comforting , not appetizing and uncooked ."], "output": "[['food', 'not comforting', 'negative'], ['food', 'not appetizing', 'negative'], ['food', 'uncooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good Food"], "output": "[['Food', 'Good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was great and tasty , but the sitting space was too small , I do n't like being cramp in a corner ."], "output": "[['food', 'great', 'positive'], ['food', 'tasty', 'positive'], ['sitting space', 'too small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Over all it was a very nice romantic place ."], "output": "[['place', 'nice romantic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A coworker and I tried Pacifico after work a few Fridays and loved it ."], "output": "[['Pacifico', 'loved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere was great ."], "output": "[['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food we ordered was excellent , although I would n't say the margaritas were anything to write home about ."], "output": "[['food', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our waitress was n't mean , but not especially warm or attentive either ."], "output": "[['waitress', \"was n't mean\", 'neutral'], ['waitress', 'not especially warm or attentive', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I must say I am surprised by the bad reviews of the restaurant earlier in the year , though ."], "output": "[['restaurant', 'bad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The servers at Flatbush Farm appear to have perfected that ghastly technique of making you feel guilty and ashamed for deigning to attract their attention ."], "output": "[['servers', 'perfected', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A different server enhanced the fun , dumping our entrees in front of us halfway through our appetizer ( which was delicious ) ."], "output": "[['server', 'enhanced', 'negative'], ['appetizer', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Overall the food quality was pretty good , though I hear the salmon is much better when it has n't sat cooling in front of the guest ."], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place has a nice fit-out , some attractive furnishings and , from what I could tell , a reasonable wine list ( I was given the food menu when I asked for the carte des vins )"], "output": "[['fit-out', 'nice', 'positive'], ['furnishings', 'attractive', 'positive'], ['wine list', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything was going good until we got our meals ."], "output": "[['meals', 'good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I took one look at the chicken and I was appalled ."], "output": "[['chicken', 'appalled', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was served with skin , over a bed of extremely undercooked spinach and mashed potatoes ."], "output": "[['spinach', 'undercooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I took one bite from the $ 24 salmon , and I have never , in the 17 years I have been going to restaurants tasted salmon as fishy , as dry , and as bland as the one in Flatbush Farms ."], "output": "[['salmon', 'fishy', 'negative'], ['salmon', 'dry', 'negative'], ['salmon', 'bland', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is where it really really gets bad : the manager said , there is absolutely nothing we can do , it 's a matter of taste that she did n't like it , and I can not comp it ."], "output": "[['manager', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The manager came to the table and said we can do what we want , so we paid for what we did enjoy , the drinks and appetizers , and walked out ."], "output": "[['drinks', 'enjoy', 'positive'], ['appetizers', 'enjoy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["THIS STAFF SHOULD BE FIRED ."], "output": "[['STAFF', 'FIRED', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["cirspy crust margherita pizza"], "output": "[['margherita pizza', 'cirspy crust', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it was really good pizza ."], "output": "[['pizza', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the crust was imazingly cooked well and pizza was fully loaded : ) : ) : )"], "output": "[['crust', 'cooked well', 'positive'], ['pizza', 'fully loaded', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Single Worst Restaurant in Manhattan"], "output": "[['Restaurant', 'Worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 'll being with a couple of positives : cool decor , good pita and hummus , and grilled octopus that was actually pretty tasty ."], "output": "[['decor', 'cool', 'positive'], ['pita', 'good', 'positive'], ['hummus', 'good', 'positive'], ['grilled octopus', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is quite a spectacular scene i 'll give them that ."], "output": "[['scene', 'spectacular', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The decor however seems to be the distraction so you wo n't notice that you just payed 300 bucks for some cold eggplant that took 2 FRICKIN HOURS TO COME ! ! ! !"], "output": "[['decor', 'distraction', 'neutral'], ['eggplant', 'cold', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Hot Dogs !"], "output": "[['Hot Dogs', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hot dogs are top notch , and they 're Slamwich is amazing !"], "output": "[['hot dogs', 'top notch', 'positive'], ['Slamwich', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Going to Bark is always worth the train ride , and will make your tongue and belly very happy !"], "output": "[['Bark', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But nonetheless -- great spot , great food ."], "output": "[['spot', 'great', 'positive'], ['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fabulous food - if the front of house staff do n't put you off \u2013"], "output": "[['food', 'Fabulous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Each time we 've been , the front of house staff ( not the waiters - they 're fantastic - but the people who greet and seat you ) has been so hideous to us that were it not for the exceptional fish dishes I would never return ."], "output": "[['waiters', 'fantastic', 'positive'], ['front of house staff', 'hideous', 'negative'], ['fish dishes', 'exceptional', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["As BFC does n't take reservations you almost always have to wait by the bar - and be abused by the front of house staff until you are seated , which can be over an hour later !"], "output": "[['front of house staff', 'abused', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The frizzy retro girl ( with winged/ Dame Edna glasses ) will yell at you if you try to order a drink ."], "output": "[['girl', 'frizzy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 'd be horrified if my staff were turning away customers so early and so rudely !"], "output": "[['staff', 'horrified', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There 's another girl who I ca n't describe , she is about 5'6 '' with brown hair , who eavesdrops on your conversation and chimes in - except she only hears the last part of what you said , so her uninvited opinions are often out of context and nothing to do with what you 're *really* talking about ."], "output": "[['girl', 'uninvited', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Considering you will spend at least $ 60 a head , I expect better service ."], "output": "[['service', 'expect better', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food and service were fine , however the maitre-D was incredibly unwelcoming and arrogant ."], "output": "[['food', 'fine', 'positive'], ['service', 'fine', 'positive'], ['maitre-D', 'unwelcoming', 'negative'], ['maitre-D', 'arrogant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While finishing our meals which included a high-end bottle of wine , our son 's fiance joined us for a glass of wine and dessert ."], "output": "[['bottle of wine', 'high-end', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This guy refused to seat her and she left , followed shortly by the four of us , but not before I told him that in my 40 years of world travel , including Paris , that I had never seen such a display of bad behavior by a frontman in a restaurant ."], "output": "[['frontman', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best meal in a long time !"], "output": "[['meal', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mussles and calamari were superb Saturday evening ."], "output": "[['Mussles', 'superb', 'positive'], ['calamari', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had the Lamb special which was perfect ."], "output": "[['Lamb special', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My father had the flank steak which was very good , and my mother had the swordfish ."], "output": "[['flank steak', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Four Seasons restaurant is a great experience ."], "output": "[['The Four Seasons restaurant', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great and the environment is even better ."], "output": "[['food', 'great', 'positive'], ['environment', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Here the hot dog is elevated to the level of a real entree with numerous variations available ."], "output": "[['hot dog', 'elevated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Atmosphere"], "output": "[['Atmosphere', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I highly recommend the fish tacos , everything else was ok ."], "output": "[['fish tacos', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cool atmosphere , the fire place in the back really ads to it but needs a bit more heat throughout on a cold night ."], "output": "[['atmosphere', 'Cool', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Poor service and management"], "output": "[['service', 'Poor', 'negative'], ['management', 'Poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Had an awful experience at Casa la Femme on a Saturday dinner ."], "output": "[['Casa la Femme', 'awful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The manager was rude and handled the situation extremely poorly ."], "output": "[['manager', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Can \u2019 t believe how an expensive NYC restaurant can be so disrespectful to its clients ."], "output": "[['restaurant', 'expensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is very good , but not outstanding ."], "output": "[['food', 'good', 'neutral'], ['food', 'not outstanding', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bread was stale , the salad was overpriced and empty ."], "output": "[['bread', 'stale', 'negative'], ['salad', 'overpriced', 'negative'], ['salad', 'empty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pasta was well cooked , did n't have enough sauce though or flavor ."], "output": "[['pasta', 'well cooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hostess was rude and I got a distinct feeling that they did not want to serve us ."], "output": "[['hostess', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only thing that my friend left out is that when we sat down at the bar the bartender disappeared ."], "output": "[['bartender', 'disappeared', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Shame on this place for the horrible rude staff and non-existent customer service ."], "output": "[['staff', 'rude', 'negative'], ['customer service', 'non-existent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["bad staff"], "output": "[['staff', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I generally like this place ."], "output": "[['place', 'like', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is good ."], "output": "[['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The design of the space is good ."], "output": "[['space', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the service is HORRID !"], "output": "[['service', 'HORRID', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Serves really good sushi ."], "output": "[['sushi', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not the biggest portions but adequate ."], "output": "[['portions', 'Not the biggest', 'neutral'], ['portions', 'adequate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Green Tea creme brulee is a must !"], "output": "[['Green Tea creme brulee', 'must', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It has great sushi and even better service ."], "output": "[['sushi', 'great', 'positive'], ['service', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The entire staff was extremely accomodating and tended to my every need ."], "output": "[['staff', 'accomodating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The owner is belligerent to guests that have a complaint ."], "output": "[['owner', 'belligerent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good food !"], "output": "[['food', 'Good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is a great place to get a delicious meal ."], "output": "[['meal', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff is pretty friendly ."], "output": "[['staff', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The onion rings are great !"], "output": "[['onion rings', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lemon chicken tasted like sticky sweet donuts and the honey walnut prawns , the few they actually give you ... ..were not good ."], "output": "[['lemon chicken', 'sticky sweet', 'negative'], ['honey walnut prawns', 'not good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nice ambience , but highly overrated place ."], "output": "[['ambience', 'Nice', 'positive'], ['place', 'overrated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Worst Service I Ever Had"], "output": "[['Service', 'Worst', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everyone that sat in the back outside agreed that it was the worst service we had ever received ."], "output": "[['service', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our waiter was non-existent and after our food finally arrived over an hour after we ordered , we were not given any water or utensils ."], "output": "[['waiter', 'non-existent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I complained to the manager , but he was not even apologetic ."], "output": "[['manager', 'not even apologetic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fabulous Italian Food !"], "output": "[['Italian Food', 'Fabulous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I highly recommend Mioposto ."], "output": "[['Mioposto', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I am so happy to have a wonderful Italian restaurant in my neighborhood ."], "output": "[['Italian restaurant', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine list is wonderful and the food reminds me of my recent trip to Italy ."], "output": "[['wine list', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love this restaurant"], "output": "[['restaurant', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I will never forget the amazing meal , service , and ambiance I experience at this restaurant ."], "output": "[['meal', 'amazing', 'positive'], ['service', 'amazing', 'positive'], ['ambiance', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine list is incredible and extensive and diverse , the food is all incredible and the staff was all very nice , good at their jobs and cultured ."], "output": "[['wine list', 'incredible', 'positive'], ['wine list', 'extensive', 'positive'], ['wine list', 'diverse', 'positive'], ['food', 'incredible', 'positive'], ['staff', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was great !"], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 In a age of incremental cost cutting in restaurants , its nice to see a place that bucks that trend , and just plain delivers high quality food and good service , period ."], "output": "[['food', 'high quality', 'positive'], ['service', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This is the place to relax and enjoy the finest quality food the industry can offer ."], "output": "[['place', 'relax', 'positive'], ['food', 'finest quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Caution - its real food for people who love the best ."], "output": "[['food', 'real', 'positive'], ['food', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I liked the atmosphere very much but the food was not worth the price ."], "output": "[['atmosphere', 'liked', 'positive'], ['food', 'not worth the price', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I may not be a sushi guru but I can tell you that the food here is just okay and that there is not much else to it ."], "output": "[['food', 'okay', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Rice is too dry , tuna was n't so fresh either ."], "output": "[['Rice', 'too dry', 'negative'], ['tuna', \"was n't so fresh\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have eaten here three times and have found the quality and variety of the fish to be excellent ."], "output": "[['fish', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , the value and service are both severely lacking ."], "output": "[['service', 'lacking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Furthermore , while the fish is unquestionably fresh , rolls tend to be inexplicably bland ."], "output": "[['fish', 'fresh', 'positive'], ['rolls', 'bland', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service ranges from mediocre to offensive ."], "output": "[['service', 'mediocre', 'negative'], ['service', 'offensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["On a recent trip , our waiter was extremely dismissive , while no less than three staff members waited hand-and-foot on a pair of Japanese girls seated nearby ."], "output": "[['waiter', 'dismissive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Freshest sushi \u2013 I love this restaurant ."], "output": "[['sushi', 'Freshest', 'positive'], ['restaurant', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They pay such detail to everything from miso soup to complex rolls ."], "output": "[['rolls', 'complex', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sashimi was the freshest and most tender I have ever tasted ."], "output": "[['sashimi', 'freshest', 'positive'], ['sashimi', 'tender', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Their apps are all delicious ."], "output": "[['apps', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only drawback is that this place is really expensive and the portions are on the small side ."], "output": "[['place', 'expensive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the space is small and lovely , and the service is helpful ."], "output": "[['space', 'small', 'positive'], ['space', 'lovely', 'positive'], ['service', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 The food was not great & the waiters were rude ."], "output": "[['food', 'not great', 'negative'], ['waiters', 'rude', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great service"], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["my service was stellar !"], "output": "[['service', 'stellar', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["food was fine , with a some little-tastier-than-normal salsa ."], "output": "[['food', 'fine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the food was great , the margaritas too but the waitress was too busy being nice to her other larger party than to take better care of my friend and me ."], "output": "[['food', 'great', 'positive'], ['margaritas', 'great', 'positive'], ['waitress', 'too busy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mama Mia \u2013 I live in the neighborhood and feel lucky to live by such a great pizza place ."], "output": "[['pizza place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Sushi in town ."], "output": "[['Sushi', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The best calamari in Seattle !"], "output": "[['calamari', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 ... and the best summertime deck experience -- they will even bring you a blanket if you get cold in the Seattle evening weather ."], "output": "[['deck', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["A perfect place to take out of town guests any time of the year ."], "output": "[['place', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Endless fun , awesome music , great staff ! ! !"], "output": "[['music', 'awesome', 'positive'], ['staff', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 By far the best bar in the east village ..."], "output": "[['bar', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great draft and bottle selection and the pizza rocks ."], "output": "[['draft and bottle selection', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Definitely has one of the best jukebox 's i 've seen in a long long time ."], "output": "[[\"jukebox 's\", 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great , the bartenders go that extra mile ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The owners are great fun and the beer selection is worth staying for ."], "output": "[['owners', 'great', 'positive'], ['beer selection', 'worth staying for', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And the upstairs is a great place to hang out ."], "output": "[['upstairs', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not alot of smoking places left in New York , but I have found my favorite smoking balconey in the city ."], "output": "[['balconey', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi here is delicious !"], "output": "[['sushi', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They have a wide variety of fish and they even list which oceans they come from ; Atlantic or Pacific ."], "output": "[['fish', 'wide variety', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had the Jellyfish , Horse Mackerel , Blue Fin Tuna and the Sake Ikura roll among others , and they were all good ."], "output": "[['Jellyfish', 'good', 'positive'], ['Horse Mackerel', 'good', 'positive'], ['Blue Fin Tuna', 'good', 'positive'], ['Sake Ikura roll', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The decor is rustic , traditional Japanese ."], "output": "[['decor', 'rustic', 'neutral'], ['decor', 'traditional Japanese', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was courteous and attentive ."], "output": "[['service', 'courteous', 'positive'], ['service', 'attentive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mediocre food"], "output": "[['food', 'Mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The outside patio area has an abbreviated menu ."], "output": "[['menu', 'abbreviated', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My g/f and I both agreed the food was very mediocre especially considering the price ."], "output": "[['food', 'mediocre', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We are locals , and get the feeling the only way this place survives with such average food is because most customers are probably one-time customer tourists ."], "output": "[['food', 'average', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was decent ."], "output": "[['Service', 'decent', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Drinks were good ."], "output": "[['Drinks', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Excellent food , nice ambience , fairly expensive"], "output": "[['food', 'Excellent', 'positive'], ['ambience', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I loved the pumpkin ravioli and the goat cheese gnocchi ( 5 big ones to a plate instead of 20 or so little gnocchis ) and my sister loved her filet mignon on top of spinach and mashed potatoes ."], "output": "[['pumpkin ravioli', 'loved', 'positive'], ['goat cheese gnocchi', 'loved', 'positive'], ['filet mignon on top of spinach and mashed potatoes', 'loved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The ambiance was a peaceful and relaxing break amongst all the kids running around in Downtown Disney ."], "output": "[['ambiance', 'peaceful', 'positive'], ['ambiance', 'relaxing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Indian food in L.A ."], "output": "[['Indian food', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chicken curry and chicken tikka masala are my favorite meat dishes ."], "output": "[['chicken curry', 'favorite', 'positive'], ['chicken tikka masala', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The chana masala ( garbanzo beans ) are also excellent ."], "output": "[['chana masala ( garbanzo beans )', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's located in a strip mall near the Beverly Center , not the greatest location , but the food keeps me coming back for more ."], "output": "[['location', 'not the greatest', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Never too crowded and always great service ."], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I can highly recommend their various saag and paneer and korma ."], "output": "[['saag', 'recommend', 'positive'], ['paneer', 'recommend', 'positive'], ['korma', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I appreciate their delivery too ."], "output": "[['delivery', 'appreciate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nice food but no spice !"], "output": "[['food', 'Nice', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I really enjoyed my meal here ."], "output": "[['meal', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had yummy lamb korma , saag paneer , samosas , naan , etc ."], "output": "[['lamb korma', 'yummy', 'positive'], ['saag paneer', 'yummy', 'positive'], ['samosas', 'yummy', 'positive'], ['naan', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was all good but it was way too mild ."], "output": "[['food', 'good', 'negative'], ['food', 'too mild', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The naan was some of the best I 've had and I really enjoyed the bhartha , not too tomatoey ."], "output": "[['naan', 'best', 'positive'], ['bhartha', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Even the chickpeas , which I normally find too dry , were good ."], "output": "[['chickpeas', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I do n't understand how I was a stranger to this place for so long ... the fajita salad , the colorado , the fajitas - EVERYTHING is delicious ."], "output": "[['fajita salad', 'delicious', 'positive'], ['colorado', 'delicious', 'positive'], ['fajitas', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love the warm & cosy environment ."], "output": "[['environment', 'warm', 'positive'], ['environment', 'cosy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["best restaurant in the world , great decor , great customer service , friendly manager"], "output": "[['restaurant', 'best', 'positive'], ['decor', 'great', 'positive'], ['customer service', 'great', 'positive'], ['manager', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i am never disappointed with there food ."], "output": "[['food', 'never disappointed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the atmosphere is great ."], "output": "[['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great lunch spot"], "output": "[['lunch spot', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Great financial district mexican spot ."], "output": "[['mexican spot', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Always busy , but they are good at seating you promptly and have quick service ."], "output": "[['service', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything I 've had here is good , taco salads , burritos , enchiladas i love this place ."], "output": "[['taco salads', 'good', 'positive'], ['burritos', 'good', 'positive'], ['enchiladas', 'good', 'positive'], ['place', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also have great margaritas !"], "output": "[['margaritas', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is simply unforgettable !"], "output": "[['food', 'unforgettable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff are friendly and the decor was ethic and colorful ."], "output": "[['staff', 'friendly', 'positive'], ['decor', 'ethic', 'positive'], ['decor', 'colorful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Holy Hummus !"], "output": "[['Hummus', 'Holy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 The food is here is incredible , though the quality is inconsistent during lunch ."], "output": "[['food', 'incredible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Dinners have always been excellent , in terms of food quality ."], "output": "[['Dinners', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The side of potatoes is to die for , as is the labne ( yogurt dip ) ."], "output": "[['side of potatoes', 'die for', 'positive'], ['labne ( yogurt dip )', 'side of potatoes', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also , they serve THE best hummus in America , with a drizzle of fragrant olive oil ( which , I believe is the traditional way ) !"], "output": "[['hummus', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only drawback is the crowded seating and the slow service ."], "output": "[['seating', 'crowded', 'negative'], ['service', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , this place is a gem , and I wo n't stop going back ."], "output": "[['place', 'gem', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great beer"], "output": "[['beer', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I swore never to return for a warm beer and mediocre meal ."], "output": "[['beer', 'warm', 'negative'], ['meal', 'mediocre', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The band was very good and the service was attentive ."], "output": "[['band', 'good', 'positive'], ['service', 'attentive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We ordered a selection of the small plates , and the shoe string onions , goat cheese pizza , grilled asparagus and fried brie with fruit were all very good ."], "output": "[['shoe string onions', 'good', 'positive'], ['goat cheese pizza', 'good', 'positive'], ['grilled asparagus', 'good', 'positive'], ['fried brie with fruit', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Seattle 's BEST Winelist"], "output": "[['Winelist', 'BEST', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sommelier is fantastic , down-to-earth , & extremely knowlegable ."], "output": "[['sommelier', 'fantastic', 'positive'], ['sommelier', 'down-to-earth', 'positive'], ['sommelier', 'knowlegable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is not what it once was ( potions have seriously seen downsizing ) prices have gone up , and the service is the worst I have experienced anywhere ( including mainland Europe ) ."], "output": "[['service', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Open & Cool Place with the Best Pizza and Coffee"], "output": "[['Place', 'Cool', 'positive'], ['Pizza', 'Best', 'positive'], ['Coffee', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Mioposto has a very creative & delicious pizza menu ."], "output": "[['pizza menu', 'creative', 'positive'], ['pizza menu', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The coffe is very good , too ."], "output": "[['coffe', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great open and friendly ambience ."], "output": "[['ambience', 'Great open', 'positive'], ['ambience', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place is charming and relaxing ."], "output": "[['place', 'charming', 'positive'], ['place', 'relaxing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The servers behind the counter are always friendly and helpful ."], "output": "[['servers behind the counter', 'friendly', 'positive'], ['servers behind the counter', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a great place to enjoy food and meet friends ."], "output": "[['food', 'enjoy', 'positive'], ['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , spectacular location , and friendly service keep us coming back year after year ."], "output": "[['food', 'Great', 'positive'], ['location', 'spectacular', 'positive'], ['service', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Enjoyed the food"], "output": "[['food', 'Enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food was good and cheap ."], "output": "[['Food', 'good', 'positive'], ['Food', 'cheap', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had the kafta plate and I enjoyed it ."], "output": "[['kafta plate', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Atmosphere was nice ."], "output": "[['Atmosphere', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Service was kind of slow , our waitress took forever to give us our check even though it was n't that busy ."], "output": "[['Service', 'slow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Still I would recommend this place ."], "output": "[['place', 'recommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["WHAT ELSE CAN YOU SAY NICE PEOPLE AMAZING FOOD WOW"], "output": "[['FOOD', 'AMAZING', 'positive'], ['PEOPLE', 'NICE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food with an awesome atmosphere !"], "output": "[['food', 'Great', 'positive'], ['atmosphere', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Eggs , pancakes , potatoes , fresh fruit and yogurt -- everything they serve is delicious ."], "output": "[['Eggs', 'delicious', 'positive'], ['pancakes', 'delicious', 'positive'], ['potatoes', 'delicious', 'positive'], ['fresh fruit', 'delicious', 'positive'], ['yogurt', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great meal \u2013 the fish on the omikase platter was absolutely decadent -- there was none of the stringiness that sometimes accompanies fair sushi -- this fish was perfect ! ! ! !"], "output": "[['meal', 'great', 'positive'], ['fish on the omikase platter', 'decadent', 'positive'], ['fish on the omikase platter', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["plus , i am allergic to rice , and the waitstaff was unbelievably accomodating -- did n't even bat an eye !"], "output": "[['waitstaff', 'accomodating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["and the waiter suggested a perfect sake ! !"], "output": "[['sake', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Unbeatable sushi !"], "output": "[['sushi', 'Unbeatable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Melt in your mouth nigiri and sashmi , and very tasty rolls too ."], "output": "[['rolls', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Be sure to try the oyster roll ."], "output": "[['oyster roll', 'try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 How to describe the best sushi in NYC : hmmmm , delicious , amazing , fantastic , suculent , perfect , nah , all of the above ."], "output": "[['sushi', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The best Chuwam Mushi I have ever had ."], "output": "[['Chuwam Mushi', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good Sushi , High Price"], "output": "[['Sushi', 'Good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["One of the best Sushi place in town ."], "output": "[['Sushi place', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The house special roll is really good ."], "output": "[['house special roll', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I ca n't believe Murphy 's has been around for over 25 years , amazing ."], "output": "[[\"Murphy 's\", 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Brunch at Murphy 's is to die for , my specialty ... egg white omelet , the food is always freshly prepared ."], "output": "[['food', 'freshly prepared', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's the perfect spot for a romantic date for 2 or a secret rendezvous !"], "output": "[['spot', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Save room for scrumptious desserts ."], "output": "[['desserts', 'scrumptious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The restaurant offers an extensive wine list and an ambiance you wo n't forget !"], "output": "[['wine list', 'extensive', 'positive'], ['ambiance', \"wo n't forget\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Best Mexican place for lunch in the financial district ."], "output": "[['Mexican place', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Love the enchiladas and chicken soup - and be sure to check out their specials ."], "output": "[['enchiladas', 'Love', 'positive'], ['chicken soup', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Can get busy on Fridays for a table but once seated , the service is so efficient you can be in and out of there quickly ."], "output": "[['service', 'efficient', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi was excellent and the wait staff was quick ."], "output": "[['sushi', 'excellent', 'positive'], ['wait staff', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere was just okay ."], "output": "[['atmosphere', 'okay', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Space was limited , but the food made up for it ."], "output": "[['Space', 'limited', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We stood there for 10 minutes while employees walked back and forth ignoring us ."], "output": "[['employees', 'ignoring', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Caesar salad I ordered had so much lemon I could n't eat it ."], "output": "[['Caesar salad', \"could n't eat\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , better Margaritas !"], "output": "[['food', 'Great', 'positive'], ['Margaritas', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 This is one of my top lunch spots , huge portions , fast service and amazing margaritas ! !"], "output": "[['portions', 'huge', 'positive'], ['service', 'fast', 'positive'], ['margaritas', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["it gets really busy , so get there on the early side so you can grab a seat , if you do have to wait , its not bad because the service is quick !"], "output": "[['service', 'quick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Check out the art on the walls , very colorful !"], "output": "[['art on the walls', 'colorful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i love this place !"], "output": "[['place', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 i have been eating at this place for over 8 years now and i have never had one bad meal ."], "output": "[['meal', 'bad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lunch menu is an awesome deal !"], "output": "[['lunch menu', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["plenty of food , trust me ."], "output": "[['food', 'plenty of', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fresh ingrediants and super tasty ."], "output": "[['ingrediants', 'Fresh', 'positive'], ['ingrediants', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best food , phenominal service"], "output": "[['food', 'Best', 'positive'], ['service', 'phenominal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For the finicky sushi eater and those who have sampled the best NYC has to offer , the fish is the freshest and the service is superb ."], "output": "[['fish', 'freshest', 'positive'], ['service', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not only can the selection be innovative , but there 's a nice balance of traditional sushi as well ."], "output": "[['selection', 'innovative', 'positive'], ['sushi', 'nice', 'positive'], ['sushi', 'traditional', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The nicest waiters in town ."], "output": "[['waiters', 'nicest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 This place is unbelievably over-rated ."], "output": "[['place', 'over-rated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If I want to stand in line on Sunday for an hour to get average brunch food , then I would put Murphy 's at the top of the list ."], "output": "[['brunch food', 'average', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The regular menu here is slightly above average that is not worth the snotty attitude that you receive ."], "output": "[['regular menu', 'above average', 'neutral'], ['regular menu', 'not worth the snotty attitude', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Your a sushi fan , you love expertly cut fish , great sake , a killer SOHO location , and of course : Salmon , Tuna , Fluke , Yellow Tail , Cod , Mackeral , Jellyfish , Sea Urchin , Shrimp , Lobster , Sea Bream , Trout , Milk Fish , Blue Fin Tuna , Eel , Crab , Sardine , Monk Fish , Roe , Scallop , Oysters , and a varity of Toro ."], "output": "[['fish', 'love expertly cut', 'positive'], ['sake', 'great', 'positive'], ['SOHO location', 'killer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Bring your cell phone cause you may have to wait to get into the best sushi restaurant in the world : BLUE RIBBON SUSHI ."], "output": "[['BLUE RIBBON SUSHI', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Hands down , the best tuna I have ever had ."], "output": "[['tuna', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Blue Ribbon lives up to it 's fantastic reputation ."], "output": "[['Blue Ribbon', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great value sushi with high quality & nice setting ."], "output": "[['sushi', 'Great value', 'positive'], ['sushi', 'high quality', 'positive'], ['sushi', 'nice setting', 'positive'], ['setting', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the Chef 's Choice for sushi as the smoked yellowtail was incredible and the rolls were also tasty ."], "output": "[['rolls', 'tasty', 'positive'], ['smoked yellowtail', 'incredible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Poor customer service / poor pizza ."], "output": "[['customer service', 'Poor', 'negative'], ['pizza', 'Poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 As with most restaurants in Seattle , Mioposto 's service was bad and the food was overpriced ."], "output": "[['service', 'bad', 'negative'], ['food', 'overpriced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I know many people have their favorite types of pizza and pizza places , but Mioposto 's pizza lacks quality and good taste ."], "output": "[['pizza', 'lacks quality and good taste', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["To be honest , I 've had better frozen pizza ."], "output": "[['pizza', 'better', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only positive thing about Mioposto is the nice location ."], "output": "[['location', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I was frankly shocked when I read the bad reviews - this place is fantastic ; it has not let us down in any way , and we 've eaten here more than 10 times ."], "output": "[['place', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is fantastic , and the waiting staff has been perfect every single time we 've been there ."], "output": "[['food', 'fantastic', 'positive'], ['waiting staff', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Seabass on lobster risotto was the best ."], "output": "[['Seabass on lobster risotto', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Caesar salad was superb ."], "output": "[['Caesar salad', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great bottle of wine ."], "output": "[['bottle of wine', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was ok , but the service was so poor that the food was cold buy the time everyone in my party was served ."], "output": "[['food', 'ok', 'neutral'], ['service', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["AVOID THE PLACE"], "output": "[['PLACE', 'AVOID', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["When I got there I sat up stairs where the atmosphere was cozy & the service was horrible !"], "output": "[['atmosphere', 'cozy', 'positive'], ['service', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We left without ever getting service ."], "output": "[['service', 'without ever', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Crab Cakes in Town"], "output": "[['Crab Cakes', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great seasonal fish and seafood , with a classy waterfront setting ."], "output": "[['seasonal fish', 'Great', 'positive'], ['seafood', 'Great', 'positive'], ['waterfront setting', 'classy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Pizza , Poor Service"], "output": "[['Pizza', 'Great', 'positive'], ['Service', 'Poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Love their pizza , especially the mushroom pizza ."], "output": "[['pizza', 'Love', 'positive'], ['mushroom pizza', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Also love their caeser salad ."], "output": "[['caeser salad', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Prefer to order it and pick it up though because I do n't like the servers , one young woman in particular ."], "output": "[['servers', \"do n't like\", 'negative'], ['young woman', \"do n't like\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Many people talk about the great pizza and poor service , so it ca n't just be the rantings of a few dissatisfied customers ."], "output": "[['pizza', 'great', 'positive'], ['service', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a great little place with tons of potential to be a neighborhood joint if the service were n't so impersonal and corporate-like ."], "output": "[['place', 'great little', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Breakfast"], "output": "[['Breakfast', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is great and they make a mean bloody mary ."], "output": "[['food', 'great', 'positive'], ['bloody mary', 'mean', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love breakfast here ."], "output": "[['breakfast', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Their crab eggs benedict is addicting ."], "output": "[['crab eggs benedict', 'addicting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["All their menu items are a hit , and they serve mimosas ."], "output": "[['menu items', 'hit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["best chinese food i have tasted in a long time"], "output": "[['chinese food', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the ambiance of the restaurant was nice and good for fine dinning ."], "output": "[['ambiance', 'nice', 'positive'], ['ambiance', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the staff was very nice and courteous and obviously chinese ."], "output": "[['staff', 'nice', 'positive'], ['staff', 'courteous', 'positive'], ['staff', 'chinese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["so about the prawns , they were fresh and had a slight crispiness about the batter ... soooo good ... the walnuts were cut in smaller pieces and very crunchy and tasty ."], "output": "[['prawns', 'fresh', 'positive'], ['batter', 'crispiness', 'positive'], ['walnuts', 'crunchy', 'positive'], ['walnuts', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["best honey walnyt prawns that we have every tasted ."], "output": "[['honey walnyt prawns', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the brocollis were so fresh and tasty ."], "output": "[['brocollis', 'fresh', 'positive'], ['brocollis', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["i would normally not finish the brocolli when i order these kinds of food but for the first time , every piece was as eventful as the first one ... the scallops and prawns was so fresh and nicely cooked ."], "output": "[['scallops', 'fresh', 'positive'], ['scallops', 'nicely cooked', 'positive'], ['prawns', 'fresh', 'positive'], ['prawns', 'nicely cooked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Chintzy portions"], "output": "[['portions', 'Chintzy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 The sushi here is perfectly good , but for $ 5 a piece , either the slices of fish should be larger , or there should be no pretense that this is a moderately priced restaurant ( even for NYC ) ."], "output": "[['sushi', 'good', 'negative'], ['restaurant', 'moderately priced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Terrible service , food ok , pricey"], "output": "[['service', 'Terrible', 'negative'], ['food', 'ok', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food wise , its ok but a bit pricey for what you get considering the restaurant is n't a fancy place ."], "output": "[['Food', 'ok', 'neutral'], ['Food', 'pricey', 'neutral'], ['restaurant', \"is n't a fancy\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Another plus is the open feel of the restaurant with glass walls on all sides ."], "output": "[['feel', 'plus', 'positive'], ['feel', 'open', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Amazing Spanish Mackeral special appetizer and perfect box sushi ( that eel with avodcao -- um um um ) ."], "output": "[['Spanish Mackeral special appetizer', 'Amazing', 'positive'], ['box sushi', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["As usual the omikase did n't disappoint in freshness , although it scored low on creativity and selection ."], "output": "[['omikase', \"did n't disappoint\", 'negative'], ['omikase', 'scored low on creativity and selection', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Their specialty rolls are impressive , though I ca n't remember what we had ."], "output": "[['specialty rolls', 'impressive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great selection of sakes ."], "output": "[['selection of sakes', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is n't the cheapest sushi but has been worth it every time ."], "output": "[['sushi', \"is n't the cheapest\", 'positive'], ['sushi', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Very poor customer service ."], "output": "[['customer service', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Schooner or Later 's charming location along the marina in Long Beach and average food does not , unfortunately , compensate for its very poor customer service ."], "output": "[['customer service', 'poor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While this diner had reasonably good food , the restaurant staff seemed completely indifferent to our presence , and this attitude was reflected in the lack of service ."], "output": "[['food', 'good', 'positive'], ['restaurant staff', 'indifferent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the fish was fresh , though it was cut very thin ."], "output": "[['fish', 'fresh', 'negative'], ['fish', 'thin', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["great service ."], "output": "[['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["good sake selection ."], "output": "[['sake selection', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Ray 's is THE place to go for high quality seafood dinners ."], "output": "[['seafood dinners', 'high quality', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I love Dungeness crabs and at Ray 's you can get them served in about 6 different ways !"], "output": "[['Dungeness crabs', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We shared the family platter and I especially enjoyed the black cod in sake kasu ."], "output": "[['black cod in sake kasu', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I ended the meal with the unusual dessert of a port and chocolate tasting ... yummy !"], "output": "[['dessert of a port and chocolate tasting', 'yummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["And the service was simply spendid - quite a delight ."], "output": "[['service', 'spendid', 'positive'], ['service', 'delight', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great Breakfast"], "output": "[['Breakfast', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Great drinks , corn beef hash , coffee , B Fast burritos , Gluten Free menu ."], "output": "[['drinks', 'Great', 'positive'], ['corn beef hash', 'Great', 'positive'], ['coffee', 'Great', 'positive'], ['B Fast burritos', 'Great', 'positive'], ['menu', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is fantastic at this fun place ."], "output": "[['service', 'fantastic', 'positive'], ['place', 'fun', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Best Neighborhood Standby ."], "output": "[['Standby', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In Grammercy/Union Square/East Village this is my neighbors and my favorite spot ."], "output": "[['spot', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The music is great , no night better or worse , the bar tenders are generous with the pouring , and the lighthearted atmosphere will lifts you spirits ."], "output": "[['music', 'great', 'positive'], ['bar tenders', 'generous', 'positive'], ['atmosphere', 'lighthearted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Oh , and the cheese fries are awesome !"], "output": "[['cheese fries', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good Food , Great Service , Average Prices ( For the Strip )"], "output": "[['Food', 'Good', 'positive'], ['Service', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["When I walked in , I was taken aback by their incredible wood decor ."], "output": "[['wood decor', 'incredible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The music playing was very hip , 20-30 something pop music , but the subwoofer to the sound system was located under my seat , which became annoying midway through dinner ."], "output": "[['subwoofer to the sound system', 'annoying', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I got the shellfish and shrimp appetizer and it was alright ."], "output": "[['shellfish and shrimp appetizer', 'alright', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was n't the freshest seafood ever , but the taste and presentation was OK ."], "output": "[['seafood', \"was n't the freshest\", 'neutral'], ['seafood', 'OK', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I picked the asparagus , which turned out to be incredible and perfectly prepared ."], "output": "[['asparagus', 'incredible', 'positive'], ['asparagus', 'perfectly prepared', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The steak was done to my exact liking ( medium rare ) and was nice and juicy ."], "output": "[['steak', 'nice', 'positive'], ['steak', 'juicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It ? s served with either a peppercorn sauce or red wine reduction , though both were indistinguishable in taste ."], "output": "[['peppercorn sauce', 'indistinguishable', 'neutral'], ['red wine reduction', 'indistinguishable', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The desert was the perfect ending to an almost perfect dinner ."], "output": "[['desert', 'perfect', 'positive'], ['dinner', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the servers were extremely attentive and very friendly ."], "output": "[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["good sake , good food \u2013 i honestly do n't know much about japanese food at all ."], "output": "[['sake', 'good', 'positive'], ['food', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Server made several sake suggestions which were very good ."], "output": "[['sake', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["had many dishes but the BEST was the lobster 3 ways ."], "output": "[['lobster 3 ways', 'BEST', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiter was a bit unfriendly and the feel of the restaurant was crowded ."], "output": "[['waiter', 'unfriendly', 'negative'], ['feel', 'crowded', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Most importantly , we were so excited about the food after seeing the very creative menu ."], "output": "[['menu', 'creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["At best , the food was good and definately overpriced ."], "output": "[['food', 'good', 'negative'], ['food', 'overpriced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My favortie pizza joint in Seattle"], "output": "[['pizza joint', 'favortie', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pizza is delicious and the salads are fantastic ."], "output": "[['pizza', 'delicious', 'positive'], ['salads', 'fantastic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've always found the wait staff and , if you sit at the bar , the cooks very friendly ."], "output": "[['cooks', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I also really enjoy the simplicity of the decor and intimate feeling of a small restaurant ."], "output": "[['decor', 'enjoy', 'positive'], ['decor', 'simplicity', 'positive'], ['feeling', 'intimate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 My husband and I love eating at Mioposto Caf\u00e9 ."], "output": "[['Mioposto Caf\u00e9', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["You won \u2019 t be disappointed by their menu ."], "output": "[['menu', 'won \u2019 t be disappointed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pizza \u2019 s are thin crust and the menu offers very creative combinations and toppings ."], "output": "[['menu', 'creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Try the Pizza Ensalata !"], "output": "[['Pizza Ensalata', 'Try', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pizza \u2019 s are not huge and the crust is thin ... keep that in mind when you \u2019 re ordering ."], "output": "[['crust', 'thin', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is sinful ."], "output": "[['food', 'sinful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The staff was really friendly ."], "output": "[['staff', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere was great ."], "output": "[['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The specialty here is decadent pancakes , but I 've been back now four times , and I 've been wowed every time ."], "output": "[['pancakes', 'decadent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nothing on the menu is less than amazing ."], "output": "[['menu', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good eats ."], "output": "[['eats', 'Good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have been to this place , folks and it is BAD ."], "output": "[['place', 'BAD', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Maybe it is good for that one night once in a blue moon when the chefs decide to use fish that 's half-way decent ."], "output": "[['fish', 'decent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have been here , spent tons of money on a chef special dinner and it was a major dissappointment ."], "output": "[['chef special dinner', 'dissappointment', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 The atmosphere is great for any special occasion you might want to celebrate ."], "output": "[['atmosphere', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The best dish are the honwy walnut prawns -- just outstanding ."], "output": "[['honwy walnut prawns', 'best', 'positive'], ['honwy walnut prawns', 'outstanding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service is really attentive and charming ."], "output": "[['service', 'attentive', 'positive'], ['service', 'charming', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was excellent , the coffee was good even by starbucks standards and the food was outstanding ."], "output": "[['service', 'excellent', 'positive'], ['coffee', 'good', 'positive'], ['food', 'outstanding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I recently had the pleasure of dining as this delightful restaurant on 2nd street and wow what a great evening we had ."], "output": "[['restaurant', 'delightful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food is fantastic , authentic , delicious and very , very affordable ."], "output": "[['food', 'fantastic', 'positive'], ['food', 'authentic', 'positive'], ['food', 'delicious', 'positive'], ['food', 'affordable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The decor was beautiful and unique ."], "output": "[['decor', 'beautiful', 'positive'], ['decor', 'unique', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["There was a really nice vibe about the place ... good music , atmosphere and happy looking people ."], "output": "[['music', 'good', 'positive'], ['atmosphere', 'good', 'positive'], ['vibe', 'nice', 'positive'], ['people', 'happy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our server was very professional and friendly ."], "output": "[['server', 'professional', 'positive'], ['server', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a tiny place so if you get there before 8pm on a weekend ( Thurs ? Sun ) you will find it easier to get a table or a seat at the sushi bar ."], "output": "[['place', 'tiny', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything , and I mean everything on the menu is delectable ."], "output": "[['menu', 'delectable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waiters are very experienced and helpful with pairing your drink choice to your food tastes or vice versa ."], "output": "[['waiters', 'experienced', 'positive'], ['waiters', 'helpful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi is as fresh as it comes ? you 'd think ocean was in their backyard , no joke !"], "output": "[['sushi', 'fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["If you 're interested in good tasting ( without the fish taste or smell ) , large portions and creative sushi dishes this is your place ..."], "output": "[['portions', 'large', 'positive'], ['sushi dishes', 'creative', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["big thick pepperoni"], "output": "[['pepperoni', 'big thick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 The pepperoni 's cut real thick -- Yum ."], "output": "[[\"pepperoni 's\", 'thick', 'positive'], [\"pepperoni 's\", 'Yum', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pizza itself is not exactly the best I 've had EVER , but still pretty good ."], "output": "[['pizza', 'not exactly the best', 'positive'], ['pizza', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food was good and appetizing ."], "output": "[['Food', 'good', 'positive'], ['Food', 'appetizing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Portions was just enough for me , but may not be for a big eater ."], "output": "[['Portions', 'enough', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fair menu selection ."], "output": "[['menu selection', 'Fair', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The appetizer was interesting , but the Creme Brulee was very savory and delicious ."], "output": "[['appetizer', 'interesting', 'positive'], ['Creme Brulee', 'savory', 'positive'], ['Creme Brulee', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Indoor ambience was modern ."], "output": "[['Indoor ambience', 'modern', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a great place to people watch ."], "output": "[['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Late night dinning with exeptional food ."], "output": "[['food', 'exeptional', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["We were seated right away , the table was private and nice ."], "output": "[['table', 'private', 'positive'], ['table', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was exceptional - sometime there was a feeling that we were served by the army of friendly waiters ."], "output": "[['service', 'exceptional', 'positive'], ['waiters', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was very good , filet mignon was probably the best I 've ever try ."], "output": "[['food', 'good', 'positive'], ['filet mignon', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The portions are big though , so do not order too much ."], "output": "[['portions', 'big', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Groovy music made the dinner casual ."], "output": "[['music', 'casual', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have a but here - there was a bathroom attendant in the restroom which was odd ."], "output": "[['restroom', 'odd', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bathroom itself is very small with two toilets and only one sink , the girl was staying totally on the way hanging out paper towels from the dispenser ."], "output": "[['bathroom', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 Mercedes restaurant is so tasty , the service is undeniably awesome !"], "output": "[['service', 'awesome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The atmosphere is aspiring , and the decor is festive and amazing ..."], "output": "[['atmosphere', 'aspiring', 'positive'], ['decor', 'festive', 'positive'], ['decor', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The catering is out of this world , and Raouls chicken vegetable soup rocks my world ! ! !"], "output": "[['Raouls chicken vegetable soup', 'rocks my world', 'positive'], ['catering', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Drinks are suberb , and I feel like I am in a Third World country when I walk in the door ."], "output": "[['Drinks', 'suberb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["- Mediocre Service / Quality"], "output": "[['Service', 'Mediocre', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The presentation of Snooze is excellent and it is one of those places that you feel more sophisticated just for being there ; but peel back the layers and you have an overpriced IHOP with a high brow menu ."], "output": "[['Snooze', 'excellent', 'negative'], ['menu', 'high brow', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["They serve it in a tall , skinny hour-glass shaped glass to disguise the fact that you a getting a small juice at the price of a half gallon in a supermarket ."], "output": "[['juice', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I should have just asked for the check when I saw that ; but their menu was so unique that I continued ."], "output": "[['menu', 'unique', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pancakes were certainly inventive but $ 8.50 for 3 - 6 '' pancakes ( one of them was more like 5 '' ) in the pancake flight ( sample of 3 different pancakes ) is well over-priced ."], "output": "[['pancakes', 'inventive', 'negative'], ['pancakes', 'over-priced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pancakes should be larger ( at least 8 '' ) to justify the expense even with the unique offerings ."], "output": "[['pancakes', 'should be larger', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In the end our check came to $ 27 for 4 small pancakes , a breakfast burrito , an orange juice and an iced tea ( I had water ) ."], "output": "[['pancakes', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Much more than just a great view !"], "output": "[['view', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["\u2013 I am exceedingly pleased to report that my dinner at Ray 's Boathouse last Friday completely exceeded my expectations ."], "output": "[[\"Ray 's Boathouse\", 'exceeded my expectations', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ray 's is something of a Seattle institution , but given its gorgeous Sound views , I had suspected that the accolades were more due to the scenery than to the food and service ."], "output": "[['Sound views', 'gorgeous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Imagine my happy surprise upon finding that the views are only the third-best thing about Ray 's !"], "output": "[[\"Ray 's\", 'happy surprise', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["To start things off , our lovely server Brooke was quickly on hand to take my drink order ."], "output": "[['Brooke', 'lovely', 'positive'], ['Brooke', 'quickly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My party of two was feeling particularly ambitious , and we splurged on the Shilshole Sampler ... a beautiful assortment of enormous white gulf prawns , smoked albacore tuna , Ray 's fantastic manila clams seasoned with dill , scallops in a tasty soy dressing , and a tiny pile of Dungeness crab atop a sublime butter sauce ."], "output": "[['white gulf prawns', 'enormous', 'positive'], ['manila clams', 'fantastic', 'positive'], ['soy dressing', 'tasty', 'positive'], ['butter sauce', 'sublime', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["For my entr & eacute ; e , I completely enjoyed the seared Alaskan sea scallops complemented by chard , artichoke hearts , fennel , and pecorino toscano ."], "output": "[['seared Alaskan sea scallops', 'enjoyed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The scallops are apparently cooked in a black olive butter which really makes them unique ( not to mention tasty ) ."], "output": "[['scallops', 'unique', 'positive'], ['scallops', 'tasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["My friend enjoyed the grilled Alaskan King Salmon with delectable creamed Washington russet potatoes and crisp green beans ."], "output": "[['grilled Alaskan King Salmon', 'enjoyed', 'positive'], ['creamed Washington russet potatoes', 'delectable', 'positive'], ['green beans', 'crisp', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had a taste of all three items on her plate , and they were superb ."], "output": "[['plate', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Our server continued to be attentive throughout the night , but I did remain puzzled by one issue : Who thinks that Ray 's is an appropriate place to take young children for dinner ?"], "output": "[['server', 'attentive', 'positive'], [\"Ray 's\", 'appropriate', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["While I could have done without the youth who shared the evening with us , our wonderful server and food made the experience a very positive one ."], "output": "[['server', 'wonderful', 'positive'], ['food', 'wonderful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Oh yeah ... the view was good , too ."], "output": "[['view', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}