{"task_type": "generation", "dataset": "aste-data-v2", "input": ["I charge it at night and skip taking the cord with me because of the good battery life ."], "output": "[['battery life', '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 is of high quality , has a killer GUI , is extremely stable , is highly expandable , is bundled with lots of very good applications , is easy to use , and is absolutely gorgeous ."], "output": "[['quality', 'high', 'positive'], ['GUI', 'killer', 'positive'], ['applications', 'good', 'positive'], ['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": ["Easy to start up and does not overheat as much as other laptops ."], "output": "[['start 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": ["Great laptop that offers many great features !"], "output": "[['features', '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 night I turned the freaking thing off after using it , the next day I turn it on , no GUI , screen all dark , power light steady , hard drive light steady and not flashing as it usually does ."], "output": "[['GUI', 'no', 'negative'], ['screen', 'dark', 'negative'], ['power light', 'steady', 'neutral'], ['hard drive light', 'steady', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 multi-touch gestures and large tracking area make having an external mouse unnecessary ( unless you 're gaming ) ."], "output": "[['external mouse', 'unnecessary', '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 love the way the entire suite of software works together ."], "output": "[['suite of software', '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 speed is incredible and I am more than satisfied ."], "output": "[['speed', 'incredible', 'positive'], ['speed', '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": ["I can barely use any usb devices because they will not stay connected properly ."], "output": "[['usb devices', 'not stay connected properly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 finally had everything running with all my software installed I plugged in my droid to recharge and the system crashed ."], "output": "[['system', 'crashed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Pairing it with an iPhone is a pure pleasure - talk about painless syncing - used to take me forever - now it 's a snap ."], "output": "[['syncing', 'painless', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got the added bonus of a 30 '' HD Monitor , which really helps to extend my screen and keep my eyes fresh !"], "output": "[['screen', 'extend', '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 machine is slow to boot up and occasionally crashes completely ."], "output": "[['boot up', '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": ["After paying several hundred dollars for this service , it is frustrating that you can not get help after hours ."], "output": "[['service', '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": ["I love the operating system and the preloaded software ."], "output": "[['operating system', 'love', 'positive'], ['preloaded software', '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 best thing about this laptop is the price along with some of the newer features ."], "output": "[['price', 'best', 'positive'], ['features', 'best', 'positive'], ['features', 'newer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ABLE TO TALK TO AN AMERICAN WARRANTY SERVICE IS OUT OF COUNTRY ."], "output": "[['WARRANTY SERVICE', 'NOT BE ABLE', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 now i have realized its a problem with this brand ."], "output": "[['brand', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 kinda loud when the fan was running ."], "output": "[['fan', 'loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 also seemed to be a problem with the hard disc as certain times windows loads but claims to not be able to find any drivers or files ."], "output": "[['hard disc', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Speaking of the browser , it too has problems ."], "output": "[['browser', '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": ["The keyboard is too slick ."], "output": "[['keyboard', 'slick', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 like 9 punds , but if you can look past it , it 's GREAT !"], "output": "[['9 punds', 'GREAT', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 as fast with one program open as it is with sixteen open ."], "output": "[['program', 'fast', '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": ["Still under warrenty so called Toshiba , no help at all ."], "output": "[['warrenty', 'no 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": ["Amazing Quality !"], "output": "[['Quality', '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": ["A month or so ago , the freaking motherboard just died ."], "output": "[['motherboard', 'freaking', 'negative'], ['motherboard', 'died', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The system it comes with does not work properly , so when trying to fix the problems with it it started not working at all ."], "output": "[['system', 'not work properly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 after 4 or so months the charger stopped working so I was forced to go out and buy new hardware just to keep this computer running ."], "output": "[['charger', 'stopped 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": ["If a website ever freezes ( which is rare ) , its really easy to force quit ."], "output": "[['force quit', '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 also enjoy the fact that my MacBook Pro laptop allows me to run Windows 7 on it by using the VMWare program ."], "output": "[['Windows 7', 'enjoy', 'positive'], ['VMWare program', 'enjoy', '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 wanted to purchase the extended warranty and they refused , because they knew it was trouble ."], "output": "[['extended warranty', 'refused', '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": ["We upgraded the memory to four gigabytes in order to take advantage of the performace increase in speed ."], "output": "[['speed', 'increase', 'positive'], ['performace', 'increase', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The reality was , it heated up very quickly , and took way too long to do simple things , like opening my Documents folder ."], "output": "[['opening my Documents folder', '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": ["I had always used PCs and been constantly frustrated by the crashing and the poorly designed operating systems that were never very intuitive ."], "output": "[['operating systems', 'poorly designed', 'negative'], ['operating systems', 'intuitive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , within 5 months , the charger crapped out on me ."], "output": "[['charger', 'crapped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 if you have a iphone or ipod touch you can connect and download songs to it at high speed ."], "output": "[['speed', '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": ["I love the glass touchpad ."], "output": "[['glass touchpad', '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 continued to take the computer in AGAIN and they replaced the hard drive and mother board yet again ."], "output": "[['hard drive', 'replaced', 'negative'], ['mother board', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 HP sends it back to me with the hardware screwed up , not able to connect ."], "output": "[['hardware', 'screwed up', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , do n't forget the expensive shipping to and from HP ."], "output": "[['shipping', '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": ["Everything is so easy to use , Mac software is just so much simpler than Microsoft software ."], "output": "[['Mac software', 'easy', 'positive'], ['Microsoft software', 'simpler than', 'negative'], ['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 if you do a lot of writing , editing is a problem since there is no forward delete key ."], "output": "[['editing', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ease of use and the top service from Apple- be it their phone assistance or bellying up to the genius bar -- can not be beat ."], "output": "[['use', 'ease', 'positive'], ['service', 'top', 'positive'], ['phone assistance', 'can not be beat', 'positive'], ['genius bar', 'can not be 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 has a 10 hour battery life when you 're doing web browsing and word editing , making it perfect for the classroom or office , and in terms of gaming and movie playing it 'll have a battery life of just over 5 hours ."], "output": "[['battery life', 'perfect', 'positive'], ['web browsing', 'perfect', 'neutral'], ['word editing', '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": ["Acer has set me up with FREE recovery discs , when they are available since I asked ."], "output": "[['recovery discs', '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": ["Enabling the battery timer is useless ."], "output": "[['battery timer', '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": ["There is no need to purchase virus protection for Mac , which saves me a lot of time and money ."], "output": "[['virus protection for Mac', 'saves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 we had paid for bluetooth , and there was none ."], "output": "[['bluetooth', 'none', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always reliable , never bugged and responds well ."], "output": "[['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": ["they had to replace the motherboard in April"], "output": "[['motherboard', 'replace', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , if you need to talk to a representive at Microsoft , there is a charge , which I believe is robbery , since you are charged enormous amounts for a very badly designed system , which most people would have went with XP if they could ."], "output": "[['system', 'badly designed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 WIndows 7 which is a vast improvment over Vista ."], "output": "[['WIndows 7', '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": ["Dell 's customer disservice is an insult to it 's customers who pay good money for shoddy products ."], "output": "[[\"Dell 's customer disservice\", 'insult', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 talking it over with the very knowledgeable sales associate , I chose the MacBook Pro over the white MacBook ."], "output": "[['sales associate', 'knowledgeable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really want a bang-up system and do n't need to run Windows applications , go with an Apple ;"], "output": "[['system', 'bang-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": ["You wo n't have to spend gobs of money on some inefficient virus program that needs to be updated every month and that constantly drains your wallet ."], "output": "[['virus program', 'inefficient', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 color is even cool ."], "output": "[['color', '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": ["keys are all in weird places and is way too large for the way it is designed ."], "output": "[['keys', 'weird', 'negative'], ['keys', 'large', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , a Mac is much more money than the average laptop out there , but there is no comparison in style , speed and just cool factor ."], "output": "[['style', 'no comparison', 'positive'], ['speed', 'no comparison', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not to mention after using it for a few months or so , the battery will slowly less and less hold a charge until you ca n't leave it unplugged for more than 5 minutes without the thing dying ."], "output": "[['battery', '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": ["BEST BUY - 5 STARS + + + ( sales , service , respect for old men who are n't familiar with the technology ) DELL COMPUTERS - 3 stars DELL SUPPORT - owes a me a couple"], "output": "[['sales', '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": ["no complaints with their desktop , and maybe because it just sits on your desktop , and you do n't carry it around , which could jar the hard drive , or the motherboard ."], "output": "[['hard drive', 'jar', 'neutral'], ['motherboard', 'jar', '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": ["Yes , they cost more , but they more than make up for it in speed , construction quality , and longevity ."], "output": "[['speed', 'make up', 'positive'], ['construction quality', 'make up', 'positive'], ['longevity', 'make 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": ["It absolutely is more expensive than most PC laptops , but the ease of use , security , and minimal problems that have arisen make it well worth the pricetag ."], "output": "[['use', 'ease', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 stuck all of the time you use it , and you have to keep tapping on it to get it to work ."], "output": "[['use', 'stuck', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["lots of preloaded software ."], "output": "[['preloaded software', '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": ["I wish it had a webcam though , then it would be perfect !"], "output": "[['webcam', 'wish', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 thing I might add is the battery life is excellent ."], "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": ["One drawback , I wish the keys were backlit ."], "output": "[['keys', 'drawback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 wish the volume could be louder and the mouse didnt break after only a month ."], "output": "[['volume', 'louder', 'negative'], ['mouse', 'didnt break', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 play a lot of casual games online , and the touchpad is very responsive ."], "output": "[['touchpad', 'responsive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 everything I 'd hoped it would be from a look and feel standpoint , but somehow a bit more sturdy ."], "output": "[['look and feel standpoint', 'sturdy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 fact i dont like about apples is they generally use safari and i dont use safari but after i install Mozzilla firfox i love every single bit about it ."], "output": "[['safari', 'dont use', 'negative'], ['Mozzilla firfox', '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": ["Great battery , speed , display ."], "output": "[['battery', 'Great', 'positive'], ['speed', 'Great', 'positive'], ['display', '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 delivery was fast , and I would not hesitate to purchase this laptop again ."], "output": "[['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": ["I 've been impressed with the battery life and the performance for such a small amount of memory ."], "output": "[['battery life', 'impressed', 'positive'], ['performance', 'small', 'positive'], ['memory', '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": ["It 's applications are terrific , including the replacements for Microsoft office ."], "output": "[['applications', '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": ["I got it back and my built-in webcam and built-in mic were shorting out anytime I touched the lid , ( mind you this was my means of communication with my fiance who was deployed ) but I suffered thru it and would constandly have to reset the computer to be able to use my cam and mic anytime they went out ."], "output": "[['built-in webcam', 'shorting out', 'negative'], ['built-in mic', 'shorting out', 'negative'], ['cam', 'suffered', 'negative'], ['mic', 'suffered', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The board has a bad connector with the power supply and shortly after warrenty expires the power supply will start having issues ."], "output": "[['board', 'bad', 'negative'], ['connector', 'bad', 'negative'], ['power supply', '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": ["My dad has one of the very first Toshibas ever made , yes its abit slow now but still works well and i hooked to my ethernet !"], "output": "[['works', '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": ["Mostly I love the drag and drop feature ."], "output": "[['drag and drop feature', '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": ["oh yeah , and if the fancy webcam breaks guess who you have to send it to to get it fixed ?"], "output": "[['webcam', '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 ordered through MacMall , which saved me the sales tax I would have incurred buying locally ."], "output": "[['sales tax', 'saved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Of course , I also have several great software packages that came for free including iWork , GarageBand , and iMovie ."], "output": "[['software packages', 'great', 'positive'], ['iWork', 'free', 'positive'], ['GarageBand', 'free', 'positive'], ['iMovie', '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": ["The screen is very large and crystal clear with amazing colors and resolution ."], "output": "[['screen', 'large', 'positive'], ['screen', 'clear', 'positive'], ['colors', 'amazing', 'positive'], ['resolution', '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": ["After a little more than a year of owning my MacBook Pro , the monitor has completely died ."], "output": "[['monitor', 'died', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The brand of iTunes has just become ingrained in our lexicon now , but keep in mind that Apple started it all ."], "output": "[['iTunes', 'ingrained', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Size : I know 13 is small ( especially for a desktop replacement ) but with an external monitor , who cares ."], "output": "[['Size', 'small', 'negative'], ['external monitor', 'small', '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 display is incredibly bright , much brighter than my PowerBook and very crisp ."], "output": "[['display', 'bright', 'positive'], ['display', '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": ["The start menu is not the easiest thing to navigate due to the stacking ."], "output": "[['start menu', 'not the easiest', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 like the textured surface which shows no fingerprints ."], "output": "[['surface', '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 screen is bright and the keyboard is nice ;"], "output": "[['screen', 'bright', 'positive'], ['keyboard', '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": ["But the machine is awesome and iLife is great and I love Snow Leopard X ."], "output": "[['iLife', 'great', 'positive'], ['Snow Leopard X', '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 thought learning the Mac OS would be hard , but it is easily picked up if you are familiar with a PC ."], "output": "[['Mac OS', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 easy to use and lightweight ."], "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": ["They also have a longer service life than other computers ( I have several friends who still use the older Apple PowerBooks ) ."], "output": "[['service life', '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": ["If you check you will find the same notebook with the above missing ports and a dual core AMD or Intel processor ."], "output": "[['ports', 'missing', '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 laptop is a great price and has a sleek look ."], "output": "[['price', 'great', 'positive'], ['look', 'sleek', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the keyboard which has chiclet type keys ."], "output": "[['keyboard', 'like', 'positive'], ['keys', 'chiclet type', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bought a protector for my key pad and it works great : )"], "output": "[['protector', '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": ["The magnetic plug-in power charging power cord is great ( I even put it to the test by accident ) - excellent innovation !"], "output": "[['magnetic plug-in power charging power cord', 'great', 'positive'], ['magnetic plug-in power charging power cord', '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": ["While Apple 's saving grace is the fact that they at least stand behind their products , and their support is great , it would be nice if their products were more reliable to justify the premium ."], "output": "[['support', '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 good thing is the graphics quality ."], "output": "[['graphics quality', '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 other lock-up problems are from a myriad of causes , the most common being a corrupted version of Appleworks which can render the browser useless ."], "output": "[['Appleworks', 'corrupted', 'negative'], ['browser', '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": ["The paint wears off easily due to the keyboard being farther back than usual ."], "output": "[['paint', 'wears off', 'negative'], ['keyboard', 'farther back', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The store honored their warrenty and made the comment that they do n't even recommend the HP brand because of the problems with their warrentys ."], "output": "[['warrentys', \"do n't even recommend\", 'negative'], ['warrentys', '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": ["They sent out the box right away for me to send in my computer , they paid postage and whatnot , but when I got my computer back it still was n't running right , and now my CD drive was n't reading anything !"], "output": "[['CD drive', \"was n't reading anything\", 'negative'], ['running', \"was n't running right\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 screen size is not that bad for email and web browsing ."], "output": "[['screen size', 'not that bad', 'positive'], ['web browsing', 'not that bad', '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": ["On my PowerBook G4 I would never use the trackpad I would use an external mouse because I did n't like the trackpad ."], "output": "[['trackpad', 'never use', 'negative'], ['trackpad', \"did 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": ["This computer does n't do that well with certain games it ca n't play some and it becomes too hot while playing games ."], "output": "[['games', \"does n't do that well\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yeah , of course smarty pants `` fix it now '' ) Software - Compared to the early 2011 edition I did see inbuilt applications crashing and it prompted me to send the report to Apple ( which I promptly did ) ."], "output": "[['inbuilt applications', 'crashing', 'negative'], ['Software', 'smarty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The body is a bit cheaply made so it will be interesting to see how long it holds up ."], "output": "[['body', 'cheaply made', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a mac you do n't have to worry about antivirus software or firewall , it 's so wonderful ."], "output": "[['antivirus software', 'wonderful', 'neutral'], ['firewall', '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": ["Am very glad I bought it , great netbook , low price ."], "output": "[['price', 'low', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 team also assists you very nicely when choosing which computer is right for you : )"], "output": "[['Apple team', 'nicely', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 part of the problem with this computer is Vista , yet I know Vista is n't the entire issue because my latest purchase was my Acer and it also has Vista ( I should have waited the few months to get the next operating system ) ."], "output": "[['Vista', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The video chat is the only thing that is iffy about it but im sure once they unpdate the next version on the macbook book the quality of it will be better ."], "output": "[['video chat', 'iffy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["That whole experience was just ridiculous we sent it in and after they told us that we had to pay $ 175 to fix it we were like we will just by a portable mouse which would be way cheaper but they refused to send the laptop back until we paid the $ 175 and it was fixed ."], "output": "[['mouse', '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": ["Fan vents to the side , so no cooling pad needed , great feature !"], "output": "[['cooling pad', 'no', 'neutral'], ['feature', '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 use my mac all the time , i love the software , the way it takes a short time to load things , how easy it is to use and most of all how you do n't have to worry about viruses ."], "output": "[['software', 'love', 'positive'], ['software', '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": ["Wasted me at least 8 hours of installation time ."], "output": "[['installation time', '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": ["It has far exceeded my expectations for power , storage , and abilitiy ."], "output": "[['power', 'exceeded', 'positive'], ['storage', 'exceeded', 'positive'], ['abilitiy', 'exceeded', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 enjoying it and the quality it provides is great !"], "output": "[['quality', 'enjoying', '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": ["Suffice it to say , my MacBook Pro keeps me going with its long battery life and blazing speed ."], "output": "[['battery life', 'long', 'positive'], ['speed', 'blazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 also very user friendly , even for those that switch from a PC , with a little practice you can take full advantage of this OS !"], "output": "[['OS', 'user 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": ["iTunes is a handy music-management program , and it is essential for anyone with an iPod ."], "output": "[['iTunes', 'handy', 'positive'], ['iTunes', 'essential', 'positive'], ['program', 'handy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the programs are esay to use and are quick to process this computer works like a charm ."], "output": "[['programs', 'esay to use', 'positive'], ['use', 'esay', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tells me the latter problem is a power supply problem and have offered to fix it if it happens again ."], "output": "[['power supply', 'problem', 'negative'], ['power supply', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sells for the same as a netbook without sacrificing size ."], "output": "[['size', 'sacrificing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Windows XP SP2 caused many problems on the computer , so I had to remove it ."], "output": "[['Windows XP SP2', '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": ["this is my second one and the same problem , bad video card unreliable overall , this will be my second time returning this laptop back to best buy ."], "output": "[['video card', 'bad', 'negative'], ['video card', 'unreliable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 awesome graphics and assuring security , it 's perfect !"], "output": "[['graphics', 'awesome', 'positive'], ['security', 'assuring', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The laptop was very 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": ["I recommend for word processing and internet users ."], "output": "[['word processing', 'recommend', 'positive'], ['internet', '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": ["Since I 've had this computer I 've only used the trackpad because it is so nice and smooth ."], "output": "[['trackpad', 'nice', 'positive'], ['trackpad', '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": ["A longer battery life would have been great - but it meets it 's spec quite easily ."], "output": "[['spec', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Who could n't love a DVD burner , 80-gigabyte HD , and fairly new graphics chip ? As I soon discovered , though , there is a reason for which similarly-configured Sony and Toshiba machines cost more : they use higher-quality components that are faster , better-configured , and end up lasting a lot longer ."], "output": "[['graphics chip', 'new', 'positive'], ['components', 'higher-quality', 'positive'], ['components', 'faster', 'positive'], ['components', 'better-configured', 'positive'], ['components', '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": ["The computer itself was fast , ran smoothly , and had no problems ."], "output": "[['ran', '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": ["Like the price and operation ."], "output": "[['price', 'Like', 'positive'], ['operation', '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 brand is tarnished in my heart ."], "output": "[['brand', 'tarnished', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 likely due to poor grounding and isolation between the components , and I 'm hoping that it can be fixed with a ground loop isolator , but I still expected better product quality for this price range ."], "output": "[['components', 'poor', 'negative'], ['quality', '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": ["I 'have had it for about a 1 1/2 and yes I have had an issue with it one month out of warranty ."], "output": "[['warranty', 'out 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": ["Once open , the leading edge is razor sharp ."], "output": "[['leading edge', 'razor sharp', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Maximum sound is n't nearly as loud as it should be ."], "output": "[['Maximum sound', \"is n't nearly as loud\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 loaded windows 7 via Bootcamp and it works flawlessly !"], "output": "[['windows 7', 'flawlessly', 'positive'], ['Bootcamp', 'flawlessly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Laptop for the price , works well with action pack games ."], "output": "[['price', 'Great', 'positive'], ['action pack games', 'well', 'neutral'], ['works', '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": ["Although the price is higher then Dell laptops , the Macbooks are worth the dough ."], "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": ["So what if the laptops/mobile phones look chic and cool ? The after sales support is terrible ."], "output": "[['after sales support', 'terrible', 'negative'], ['look', 'chic', 'positive'], ['look', '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 hate the display screen and I have done everything I could do the change it ."], "output": "[['display screen', '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": ["I also like the acer arcade but these were reallythe only two things I liked about this laptop ."], "output": "[['acer arcade', '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": ["Have not yet needed any customer support with this yet so to me that is a great thing , which is leaps and bounds ahead of PC in my opinion ."], "output": "[['customer support', '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 gave it to my daughter because I just hated the screen , hated that it had no cd drive to at least play cd 's when I wanted to listen to music and do schoolwork ."], "output": "[['screen', 'hated', 'negative'], ['screen', 'hated', 'negative'], ['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": ["It runs very quiet too which is a plus ."], "output": "[['runs', 'quiet', 'positive'], ['runs', 'plus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it has a major design flaw ."], "output": "[['design', 'flaw', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 heavy , bulky , and hard to carry because of the size ."], "output": "[['size', 'heavy', 'negative'], ['size', 'bulky', 'negative'], ['size', 'hard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The games included are very good games ."], "output": "[['games', '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 computer will last you at least 7 years , thats an amazing life spanned an electronic ."], "output": "[['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": ["Three , the mac book has advantages over pcs ' with linux based os there is very few problems with system performance when it comes to a mac ."], "output": "[['system performance', 'few 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": ["A mac is very easy to use and it simply makes sense ."], "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": ["It is so much easier to use"], "output": "[['use', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 so nice not to worry about that and the extra expense that comes along with the necessary virus protection on PC 's ."], "output": "[['virus protection', 'nice', 'positive'], ['virus protection', 'necessary', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The processor screams , and because of the unique way that Apple OSX 16 functions , most of the graphics are routed through the hardware rather than the software ."], "output": "[['processor', 'screams', 'positive'], ['OSX 16', '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": ["I wanted something that had a new Intel Core processors and HDMI port so that we could hook it up directly to our TV ."], "output": "[['Intel Core processors', 'new', '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 price premium is a little much , but when you start looking at the features it is worth the added cash ."], "output": "[['price premium', 'much', 'negative'], ['features', '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 ca n't say enough of how satisfied I am with their product and help aftermarket ."], "output": "[['product and help aftermarket', '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": ["I connect a LaCie 2Big external drive via the firewire 800 interface , which is useful for Time Machine ."], "output": "[['LaCie 2Big external drive', 'useful', 'neutral'], ['firewire 800 interface', 'useful', 'positive'], ['Time Machine', 'useful', '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 am overall very pleased with my toshiba satellite , I like the extra features , I love the windows 7 home premium ."], "output": "[['extra features', 'like', 'positive'], ['windows 7 home premium', '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 battery life was shorter than expected ."], "output": "[['battery life', 'shorter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The keyboard is top notch ."], "output": "[['keyboard', '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": ["The image is great , and the soud is excelent ."], "output": "[['image', 'great', 'positive'], ['soud', 'excelent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 well worth the money it cost , Very good investment ."], "output": "[['cost', 'well worth', 'positive'], ['cost', '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": ["Upgrading from Windows 7 Starter , thru Windows 7 Home Premium , to Windows 7 Professional was a snap ;"], "output": "[['Windows 7 Professional', 'snap', '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 upgraded my old MacBook to Lion , so I kind of knew what I was getting , but had n't been able to enjoy some of the awesome new multi-touch features ."], "output": "[['multi-touch features', '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 screen is a little glary , and I hated the clicking buttons , but I got used to them ."], "output": "[['screen', 'glary', 'negative'], ['clicking buttons', '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": ["Not to mention , the battery life is absolutely amazing ."], "output": "[['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": ["Now for the hardware problems ."], "output": "[['hardware', '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": ["It 's fast and has excellent battery life ."], "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": ["Apple care included ."], "output": "[['Apple care', 'included', '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": ["Windows is also rather unsteady on its feet and is susceptible to many bugs ."], "output": "[['Windows', 'unsteady', 'negative'], ['Windows', 'susceptible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 NOT BUY GATEWAY COMPUTERS THEY ARE JUNK AND THE WARRANTY COMPANY IS HORRIBLE ."], "output": "[['WARRANTY COMPANY', '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": ["The only bad part is the size / weight ."], "output": "[['size', 'bad', 'negative'], ['weight', '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 little battery that it did have would only last about an hour while just having it on the desktop ."], "output": "[['battery', 'little', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 aluminum body ."], "output": "[['aluminum body', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 for playing my apps on Facebook or watching movies ."], "output": "[['watching movies', 'good', 'positive'], ['playing', '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": ["From the build quality to the performance , everything about it has been sub-par from what I would have expected from Apple ."], "output": "[['build quality', 'sub-par', 'negative'], ['performance', 'sub-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 love the dock where I can simply drop a file ontop of a particular program , and the program will simply open that file ."], "output": "[['dock', 'love', 'positive'], ['program', '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": ["pretty much everything else about the computer is good it just stops working out of no were ."], "output": "[['working', 'stops', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 truly a great computer costing less than one thousand bucks before tax ."], "output": "[['costing', 'less', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Waiting for the i7 was well worth it , great value for the price ."], "output": "[['price', 'great', 'positive'], ['i7', '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": ["Boots up fast and runs great !"], "output": "[['Boots up', 'fast', 'positive'], ['runs', '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": ["Lightweight and the screen is beautiful !"], "output": "[['screen', '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 Macbook arrived in a nice twin packing and sealed in the box , all the functions works great ."], "output": "[['twin packing', 'nice', 'positive'], ['functions', '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 say sorry out of warranty ."], "output": "[['warranty', 'out 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": ["After having two PC laptops die with in the past 3 years , I was led to the Apple display at Best Buy by the sleek design and promise of less tech issues ."], "output": "[['design', 'sleek', 'positive'], ['tech issues', 'less', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 I received from Toshiba went above and beyond the call of duty ."], "output": "[['service', 'above', 'positive'], ['service', 'beyond', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 had many higher priced computers crash and burn long before ever got to use all that great memory and speed , etc ."], "output": "[['memory', 'great', 'negative'], ['speed', 'great', 'negative'], ['priced', '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": ["I would recommend it just because of the internet speed probably because thats the only thing i really care about ."], "output": "[['internet speed', '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 screen shows great colors ."], "output": "[['screen', 'great', 'positive'], ['colors', '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": ["Reason why ? It 's because when you buy it , you know first thing that you will not lose any value for that laptop , the price will stay the same for the next year , and even if Apple does decides to change mode , your laptop value will only drop 10-20 % , unlike PC laptops which drop more than 80 % ."], "output": "[['value', 'drop', 'positive'], ['price', 'stay', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The 17 inch screen is very large , but the computer is very light ."], "output": "[['17 inch screen', 'large', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 opinion of Sony has been dropping as fast as the stock market , given their horrible support , but this machine just caused another plunge ."], "output": "[['support', '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": ["For the Bluetooth to work properly , you must install the Launch Manager on the Drivers/Applications DVD , or it will not show after the reload ."], "output": "[['Bluetooth', 'properly', '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 also liked the glass screen ."], "output": "[['glass screen', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The switchable graphic card is pretty sweet when you want gaming on the laptop ."], "output": "[['switchable graphic card', '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 battery life has not decreased since I bought it , so i 'm thrilled with that ."], "output": "[['battery life', 'decreased', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 called Toshiba , they would not do anything and even tried to charge me $ 35 for the phone call , even though they did n't offer any technical support ."], "output": "[['technical support', \"did n't offer\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bought this notebook and only had it for 3 months If it is overload with updates the BOOT MGR ."], "output": "[['BOOT MGR', 'overload', '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": ["Oh and if thats not bad enough it does n't come with a recovery cd so you can make one if you know how to or buy one if you buy it the cost is $ 25 for two cds ."], "output": "[['recovery cd', '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 price and features more than met my needs ."], "output": "[['price', 'more', 'positive'], ['features', '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": ["Skype is just so dang cool with this machine too ."], "output": "[['Skype', '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": ["Also , HDD secures inside using rails , and there is only one set on the main hard drive ."], "output": "[['HDD', 'secures', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 I will say now is that it was over two grand less expensive and so much better quality than my hunk of crap Vaio ."], "output": "[['quality', '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": ["Games being the main issue ."], "output": "[['Games', '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": ["They say that this will invalidate the warranty on the hard drive ( I do n't really understand why but anyway ) ."], "output": "[['warranty', 'invalidate', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 great computer for light home use and business use ."], "output": "[['home use', 'light', 'positive'], ['business use', '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": ["Also consider the MS Office apps are all trial versions , hope you have your own copies ."], "output": "[['MS Office apps', 'trial', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 so , I like playing online games , so it was wonderful that there is a feature where I can dualboot Windows ."], "output": "[['feature', '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 battery life is amazingly long at 7hrs and 5hrs if you use it ."], "output": "[['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": ["lightweight , long battery life , excellent transition from PC ;"], "output": "[['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 Nortons virus scan is only for a very short time unlike others that usually are good for a year ."], "output": "[['Nortons virus scan', '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": ["I am first time Mac Buyer and am amazed at features and ease of use the Mac offers ."], "output": "[['features', 'amazed', 'positive'], ['use', 'ease', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Came fully loaded - good ."], "output": "[['loaded', 'fully', 'positive'], ['loaded', '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 noticed windows has a new system called Windows 7 , what about us Vista users ? They should get all the bugs out of Vista before investing in a new system ."], "output": "[['Windows 7', 'new', '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 that I have , is the key broad is a little dark to see the letters , would help if it was a little lighter then it is ."], "output": "[['key broad', '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": ["This is the complete opposite to an ergonomic design ."], "output": "[['design', 'opposite', 'negative'], ['design', 'ergonomic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 I do n't like about my mac is that sometimes there are programs that I want to be able to run and I am not able to ."], "output": "[['programs', \"do n't like\", 'negative'], ['programs', 'not able', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wireless has not been a issue for me , like some others have meantioned ."], "output": "[['Wireless', 'not been a issue', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["MacBook Notebooks quickly die out because of their short battery life , as well as the many background programs that run without the user 's knowlede ."], "output": "[['battery life', 'short', 'negative'], ['programs', 'background', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 things you can do with the trackpad make navigating around the computer and its programs so much simpler , quicker , and easier ."], "output": "[['trackpad', 'simpler', 'positive'], ['trackpad', 'quicker', 'positive'], ['trackpad', 'easier', 'positive'], ['navigating', 'simpler', 'positive'], ['navigating', 'quicker', 'positive'], ['navigating', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 guess the only good thing that came out of these were the speakers and the subwoofer ."], "output": "[['speakers', 'good', 'positive'], ['subwoofer', '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": ["Theres a built in camera with special effects- for video and photography ."], "output": "[['built in camera', 'special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 for such a great price ."], "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": ["Another thing is that after only a month the left mouse key broke and it costed $ 175 to send it in to fix it ."], "output": "[['left mouse key', 'broke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 speed and plenty of hard drive space ."], "output": "[['speed', 'good', 'positive'], ['hard drive space', '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": ["Very long-life battery ( up to 10-11 hours depending on how you configure power level settings ) ."], "output": "[['battery', 'long-life', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The black model also has a very nice seamless appearance - one of the better looking notebooks I 've seen ."], "output": "[['appearance', 'nice 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": ["The technical service for dell is so 3rd world it might as well not even bother ."], "output": "[['technical service for dell', '3rd world', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The graphics were awful and the warranty is n't even worth the cheap payment on the computer ."], "output": "[['graphics', 'awful', 'negative'], ['warranty', \"is n't even 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": ["They gave me a hard time yet again , but their was a malfunction in the battery itself , it did n't die ."], "output": "[['battery', 'malfunction', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 do n't feel comfortable doing it yourself , just buy the case and be happy , plus it looks nice , I bought the white one from Best Buy ."], "output": "[['case', '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": ["Excellent speed for processing data ."], "output": "[['speed', '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 has come into good use for my finances , scheduling , my parents business expenses , and it is definitely amazing for gaming ."], "output": "[['gaming', 'amazing', 'positive'], ['use', '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 taught to use Photoshop and was amazed ."], "output": "[['Photoshop', '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": ["The driver updates do n't fix the issue , very frustrating ."], "output": "[['driver updates', '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": ["It doesnt work worth a damn ."], "output": "[['work', 'doesnt', 'negative'], ['work', 'damn', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really well ."], "output": "[['works', '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": ["Bigger HD , better graphics card , and a bid HD ."], "output": "[['HD', 'Bigger', 'positive'], ['HD', 'bid', 'positive'], ['graphics card', '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 built in camera is very useful when chatting with other techs in remote buildings on our campus ."], "output": "[['built in camera', 'useful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The DVD burner broke after burning 3 DVD 'd during that time !"], "output": "[['DVD burner', 'broke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 with our wireless and they 've had not problems ."], "output": "[['works', '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": ["Product support very poor as each phone call costs me long distan"], "output": "[['Product support', '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": ["Overall the computer is very easy to use , the screen is perfect , great computer , my daughter loves ."], "output": "[['screen', 'perfect', 'positive'], ['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": ["The casing of the power cord fried and shocked my husband when he pulled it out of the socket ."], "output": "[['casing of the power cord', 'fried', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 does not keep internet signals no matter where you bring it ."], "output": "[['internet signals', 'not keep', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 product for a great price !"], "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": ["But see the macbook pro is different because it may have a huge price tag but it comes with the full software that you would actually need and most of it has free future updates ."], "output": "[['software', 'full', 'positive'], ['updates', '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": ["and the multiple page viewer ( allows you to press one button to see every separate page currently opened at the same time in one screen ) are great for those who are working non stop or just shopping online ."], "output": "[['multiple page viewer', '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": ["Keyboard good sized and easy to use ."], "output": "[['Keyboard', 'good sized', 'positive'], ['Keyboard', 'easy to use', 'positive'], ['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": ["wonderful features ."], "output": "[['features', '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": ["Im glad that it has such great features in it ."], "output": "[['features', '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 TYPING , LETTERS AND SPACES ARE FREQUENTLY OMITTED REQUIRING THE USER TO REDO MANY WORDS AND SENTENCES ."], "output": "[['TYPING', 'OMITTED', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a few days after I received the computer back , the screen froze again ."], "output": "[['screen', 'froze', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not ideal for children because of the temp ."], "output": "[['temp', 'not ideal', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 do believe that Windows operating system may be to fault for some of the problems ."], "output": "[['Windows operating system', 'fault', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 OS , fabulous improvements to the existing line bumping up the processor speed and adding the thunderbolt port ."], "output": "[['OS', 'Great', 'positive'], ['OS', 'fabulous', 'positive'], ['processor speed', 'fabulous', 'positive'], ['thunderbolt port', 'adding', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Images are crisp and clean ."], "output": "[['Images', 'crisp', 'positive'], ['Images', '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": ["although its windows vista compared to windows xp sucks ."], "output": "[['windows vista', 'sucks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The computer runs very fast with no problems and the iLife software that comes with it ( iPhoto , iMovie , iWeb , iTunes , GarageBand ) is all very helpful as well ."], "output": "[['iLife software', 'helpful', 'positive'], ['iPhoto', 'helpful', 'positive'], ['iMovie', 'helpful', 'positive'], ['iWeb', 'helpful', 'positive'], ['iTunes', 'helpful', 'positive'], ['GarageBand', 'helpful', 'positive'], ['runs', '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": ["At first it worked well for a month or so then the system board failed and I send it in to toshiba some complaints and three weeks later I then receive my laptop back only to discover that it still has the same problem so now I have to send it back again to get it fixed again ."], "output": "[['system board', 'failed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Until I bought the Dell , I thought you just looked for what you wanted ( size , software , options , hardware ) and purchase the best deal you could find ."], "output": "[['hardware', '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": ["It has plenty of memory , lots of hard drive , and great graphics ."], "output": "[['memory', 'plenty', 'positive'], ['hard drive', 'lots', 'positive'], ['graphics', '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": ["However , my girlfriend realized that the netbook 's hinge is a bit loose ( when you open or close the LCD ) ."], "output": "[['hinge', 'loose', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 problem was with DELL Customer Service ."], "output": "[['DELL Customer Service', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Newegg 's RMA service was great as always , I contacted them late Friday night , and they issued me an RMA number and a PrePaid UPS shipping label the very next morning on Saturday ."], "output": "[['RMA 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": ["Design : very durable ."], "output": "[['Design', 'durable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 easy to go from one keyboard to another ."], "output": "[['keyboard', 'easy', '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 ONLY issues are : 1 ) the screen/video resolution wo n't increase to a higher resolution then 1024 x 60"], "output": "[['screen/video resolution', 'issues', 'negative'], ['screen/video resolution', \"wo n't increase\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 pretty fast and does not have hiccups while I am using it for web browsing , uploading photos , watching movies ( 720p ) on occasion and creating presentations ."], "output": "[['web browsing', 'fast', 'positive'], ['uploading photos', 'fast', 'positive'], ['watching movies', 'fast', 'positive'], ['creating presentations', '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": ["Quality Display I love HP , , it 's the only computer/printer we will buy ."], "output": "[['Quality Display', '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 features are great , the only thing it needs is better speakers ."], "output": "[['features', 'great', 'positive'], ['speakers', '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": ["I bought this laptop and found its TAB is not functioning ."], "output": "[['TAB', 'not functioning', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["-Called headquarters again , they report that TFT panel is broken , should be fixed by the end of the week ( week 3 ) ."], "output": "[['TFT panel', 'broken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Navigation through the computer is far superior compared to Windows operating systems , as well ."], "output": "[['Navigation', '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": ["The screen is framed by half- to a full-inch margin that is obviously unnecessary , reduces the screen size and increases the bulk ."], "output": "[['screen', 'unnecessary', 'negative'], ['screen size', 'reduces', 'negative'], ['bulk', 'increases', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 re-install Windows within two weeks of the purchase and soon discovered cracks in the screen hinges ."], "output": "[['screen hinges', 'cracks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 SECOND PROBLEM INVOLVES THE BATTERY WHICH IS ADVERTISED AS HAVING A STORAGE LIFE OF 11 HOURS BUT WHEN FULLY CHARGED SHOWS ONLY 7 HOURS OF SERVICE ."], "output": "[['BATTERY', 'PROBLEM', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 plenty of storage with 250 gb ( though I will upgrade this and the ram.. )"], "output": "[['storage', '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": ["Programs would crash all the time , and it turned out to be a very unstable , unreliable laptop for me ."], "output": "[['Programs', '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 key bindings take a little getting used to , but have loved the Macbook Pro ."], "output": "[['key bindings', 'loved', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 is reasonable size ."], "output": "[['Keyboard', 'reasonable size', 'positive'], ['size', '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": ["Fan noise : The fan made a constant hissing noise in the background ."], "output": "[['Fan', 'noise', 'negative'], ['fan', 'noise', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is bright and clear , the operating system is solid and friendly to a novice ."], "output": "[['screen', 'bright', 'positive'], ['screen', 'clear', 'positive'], ['operating system', 'solid', 'positive'], ['operating system', '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 has a .1 ghz faster processor and a stock 500gb hard drive ."], "output": "[['processor', 'faster', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 n't a big deal , I have n't noticed the issue with DVDs or other media , only through USB output ."], "output": "[['USB output', '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": ["With Windows laptops a wireless mouse is an absolute must ."], "output": "[['wireless mouse', 'must', '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 good quality and well made ."], "output": "[['quality', '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 niece and nephew have played a few web games and it runs anything that does n't require a dedicated video card ."], "output": "[['video card', 'dedicated', '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 had the full sized touch pad with 2 buttons instead of just one ."], "output": "[['touch pad', 'full sized', '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": ["Typically , when I purchase a new laptop I always end up using an external mouse for convenience ."], "output": "[['external mouse', 'convenience', '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 super easy to set up and Is really easy to get used to ."], "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 only thing that can be updated is the video , other than that you 're all set ."], "output": "[['video', 'updated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a good laptop for its value ."], "output": "[['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": ["Then the hard drive failed ;"], "output": "[['hard drive', 'failed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["of course my warranty runs out next month ."], "output": "[['warranty', 'runs out', '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 found also , it is very easy to be able to access wireless internet access ;"], "output": "[['wireless internet access', '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": ["This is a great value for the money ."], "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 battery has never worked well ."], "output": "[['battery', 'never worked well', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 never buy another computer from Dell ever again do to how awful it worked and how I was treated by the company ."], "output": "[['company', '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": ["Small enough to use on a long flight , Light enough to carry through airports and powerful enough to replace my desktop while on long business trips ."], "output": "[['carry', '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": ["Typing on the keyboard becomes uncomfortable after extended use due to the sharp edges that your wrists rest on ."], "output": "[['keyboard', 'uncomfortable', 'negative'], ['edges', 'sharp', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 many great programs , such as ILife , iPhotos and others ."], "output": "[['programs', 'great', 'positive'], ['ILife', 'great', 'positive'], ['iPhotos', '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 this laptop to anybody that wants great performance from a laptop and would like to relax and not become enraged cursing the gods about to throw your laptop out the door ."], "output": "[['performance', '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 screen resolution was exactly what I was looking for ."], "output": "[['screen resolution', 'exactly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it is running Snow Leopard , 2.4 GHz C2D is a bit of an antiquated CPU and thus the occasional spinning wheel would appear when running Office Mac applications such as Word or Excel ."], "output": "[['CPU', 'antiquated', 'negative'], ['spinning wheel', 'occasional', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 number pad to the right of the keyboard which is a bummer ."], "output": "[['pad', 'no', 'negative'], ['pad', 'bummer', 'negative'], ['keyboard', 'bummer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 upgrade is possible to the full Windows 7 , then I will truly be a very happy geek ."], "output": "[['Windows 7', '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": ["I was originally concerned that I could n't view work I had done in college on my Mac because of the PC formatting , but I was even more thrilled to learn of programs like iLife and iWork that allow you to convert your PC documents into readable files on Macs ."], "output": "[['programs', 'thrilled', 'positive'], ['iLife', 'thrilled', 'positive'], ['iWork', '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": ["Runs fast and the regular layout keyboard is so much better ."], "output": "[['regular layout keyboard', 'better', 'positive'], ['Runs', '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": ["All the programs are easy and straight forward on my MacBook Pro , it is clean and organized , which I always strive to be myself ."], "output": "[['programs', 'easy', 'positive'], ['programs', 'straight forward', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Windows 7 Starter is terrific ( no you ca n't change the background ) but I do n't need to , I use it just for school work ."], "output": "[['Windows 7 Starter', '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": ["Support has been lackluster and now I just want a refund ."], "output": "[['Support', 'lackluster', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["`` > iPhoto is probably the best program I have ever worked with : easy and convenient ."], "output": "[['iPhoto', 'best', 'positive'], ['iPhoto', 'easy', 'positive'], ['iPhoto', '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": ["I love to write and play with graphics and html programming and my new Toshiba works great on both !"], "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": ["My laptop now has no battery ."], "output": "[['battery', '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": ["It made the computer much easier to use and navigate ."], "output": "[['use', 'easier', 'positive'], ['navigate', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 longer lasting battery , More than 1 to 2 Hrs ."], "output": "[['battery', 'longer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 May I started having problems with the USB ports not working ."], "output": "[['USB ports', 'problems', 'negative'], ['USB ports', '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": ["The Mac version of Microsoft Office is cheaper than buying the actual and works just as well ."], "output": "[['Mac version of Microsoft Office', 'cheaper', 'positive'], ['Mac version of Microsoft Office', 'as 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 Toshiba Net book operates very well ."], "output": "[['operates', '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 touch pad is fine - again , it 's a real touch pad ."], "output": "[['touch pad', 'fine', 'positive'], ['touch pad', 'real', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pictures are clear as can be ."], "output": "[['pictures', '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": ["It is also very lightweight , making transporting this computer very easy ."], "output": "[['transporting', '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 's wonderful for computer gaming ."], "output": "[['gaming', '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 flaws are , this computer is not for computer gamers because of the OS X ."], "output": "[['OS X', 'flaws', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 do have the worlds very worst repair service ."], "output": "[['repair 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": ["I was also able to install and use my Photoshop and AfterEffects programs easily ."], "output": "[['Photoshop', 'easily', 'positive'], ['AfterEffects programs', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 perfect for everything and runs faster than an average pc !"], "output": "[['runs', 'faster', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 after paying for it to be examined I was told it was same problem cited on website but I 'd have to pay anyways since it was past warrenty ."], "output": "[['warrenty', 'past', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 already hooked on the sleek look and dependability that this laptop has shown ."], "output": "[['look', 'sleek', 'positive'], ['dependability', 'sleek', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 having to deal with the company has been a even worse nightmare ."], "output": "[['company', 'worse 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": ["It has all the features that are necessary for college and if not they are able to be added onto the computer ."], "output": "[['features', 'necessary', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 owned this labtop for less then two months , already the mouse button has broke ."], "output": "[['mouse button', 'broke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 did fairly well , other than it 's poor performance , overheating and occational blue screen ."], "output": "[['performance', '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": ["lots of extra space but the keyboard is ridiculously small ."], "output": "[['space', 'lots', 'positive'], ['keyboard', '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": ["It 's so bad that I 'm thinking I only got half a battery or something ."], "output": "[['battery', '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": ["Good keyboard , long battery life , largest hard drive and windows 7 ."], "output": "[['keyboard', 'Good', 'positive'], ['battery life', 'long', 'positive'], ['hard drive', 'largest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The processor is very quick and effective as I load webpages and applications ."], "output": "[['processor', 'quick', 'positive'], ['processor', 'effective', 'positive'], ['load', 'quick', 'positive'], ['load', 'effective', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 battery went bad about a year and a half after having it and it cost around eighty to a hundred dollars !"], "output": "[['battery', '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 pretty much does everything we could ever need , and looks great to boot ."], "output": "[['boot', '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": ["As a lifelong Windows user , I was extremely pleased to make the change to Mac ."], "output": "[['Windows', 'pleased', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is also made better , my computer has never got a virus , and the laptop runs just as fast as the first day I bought it ."], "output": "[['runs', '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 wiped nearly everything off of it , installed OpenOffice and Firefox , and I am operating an incredibly efficient and useful machine for a great price ."], "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": ["Overall I feel this netbook was poor quality , had poor performance , although it did have great battery life when it did work ."], "output": "[['quality', 'poor', 'negative'], ['performance', 'poor', 'negative'], ['battery life', '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 picked it out because it was inexpensive ( $ 400 ) and I thought it would be a good , easy to use first laptop ."], "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": ["MY ONLY PROBLEM IS I CAN NOT REG . THE PRODUCT KEY ."], "output": "[['PRODUCT KEY', 'PROBLEM', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 has the one touch keys but that was the best feature of the computer ."], "output": "[['one touch keys', '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 battery life ."], "output": "[['battery life', '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": ["At first , the computer seemed a great deal -- seemingly high-end specs for a low , low price ."], "output": "[['specs', 'high-end', 'positive'], ['price', 'low', 'positive'], ['price', 'low', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 stability of the Mac software and operating system ."], "output": "[['stability', 'Love', 'positive'], ['Mac software', 'Love', 'positive'], ['Mac software', 'stability', 'positive'], ['operating system', 'Love', 'positive'], ['operating system', 'stability', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 also very capable of doing moderate video editing ( although you may need the performance boost of the larger MacBook Pros for heavy duty mobile video editing ) ."], "output": "[['video editing', 'capable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 faster processor and more ram ."], "output": "[['processor', 'faster', 'positive'], ['ram', '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": ["Would like more trendy , high tech features ."], "output": "[['features', 'trendy', 'negative'], ['features', 'high tech', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 is great but primary and secondary control buttons could be more durable ."], "output": "[['Keyboard', 'great', 'positive'], ['control buttons', 'durable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it back again and was told the motherboard had been replaced , so I was now on the SECOND motherboard within 3 months ."], "output": "[['motherboard', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 speed , especially !"], "output": "[['speed', '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": ["Not only are the versions of these programs able to be saved , worked on and opened on both a PC and Mac , the versions of these programs on a Mac are graphically and functionally superior ."], "output": "[['programs', '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": ["The speed gives you the power to work on these projects seamlessly , and multiple at a time if you sowish ."], "output": "[['speed', 'seamlessly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 laptop and the perfect size to carry around in college ."], "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": ["My real problem with it ? The statement of 7 hour battery life is not just mere exaggeration -- it 's a lie ."], "output": "[['battery life', 'problem', 'negative'], ['battery life', 'exaggeration', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 also relatively good ."], "output": "[['battery life', '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 found it very easy to use , very informative , wonder alerts and tutorials making it very easy for someone like me who is not exactly technologically advanced to learn to use the various features and programs ."], "output": "[['features', 'various', 'positive'], ['programs', 'various', 'positive'], ['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": ["I do n't have stupid pop up windows ( even when I have pop ups blocked ) , I do n't have to wait 5 minutes for a webpage to download , and best of all I can run all the web programming software I need to use all at once without slowing me down ."], "output": "[['pop up windows', 'stupid', 'positive'], ['web programming software', '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": ["Memory is upgradable ."], "output": "[['Memory', 'upgradable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 access through the 3G network is so slow , it 's very frustrating and VERY DISAPPOINTING ."], "output": "[['3G network', 'slow', 'negative'], ['3G network', 'frustrating', 'negative'], ['Web access', 'slow', 'negative'], ['Web access', '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": ["The large screen also helps when you are working in design based programs like Adobe Creative Suite ."], "output": "[['screen', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 my first Dell I heard their customer service was lacking and that they were working on improving it !"], "output": "[['customer 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": ["As well as having the plug in the computer come loose ."], "output": "[['plug', 'loose', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Second HDD cover has walls inside that need to be broken if you what to install one ."], "output": "[['HDD cover', 'broken', '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": ["Great product by Apple with the new great looking design ."], "output": "[['design', 'new 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 love the keyboard ."], "output": "[['keyboard', '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 use iphoto all the time , which is a great program for anyone who is into photography - amateurs and experts alike ."], "output": "[['iphoto', 'great', 'positive'], ['program', '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": ["Now , as easy as it is to use , and I do think it is a great STARTER laptop ."], "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": ["Ever since I bought this laptop , so far I 've experience nothing but constant break downs of the laptop and bad customer services I received over the phone with toshiba customer services hotlines ."], "output": "[['customer services', '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": ["Also , the space bar makes a noisy click every time you use it ."], "output": "[['space bar', 'noisy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["iPhotos is an excellent program for storing and organizing photos ."], "output": "[['iPhotos', 'excellent', 'positive'], ['program', '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": ["Other than that its a great performing machine and well meets all my needs and more ."], "output": "[['performing', '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 programs are great , like iphoto ( love the editing capabilities ) , imail ( which can incorporate with the address book on the ipod and ipad ) , imovie , etc ."], "output": "[['programs', 'great', 'positive'], ['iphoto', 'great', 'positive'], ['iphoto', 'love', 'positive'], ['imail', 'great', 'positive'], ['imovie', '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": ["Comfortable to use light easy to transport ."], "output": "[['use', 'Comfortable', '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": ["The Computer itself is a good product but the repair depot stinks ."], "output": "[['repair depot', '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 thought the price was great for the specs ."], "output": "[['price', 'great', 'positive'], ['specs', '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 only down fall is that it has no cd drive but i found that they are very cheap to by and also very portable making this the best friend to someone who is always looking for more space then they have ."], "output": "[['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": ["So , the hard disk capacity really does n't matter to me ."], "output": "[['hard disk capacity', \"does n't matter\", '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 also like that you can scroll down in a window using two fingers on the trackpad ."], "output": "[['trackpad', '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": ["Everything from the design to the OS is simple and to the point ."], "output": "[['design', 'simple', 'positive'], ['design', 'to the point', 'positive'], ['OS', 'simple', 'positive'], ['OS', 'to the 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": ["I personally like the gaming look but needed a machine that delivered gaming performance while still looking professional in front of my customers ."], "output": "[['gaming look', '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": ["This just keeps having it 's hard drive replaced !"], "output": "[['hard drive', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 you look at the specs on Apple products in comparison to a Dell or a HP , yes they do seem to offer less for a higher cost ."], "output": "[['cost', '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": ["The only downfall is the volume control ."], "output": "[['volume control', 'downfall', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 fast boot up and shut down ."], "output": "[['boot up', 'fast', 'positive'], ['shut down', '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 finally decided on this laptop because it was the right price for what I need it ."], "output": "[['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": ["If internet connectivity is important I would recommend going with a dell net book for 50 bucks more , or buy a USB wireless card ."], "output": "[['internet connectivity', 'important', 'neutral'], ['USB wireless card', '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 had read online that some users were having sound problems ."], "output": "[['sound', '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": ["It discharges too quickly ."], "output": "[['discharges', 'quickly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to be honest , the compatibility issues and the other little quirks make me think I ll buy a PC next time ."], "output": "[['compatibility', '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": ["Then it ceased charging at all ."], "output": "[['charging', 'ceased', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 experience a lot of heat coming out of it , however I would highly suggest purchasing a stand however , due to the nature of the design of the macbook as it is one very large heat sink ."], "output": "[['stand', 'suggest', 'neutral'], ['heat sink', 'large', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Webcam is a bit laggy , not the greatest ."], "output": "[['is', ',', 'negative'], ['is', 'the greatest .', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 have n't had any major problems with the laptop except that the plastic piece that covers the usb port wires have all come off ."], "output": "[['plastic piece', 'problems', 'negative'], ['plastic piece', 'come off', 'negative'], ['usb port wires', 'problems', '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": ["Wonderful sleek case design is only on the outside ."], "output": "[['case design', 'Wonderful sleek', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 speedy when connected wirelessly to any network regardless if the connection is weak or not ."], "output": "[['connection', 'speedy', '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 pricing is very competitive ."], "output": "[['pricing', 'competitive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 exceptionally thin for it 's screen size and processing power ."], "output": "[['screen size', 'thin', 'positive'], ['processing power', '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": ["Maybe this is virus related , maybe not , but the computer has locked up many times , and on two occasions , the screen has simply gone black ."], "output": "[['screen', 'black', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is bright and vivid and the keyboard is very easy to use , very important for use quick typers ."], "output": "[['screen', 'bright', 'positive'], ['screen', 'vivid', 'positive'], ['keyboard', 'easy to use', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 my IWORKS , Itunes , Email , MS Office , network and printers set up and completely working perfectly within an hour ."], "output": "[['IWORKS', 'perfectly', 'positive'], ['Itunes', 'perfectly', 'positive'], ['MS Office', '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 macbooks are small enough to be very portable yet hold tons of information and performance ."], "output": "[['performance', 'hold', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 downfall is a lot of the software I have wo n't work with Mac and iWork is not worth the price of it ."], "output": "[['iWork', 'downfall', 'negative'], ['iWork', 'not worth', 'negative'], ['software', 'downfall', '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": ["The mousepad is a huge pain in the arse !"], "output": "[['mousepad', 'huge pain', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 then i have had minor problems with slow operation ."], "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": ["Registration/1st use is easy ."], "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": ["Take your time and go through the tutorials patiently ."], "output": "[['tutorials', 'patiently', '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": ["Keyboard could use some trimming ."], "output": "[['Keyboard', 'trimming', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Returned laptop for repair a 2nd time and it came back with obvious physical damage ( keyboard bulging and speaker grill pressed in ) , buttons not working and USB ports inoperative ."], "output": "[['keyboard', 'damage', 'negative'], ['keyboard', 'bulging', 'negative'], ['speaker grill', 'damage', 'negative'], ['speaker grill', 'pressed in', 'negative'], ['buttons', 'not working', 'negative'], ['USB ports', 'inoperative', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The letter A stopped working after the first week ."], "output": "[['letter A', 'stopped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 what I do know how to do , the computer works beautiful ."], "output": "[['works', '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": ["Most everything is fine with this machine : speed , capacity , build ."], "output": "[['speed', 'fine', 'positive'], ['capacity', 'fine', 'positive'], ['build', '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 use this for my tutoring business , and since I 'm always bouncing from student to student , it is ideal for portability and battery life ( yes , it gets the 8 hours as advertised ! ) ."], "output": "[['portability', 'ideal', 'positive'], ['battery life', '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": ["It is in the best condition and has a really high quality ."], "output": "[['quality', '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": ["When it come time for warranty service to Toshiba you do n't matter ."], "output": "[['warranty service to Toshiba', \"do n't matter\", '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 the frozen screens kept happening ."], "output": "[['screens', 'frozen', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 short on space , and downloads always had problems being completed , or were said to be 'corrupted ' ."], "output": "[['space', 'short', 'negative'], ['downloads', '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": ["3 ) Horrible customer support"], "output": "[['customer support', '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": ["Apple is always great about the aesthetics of things , they always come up with good looking products ."], "output": "[['aesthetics', '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": ["Runs smooth and quick ."], "output": "[['Runs', 'smooth', 'positive'], ['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": ["The downside to this netbook is pretty much the same for any netbook : screen size is not something I 'd stare at for the entire 10-11 hours of battery life five days a week ."], "output": "[['screen size', 'downside', '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 graphics are great ."], "output": "[['graphics', '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": ["in 5 months the connect quality got worse and worse ."], "output": "[['connect quality', 'worse', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The big screen allows you to enjoy watching movies , pictures and etc !"], "output": "[['screen', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the headphone and mic jack are in front of touch-pad making the touch-pad hard to use when using headphones/mic , not to mention the laptop was designed for right handed person ."], "output": "[['headphone', 'hard', 'negative'], ['mic jack', 'hard', 'negative'], ['touch-pad', 'hard to use', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 [ $ ] price ( special offer ) this is a great laptop ."], "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": ["What I 'd like is for the laptop to run well without having to purchase additional memory ."], "output": "[['run', 'well', '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 fast booting up , shutting down , and connection with the internet ."], "output": "[['connection with the internet', 'fast', 'positive'], ['booting up', 'fast', 'positive'], ['shutting down', '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": ["This is not a serious gaming laptop or a serious media machine ;"], "output": "[['gaming', 'serious', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 replaced my hard drive as well as my mother board ."], "output": "[['hard drive', 'replaced', 'neutral'], ['mother board', 'replaced', '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 nothing to complain about the system ."], "output": "[['system', 'nothing to complain', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it comes with the new OSX that comes with new features that makes the use more easy ."], "output": "[['OSX', 'new', 'positive'], ['features', 'new', 'positive'], ['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": ["Now the screen is going darker , darker , darker ."], "output": "[['screen', 'darker', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 take it everywhere with me because it 's so easy to carry ."], "output": "[['carry', '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": ["Oh and it has word and stuff but its a trial verion so after about a month or so when you go to open it it asks for a product key which didnt come with the computer and even after clicking cancel it wont let you use it at all I use the old word processer which works good ."], "output": "[['word processer', '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 keyboard has a wonderful nature feel ."], "output": "[['keyboard', '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 battery does n't last long but I 'm sure an upgrade battery would solve that problem ."], "output": "[['battery', \"does n't last 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": ["I was looking too closely at the other performance specs and while comparing , I took it for granted that these features were standard ."], "output": "[['features', 'standard', '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 bought this last week , and the very next day had to return it because it over heated and the touch-mouse stopped responding ."], "output": "[['touch-mouse', 'stopped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The cover for the DVD drive soon came off , too -- a mark of poor construction quality ."], "output": "[['cover for the DVD drive', 'came off', 'negative'], ['cover for the DVD drive', 'poor', 'negative'], ['construction quality', '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": ["But the arm velcro is torn after one use ."], "output": "[['arm velcro', 'torn', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The software is amazing ."], "output": "[['software', '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": ["We carry the netbook around here and there , hence it 's kinda of irritating when the LCD just `` slide '' downwards ."], "output": "[['LCD', 'irritating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 GB of RAM is plenty , able to run Windows 7 and at least 2 or 3 other programs with next to no slowdown ."], "output": "[['2 GB of RAM', 'plenty', 'positive'], ['Windows 7', 'able', 'positive'], ['programs', 'able', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 amazing , the versitility is outstanding ."], "output": "[['battery life', 'amazing', 'positive'], ['versitility', '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": ["Vista is a nightmare ."], "output": "[['Vista', '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": ["The program came with the computer and works beautifully ."], "output": "[['program', 'beautifully', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 loving this Netbook because it had an amazing screen and display and was small and light , but after 1 week it stopped openning web pages for me ( even after installing new browsers ) then eventually it just started giving me a blue screen and crashing everytime I booted it ."], "output": "[['screen', 'amazing', 'positive'], ['display', 'small', 'positive'], ['display', 'light', 'positive'], ['browsers', 'new', '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 So called laptop Runs to Slow and I hate it !"], "output": "[['Runs', 'Slow', 'negative'], ['Runs', '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": ["Charger seems large for this class of computer ."], "output": "[['Charger', 'large', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dislike the quality and the placement of the speakers ."], "output": "[['speakers', '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": ["The screen graphics and clarity , and sharpness are great ."], "output": "[['screen graphics', 'great', 'positive'], ['clarity', 'great', 'positive'], ['sharpness', '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": ["So I called customer support ( which is good too ) and they went through it and it is just a safety feature and it does not affect performance at all , I just chose to hide the message ."], "output": "[['customer support', 'good', 'positive'], ['performance', 'not affect', '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 unibody design is edgy and durable ."], "output": "[['unibody design', 'edgy', 'positive'], ['unibody design', 'durable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["STOPPED BOOTING UP less than a week after my one-year warranty was up ."], "output": "[['BOOTING UP', 'STOPPED', 'negative'], ['one-year warranty', 'up', '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 , for the cost this is a winner ."], "output": "[['cost', '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": ["Also , the battery does not last very long at all ."], "output": "[['battery', '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": ["I bought it from HSN because it was `` bundled '' with extra software , but as it turns out , that software just crashes it more often ... .."], "output": "[['software', 'crashes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 constantly had to send my laptop in for services every 3 months and it always seems to be the same problem that they said they had already fixed ."], "output": "[['services', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 performance in this device makes use of fun and a strong sense of the era of speed This device serves all modern requirements is a very strong game and is very useful for designers ."], "output": "[['performance', '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": ["I was sorely disapointed to discover that HP ( what I thought was a reputable company ) would n't honor the warrenty when the fan blade fell apart ."], "output": "[['warrenty', 'sorely disapointed', 'negative'], ['fan blade', 'fell apart', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 most people say that PCs hold functionality and value and Macs are just pretty to look at , I think there 's something to be said about the simplicity of Macs ."], "output": "[['look', 'pretty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 macbook is so much better looking and so thin !"], "output": "[['looking', '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 battery gets so HOT it is scary ."], "output": "[['battery', 'HOT', 'negative'], ['battery', 'scary', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to look at and the keys are easy to type with ."], "output": "[['keys', 'easy', 'positive'], ['look', '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": ["It is absolutely horrible to use , despite all its so called advanced features ."], "output": "[['features', 'advanced', 'negative'], ['use', '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 have to keep turning it until it decides to lower and there is no mute ."], "output": "[['mute', '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": ["It 's still beautiful and has better color reproduction than I could ever expect from a notebook ."], "output": "[['color reproduction', '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": ["He loves it and it is easy to use and well the schools start teaching the kids early about computers so it was easy for him to get started ."], "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": ["Also , macbooks come with much more features which are so cool !"], "output": "[['features', 'more', '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": ["Getting the Apple Care plan is a must ."], "output": "[['Apple Care plan', '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": ["overall i would recomend this to anybody and tell them that if they want to burn their music or play there video games to buy the cd drive ."], "output": "[['cd drive', 'recomend', '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 dv4 boasted a faster processor , more memory , and a bigger hard drive than my old computer , plus a better quality web cam , nicer screen , and many other features ."], "output": "[['processor', 'faster', 'positive'], ['memory', 'more', 'positive'], ['hard drive', 'bigger', 'positive'], ['web cam', 'better', 'positive'], ['screen', 'nicer', 'positive'], ['features', '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": ["The only downfall is the battery only last 1.5-2.0 hrs when not plugged in ."], "output": "[['battery', 'downfall', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The graphics on this computer are also stellar - very clear and vivid ."], "output": "[['graphics', 'stellar', 'positive'], ['graphics', 'clear', 'positive'], ['graphics', 'vivid', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Aside from the trial software and the short battery life , lack of a webcam , its great ."], "output": "[['battery life', 'short', 'negative'], ['webcam', '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 newer black keyboard took a little bit away from the previous gray one which looked really slick , but it is still a great notebook !"], "output": "[['black keyboard', 'newer', 'negative'], ['black keyboard', 'great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sony parts reliability and quality of service is recenlty the worst ."], "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": ["As with any laptop not purchased with software options , it comes with a lot of what I consider useless applications ."], "output": "[['applications', '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": ["Its Office compatible , but the features and its functioning is all new again so you might as well save the money and just learn the pre installed mac programs ."], "output": "[['features', 'new', 'neutral'], ['functioning', 'new', 'neutral'], ['Office', 'compatible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 flawlessly !"], "output": "[['works', 'flawlessly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 having the laptop returned unrepaired since paying $ 176 every 3 months just is n't worth it ( that 's about how long the port seems to last ) ."], "output": "[['port', '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": ["also the battery is completely shot ."], "output": "[['battery', 'completely shot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 cooling system / much better grafics card ( ATI 5870 ) / 8GB RAM / LED backlit screen ..."], "output": "[['cooling system', 'awesome', 'positive'], ['grafics card', 'better', 'positive'], ['LED backlit screen', 'better', 'positive'], ['8GB RAM', '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 biggest problem is that the box had no instructions in it ."], "output": "[['instructions', 'problem', 'negative'], ['instructions', '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": ["Compared to similarly spec 'd PCs , this machine is good value , well built and works easily right out of the box ."], "output": "[['value', 'good', 'positive'], ['built', 'well', 'positive'], ['works', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 crystal clear and the system is very responsive ."], "output": "[['Screen', 'crystal clear', 'positive'], ['system', 'responsive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 easy to operate and I have already ordered more software and gadgets for my new Rolls Royce of laptops ."], "output": "[['software', 'more', 'neutral'], ['operate', 'easy', 'positive'], ['gadgets', 'more', '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 might be something deep within Windows , for I was unable to create a disk image on my hard drive ."], "output": "[['Windows', 'unable', 'negative'], ['hard drive', 'unable', 'negative'], ['disk image', 'unable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The track pad to me is what really stands out though , you can do several different things with it just depending on how many fingers you use on the track pad , awesome thinking Apple !"], "output": "[['track pad', 'stands 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": ["Now I had not tried to use this since the disc drive had been replaced and after taking it back to the Geek Squad I found out they had accidently not used the right drive when they replaced the first one , so back it went to get the correct drive ."], "output": "[['disc drive', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , you ll discover that the word processing program known as Appleworks rarely translates perfectly on anyone else s computer , if it translates at all ."], "output": "[['Appleworks', 'rarely translates perfectly', 'negative'], ['word processing program', 'rarely translates perfectly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Battery is not upgradable to a longer life battery ."], "output": "[['Battery', 'not upgradable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 has a reputation and is well known for its easy usage ."], "output": "[['usage', '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": ["Returned laptop for a 3rd repair and it came back with previous problems fixed ( except for speaker grill ) but the unit started locking up during use and eventually would not operate at all ."], "output": "[['speaker grill', '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": ["Love the graphics , awesome programs ( including Garageband ) , and really cool default background ."], "output": "[['graphics', 'Love', 'positive'], ['programs', 'awesome', 'positive'], ['Garageband', 'awesome', 'positive'], ['default background', '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": ["Screen , keyboard , and mouse : If you cant see yourself spending the extra money to jump up to a Mac the beautiful screen , responsive island backlit keyboard , and fun multi-touch mouse is worth the extra money to me alone ."], "output": "[['screen', 'beautiful', 'positive'], ['island backlit keyboard', 'responsive', 'positive'], ['multi-touch mouse', '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": ["Overall , I experienced a huge change in that my mac runs pretty fast compared to my old PC ."], "output": "[['runs', '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": ["When I got the computer back and realizwed it still was not correct HP told me it was out of warranty and now it was my problem ."], "output": "[['warranty', 'out 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": ["It also came with a built it web cam which is great because I can see an communicate with my family members back home ."], "output": "[['built it web cam', '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 was secure and easy to navigate ."], "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": ["I was a little weary at purchasing another 13 '' macbook almost 2 years later but t looks like the newer macbooks have gotten its current line of graphics cards in order this time around ."], "output": "[['graphics cards', 'in order', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 by far the easiest systems to actually learn about computers with ."], "output": "[['systems', 'easiest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The video card is great for media , and above average for gaming , but not a gamers first choice ."], "output": "[['gaming', 'above average', 'positive'], ['media', '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": ["Apparently there is a manufacturing defect , something with the amount of thermal paste ."], "output": "[['thermal paste', 'defect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Asus facial recognition does n't work and windows logon is n't either ."], "output": "[['facial recognition', \"does n't work\", 'negative'], ['windows logon', \"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": ["Windows Vista makes this computer almost unusable for online service ."], "output": "[['Windows Vista', 'unusable', 'negative'], ['online service', '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": ["I contacted Acer and they are giving me FREE recovery DVDs , so do n't go and pay for them , just ask for them and they should give them to you ."], "output": "[['recovery DVDs', '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": ["Now when I order I did not go full scale for the webcam or full keyboard I wanted something for basics of being easy to carry when I use crutchs or wheelchair and with a backpack laptop bag ."], "output": "[['carry', '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": ["Can listen to my music and watch my videos with ease and with a great display ."], "output": "[['display', '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 is awesome ."], "output": "[['performance', '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 display is beyond horrible ."], "output": "[['display', '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": ["There is hardly any memory on the computer 's hard drive ."], "output": "[['memory', 'hardly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the laptop preformed pretty well ."], "output": "[['preformed', '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 minute you fire it up it 's all good , very easy user interface ."], "output": "[['user interface', 'good', 'positive'], ['user interface', '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 actually contact Toshiba before I started having problem and was given run around after I supplied serial number in order to delay me sending in laptop until after warrenty expired ."], "output": "[['warrenty', 'expired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 hard drive the battery stopped working ( 3 months of use ) which was frustrating ."], "output": "[['battery', 'stopped working', 'negative'], ['battery', '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": ["I love the easy to see screen , and It works well for work , persoal or just play ."], "output": "[['screen', 'love', 'positive'], ['screen', 'easy', 'positive'], ['works', '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": ["Awesome graphics !"], "output": "[['graphics', '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 pro is a great product , I wish that the 13 inch models came with the Intel i processors and had a more comfortable edge ( the edges hurt my wrists ) ."], "output": "[['edge', 'comfortable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 drawback I noticed was sound quality via USB ."], "output": "[['sound quality via USB', 'drawback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 sucked the juice from my laptop and when the extended life battery went out we were SOL there to , so much for that warranty covering all the products we purchased ."], "output": "[['battery life', 'sucked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 another Mac , but it got slow due to an older operating system ."], "output": "[['operating system', 'slow', 'negative'], ['operating system', 'older', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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'ts nice to have the higher-end laptops , but this fits my budget and the features I need ."], "output": "[['features', '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": ["Was disappointed to find out that the model had been discontinued , apparently because of known motherboard problems ."], "output": "[['motherboard', 'disappointed', 'negative'], ['motherboard', '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": ["Also the speakers are not very loud , But it is a netbook ."], "output": "[['speakers', 'not very loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 LAPTOP WONDERFUL PRICE FOR WHAT YOU GET !"], "output": "[['PRICE', 'LOVE', 'positive'], ['PRICE', '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": ["A key contributor that led me to Mac is the art aspect ."], "output": "[['art aspect', 'contributor', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Accordingly , I have decided to NEVER purchase another HP product ( my five year old Compaq ) lasted 5-years before the hard drive crashed ."], "output": "[['hard drive', 'crashed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 that everyone thinks Macs are overpriced and overrated , but once you get past the initial expense you 'll find that they 're worth every penny ( besides , there 's always the financing plan that Best Buy offers ) ."], "output": "[['expense', '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": ["I love the multi-touch trackpad ."], "output": "[['multi-touch 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": ["HP is more interested in selling extended warranties ( which cost more than the netbook new ) then they are in helping or fixing ."], "output": "[['extended warranties', 'cost more', 'negative'], ['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": ["Not too much `` junk '' software to remove ."], "output": "[['software', 'junk', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 loosing about 20 % of performance because of that ."], "output": "[['performance', 'loosing', 'negative'], ['System', 'loosing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The difference in the Apple keyboard from a PC 's keyboard took a bit of tim to get used to , but overall it 's worth it !"], "output": "[['Apple keyboard', 'worth', 'neutral'], [\"PC 's keyboard\", 'worth', '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": ["Only issue is that it is a little slow , and I 'm fixing that by adding more RAM ."], "output": "[['RAM', 'more', '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 hard drive crashed as well , and I had to buy a new power cord ."], "output": "[['hard drive', 'crashed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 issue I have with it is the battery ."], "output": "[['battery', '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": ["My MacBook Pro works like a dream , it has never overheated , or even been slightly warm for that matter ."], "output": "[['works', 'dream', 'positive'], ['works', 'never overheated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 get a ton of compliments on its size , and speaking as someone who regularly commutes on a bus , I can attest to the fact that this is the perfect size computer if you 're restricted to the width of your body for computing room ."], "output": "[['size', 'compliments', 'positive'], ['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": ["Easy to carry , can be taken anywhere , can be hooked up to printers , headsets ."], "output": "[['carry', '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": ["When I got my laptop back after this first instance it worked okay for a little bit then I started expeirencing issues again , everything from programs and drivers failing again , to it powering off for no reason , to locking up and freezing and just all sorts of issues ."], "output": "[['programs', 'issues', 'negative'], ['programs', 'failing', 'negative'], ['drivers', 'issues', 'negative'], ['drivers', 'failing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 that it does n't take up space like a regular computer ."], "output": "[['space', '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": ["So , I took it back to the apple store and they narcissist genius bar staff ) fixed it by resetting the fan at boot up ."], "output": "[['fan', 'fixed', '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 mouse on the pad , the left button always sticks ."], "output": "[['mouse on the pad', 'sticks', 'neutral'], ['left button', 'sticks', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 use the built in tools often , iTunes is open nearly every day and works great with my iPhone ."], "output": "[['built in tools', 'great', 'neutral'], ['iTunes', '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 size of has actually help me out quite a bit by me being able to fit it in an already full backpack and to use it at a resturant where the food on the table is always so space consuming ."], "output": "[['size', 'able to fit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["True quality at a great price !"], "output": "[['quality', 'True', '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": ["The programs that come standard with the Leopard running system are enough for the average person to run all the basics ."], "output": "[['programs', '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": ["So what am I supposed to do ? The LG service center can not provide me the `` service '' when it is called the `` service center '' ."], "output": "[['service center', 'can not 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": ["The Material this Pro is made out of seems a lot nicer than any PC Specs : Like I said this performs a lot better than any computer I 've had in the past ."], "output": "[['Material', 'nicer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 doing extensive research , macconnection had the lowest price on the 15 '' MBP i5 ."], "output": "[['price', 'lowest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ADDICTED to photo booth !"], "output": "[['photo booth', 'ADDICTED', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The operating system and user interface is very intuitive , and the large multi-touch track pad is amazing ."], "output": "[['operating system', 'intuitive', 'positive'], ['user interface', 'intuitive', 'positive'], ['multi-touch track pad', 'large', 'positive'], ['multi-touch track pad', '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": ["Hard disk - The new editions gives you more hard disk space ( 500GB instead of 320GB ) but time has taught me never to trust an internal hard disk ."], "output": "[['hard disk space', 'more', 'positive'], ['internal hard disk', 'never to trust', '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 extremely portable and easily connects to WIFI at the library and elsewhere ."], "output": "[['connects to WIFI', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 things first , Macbook pro has many applications to make life easier , unlike the windows computers ."], "output": "[['applications', 'many', 'positive'], ['applications', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 screen on this thing is absolutely amazing for high quality videos and movies and gaming ."], "output": "[['screen', 'amazing', 'positive'], ['gaming', '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": ["I considered I may have too much on the computer , but after looking , there was plenty of space and that is not the issue ."], "output": "[['space', '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": ["Now mainboard is broken , have to wait for a new one ."], "output": "[['mainboard', 'broken', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The speed difference is next to NOTHING for a mac , and the hard drive can be manually upgraded or you could just buy a $ 60 500gb external hard drive ."], "output": "[['speed', 'NOTHING', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The people are frustrating to work with , the product itself is very cheaply made , and the accessories are less than satisfactory ."], "output": "[['accessories', 'less than satisfactory', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a mac is wonderful , it takes a little used to learning and getting used to the new system , but you will learn fast and its all worth it ."], "output": "[['system', 'new', 'neutral'], ['system', 'learn fast', 'neutral'], ['system', 'worth', '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 love the size of the computer since i play games on it ."], "output": "[['size', '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 know , using the computer should be fun , not aggrevation , especially when you are playing games or working with photos ."], "output": "[['playing games', 'fun', 'neutral'], ['playing games', 'not aggrevation', '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": ["To be honest i think it was faulty equipment or something but idk ."], "output": "[['equipment', '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": ["I also love the small , convenient size of my laptop , making it a perfect tool for my academic studies ."], "output": "[['size', 'small', 'positive'], ['size', '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": ["I love its solid build , light wt and excellent battery life ( for now ) ."], "output": "[['build', 'love', 'positive'], ['build', 'solid', 'positive'], ['wt', 'love', 'positive'], ['wt', 'light', 'positive'], ['battery life', 'love', 'positive'], ['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": ["The battery holds up well , it 's built very solidly , and runs fast ."], "output": "[['battery', 'holds up well', 'positive'], ['built', 'solidly', 'positive'], ['runs', '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": ["Sound card is limited though ."], "output": "[['Sound card', '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": ["This is a nicely sized laptop with lots of processing power and long battery life ."], "output": "[['processing power', 'lots of', 'positive'], ['battery life', 'long', 'positive'], ['sized', 'nicely', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["-Computer crashed frequently and battery life decreased very quickly ."], "output": "[['battery life', 'decreased very quickly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 propose that they can just swap the hard drives ."], "output": "[['hard drives', 'swap', '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 also fairly easy to use the Operating System ."], "output": "[['Operating System', '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": ["So having the AC plug go out on me and get lose or I could actually here it inside my computer on two of the three times is not good ."], "output": "[['AC plug', '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": ["Peformance is good for the price ."], "output": "[['Peformance', 'good', '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": ["Summary : HP knew they were shipping out bad BIOS and did nothing proactive to resolve it ."], "output": "[['BIOS', '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 had 3 months when the ports started going out ."], "output": "[['ports', 'going out', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The improvements to the OS have been relatively gradual , but substantive ."], "output": "[['OS', 'improvements', 'positive'], ['OS', 'relatively gradual', 'positive'], ['OS', 'substantive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 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": ["Many of my classmates computers hard drives crashed ."], "output": "[['hard drives', 'crashed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ease of use is just one of the benefits I love about my Mac ."], "output": "[['use', 'Ease', 'positive'], ['use', 'benefits', 'positive'], ['use', '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 13 '' Macbook Pro just fits in my budget and with free shipping and no tax to CA this is the best price we can get for a great product ."], "output": "[['shipping', 'free', 'positive'], ['price', 'best', 'positive'], ['budget', 'fits', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sheer power and flexibility makes the MacBook Pro a must have for any techie !"], "output": "[['power', 'must', 'positive'], ['flexibility', '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": ["The notebook is lacking a HDMI port and a S-video port that would enable one to hook it to a TV ."], "output": "[['HDMI port', 'lacking', 'negative'], ['S-video port', '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": ["Battery is lasting about 6 hours as I am surfing the web on Sundays while checking football scores and watching funny Youtube videos ."], "output": "[['Battery', 'lasting', '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": ["Iphoto is great for adding pictures right to facebook and other social networking sites ."], "output": "[['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": ["Some features arent friendly ( volume wheel , sound quality , etc ."], "output": "[['volume wheel', 'arent friendly', 'negative'], ['sound quality', 'arent friendly', 'negative'], ['features', 'arent 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": ["A cheaper price should not equal a `` cheap '' product ."], "output": "[['price', '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": ["After a couple of years , my battery life began to diminish but was replaced for free due to a company-wide recall of my particular battery ."], "output": "[['battery', 'particular', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The system constantly overheats , the battery life is too short , the case is coming apart , and my core applications that I use every day in my work as a graphic artist run poorly ."], "output": "[['battery life', 'short', 'negative'], ['case', 'coming apart', 'negative'], ['core applications', 'poorly', 'negative'], ['system', 'overheats', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The company sent me a whole new cord overnight and apologized ."], "output": "[['cord', '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 's even easy to hook up to other wireless networks ."], "output": "[['hook up to other wireless networks', '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 rep did not even answer my question , I had to ask him , if he understood what I ask or if he spoke english because he did n't even try to acknowledge my question ."], "output": "[['rep', 'did 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": ["Again I sent it back and they replaced the motherboard and some fan inside ."], "output": "[['motherboard', 'replaced', 'neutral'], ['fan', 'replaced', '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": ["For me , keys were starting to get stuck and would n't type very well ."], "output": "[['keys', 'stuck', 'negative'], ['keys', \"would n't type very well\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["ca n't reinstall with standard os cd because of proprietary hardware drivers ."], "output": "[['standard os cd', \"ca n't reinstall\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The computer was two weeks late in delivery because HP forgot to complete the required import paperwork ."], "output": "[['delivery', 'late', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very pleased with the performance of this laptop ."], "output": "[['performance', '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": ["I bought it for my mom and she reports that the battery life lasts all day for her , it 's very lightweight , and the response for the computing she 's doing ( Internet focused activity : mail , research , etc . ) is excellent ;"], "output": "[['battery life', 'lasts all day', 'positive'], ['response', 'excellent', 'positive'], ['Internet focused activity', 'excellent', '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 very nice and once you learn the features you will be so happy to have such a sophisticated computer ."], "output": "[['features', 'happy', '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 sleek and lightweight and charges quickly when needed ."], "output": "[['charges', '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": ["also you may need to charge it once a day , if for medium use every thing fast and easy with mac the size and look is the most feature that attracted me to it ."], "output": "[['size', 'attracted', 'positive'], ['look', 'attracted', 'positive'], ['feature', 'attracted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 think it had a camera because that was one of my requirements , but forgot to check in the specifications on this one before I purchased ."], "output": "[['specifications', 'check in', '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": ["little short on RAM but you get what you pay for ."], "output": "[['RAM', '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": ["It did n't come with any software installed outside of windows media , but for the price , I was very pleased with the condition and the overall product ."], "output": "[['software', \"did n't come with\", 'negative'], ['price', '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": ["THEN , one month after the warranty expired , the replacement charger went ."], "output": "[['warranty', 'expired', '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 love a `` pc '' but I was ready for a change and tired of the windows system ."], "output": "[['windows system', 'tired 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": ["Other installed features , such as certain printer software , are also most attractive ."], "output": "[['features', 'attractive', 'positive'], ['printer software', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 doing so , the hinge may just be slightly tightened only ."], "output": "[['hinge', 'tightened', '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": ["company provides UPS shipping , fast , great !"], "output": "[['shipping', 'fast', '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": ["It is easy to use , has great screen quality , and every so light weight ."], "output": "[['screen quality', 'great', 'positive'], ['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": ["The iLife software that comes with the computer is so simple to use and produces a great finished product ."], "output": "[['iLife software', 'simple', 'positive'], ['iLife software', 'great', '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": ["The shop will definitely push the problem to the service center ."], "output": "[['service center', 'problem', '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 mostly use it for email , internet and gaming , I 'm confident all other applications live up to the high standard I 've come to appreciate from Mac laptops ."], "output": "[['applications', 'high standard', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 laptop looks great on the surface : 17 '' inch screen , good price-point , nice appearance , boots up quickly , runs fast etc ."], "output": "[['price-point', 'great', 'positive'], ['price-point', 'good', 'positive'], ['appearance', 'great', 'positive'], ['appearance', 'nice', 'positive'], ['boots up', 'quickly', 'positive'], ['runs', '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 apple systems are over priced luxurys that ar n't worth what they are being charged for , this model 's specifications are far from being impressive and they only thing you get out of this is the apple name ."], "output": "[['specifications', 'far from being impressive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["pros : the macbook pro notebook has a large battery life and you wont have to worry to charge your laptop every five hours or so ."], "output": "[['battery life', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Disappointing for such a lovely screen and at a reasonable price"], "output": "[['screen', 'Disappointing', 'positive'], ['screen', 'lovely', 'positive'], ['price', 'Disappointing', '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": ["The only bad thing about it is they give you the worst batteries possible ."], "output": "[['batteries', '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": ["Good price ."], "output": "[['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": ["the speed is fine ."], "output": "[['speed', '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": ["It was not clear that the Microsoft Student Edition that was loaded on the computer , was a six month trial ."], "output": "[['Microsoft Student Edition', 'not clear', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 every day computing and web browsing ."], "output": "[['web browsing', 'Good', 'positive'], ['every day computing', '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": ["Also , I have had a lot of trouble with the keys sticking and will not type correctly ."], "output": "[['keys', 'trouble', 'negative'], ['keys', 'sticking', 'negative'], ['keys', 'not type correctly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 LED monitor and well equipped ."], "output": "[['LED monitor', '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": ["Without a doubt , the * design * of this laptop is fantastic ."], "output": "[['design', '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 could save ten essay papers and have hardly any memory left ."], "output": "[['memory', 'hardly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 that , I would recommend this to someone in need of a cheap laptop with semi-decent gaming capabilities ."], "output": "[['gaming', 'semi-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": ["But the biggest pain is that tech support is not available 24/7 ."], "output": "[['tech support', 'pain', 'negative'], ['tech support', 'not available', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 chose the iBookG4 , a laptop that is an attractive computer with a large screen big enough to please anyone ."], "output": "[['screen', 'attractive', 'positive'], ['screen', 'large', 'positive'], ['screen', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the Mac is not only visually appealing , but very easy to use ."], "output": "[['use', 'appealing', 'positive'], ['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": ["THE FIRST PROBLEM IS THAT THE KEYBOARD FUNCTION IS SIMPLY UNSATISFACTORY ."], "output": "[['KEYBOARD FUNCTION', 'UNSATISFACTORY .', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Garageband is more for the musicians , and the laptop is equipped with a good working microphone , good enough for beginners and musicians at the intermediate level ."], "output": "[['Garageband', 'good working', 'neutral'], ['microphone', 'good working', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dual boot with Linux and that other security-prone OS and it performs flawlessly ."], "output": "[['Linux', 'flawlessly', 'neutral'], ['security-prone OS', 'flawlessly', 'neutral'], ['performs', 'flawlessly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The difference is the Toshiba had a lot more memory and hard drive space ."], "output": "[['memory', 'a lot more', 'positive'], ['hard drive space', 'a lot 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": ["There was a little difficulty doing the migration as the firewire cable system ca n't be used with the iBook ."], "output": "[['firewire cable system', 'difficulty', 'negative'], ['firewire cable system', \"ca n't 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": ["Seems like maybe a bad shipment from Toshiba ."], "output": "[['shipment', '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": ["OS X is solid with lots of innovations such as quicklook which save heaps of time ."], "output": "[['OS X', 'solid', 'positive'], ['OS X', 'innovations', 'positive'], ['quicklook', 'save heaps of time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 other than that I am blown away by all the features this laptop offers ."], "output": "[['features', 'blown 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": ["The keyboard is slick and quiet and not bulky like some other laptops I have had in the past ."], "output": "[['keyboard', 'slick', 'positive'], ['keyboard', 'quiet', 'positive'], ['keyboard', 'not bulky', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 laptop is definitely a keeper with its simple yet stylish design and its array of fantastic colors to choose from ."], "output": "[['design', 'stylish', 'positive'], ['colors', '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": ["First the screen goes completely out ."], "output": "[['screen', 'completely out', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The PhotoBooth is a great program , it takes very good pictures with the built-in camera ."], "output": "[['PhotoBooth', 'great', 'positive'], ['program', 'great', 'positive'], ['built-in camera', '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": ["Many kinds of software that is necessary to the working person is not available and can not be downloaded ."], "output": "[['software', 'not available', 'negative'], ['software', 'can not be downloaded', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bluescreened on me without any warning , running simply basic Chrome ."], "output": "[['Chrome', 'basic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 researched and found the best price at MacConnection ."], "output": "[['price', '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": ["But guess what ? ( you have to buy an external dvd drive it does n't have a built in type ) The notebook ca n't be used because it does n't read anything for an external drive ."], "output": "[['external dvd drive', \"does n't have\", 'negative'], ['external drive', \"does n't read\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["GET THIS COMPUTER FOR PORTABILITY AND FAST PROCESSING ! ! !"], "output": "[['PROCESSING', '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 use a cooling pad but it does n't help ."], "output": "[['cooling pad', \"does n't 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": ["Supplied software : The software that comes with this machine is greatly welcomed compared to what Windows comes with ."], "output": "[['Supplied software', 'greatly welcomed', 'neutral'], ['software', 'greatly welcomed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tired of the inept service ."], "output": "[['service', 'tired 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": ["Garageband is easy to work with , like all the other apple applications I 've had experience with ."], "output": "[['Garageband', 'easy', 'positive'], ['apple applications', '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": ["No , tey do n't even support their own bios and it `` could be a problem with the bios '' How can a company that makes a fairly decent product get away with such insanity ? ? ! !"], "output": "[['bios', \"do n't even support\", 'negative'], ['bios', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 laptop looked brand new and was shipped very quickly ."], "output": "[['shipped', '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": ["Info : Windows failed to load because the kernal is missing , or corrupt ."], "output": "[['Windows', 'failed', 'negative'], ['kernal', 'missing', 'negative'], ['kernal', 'corrupt', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The display on this computer is the best I 've seen in a very long time , the battery life is very long and very convenient ."], "output": "[['display', 'best', 'positive'], ['battery life', 'long', 'positive'], ['battery life', '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": ["But the quality , in general was less than the worth of the cheap laptop ."], "output": "[['quality', 'less than the 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": ["In the first moth of owning this computer its hardrive failed which had to be replaced ."], "output": "[['hardrive', 'failed', 'negative'], ['hardrive', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 upgraded memory , the MacBook Pro never has an issue running many many applications at once !"], "output": "[['upgraded memory', 'never has an issue', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to use , and great graphics ."], "output": "[['graphics', 'great', '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": ["The internet speed is spectacular ."], "output": "[['internet speed', '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": ["They claim call center is still down ."], "output": "[['call center', '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": ["Mac also has many apps and programs that are quite cheap or free ."], "output": "[['apps', 'cheap', 'positive'], ['apps', 'free', 'positive'], ['programs', 'cheap', 'positive'], ['programs', '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": ["My husband uses it mostly for games , email and music ."], "output": "[['games', 'mostly', '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": ["Apparently under the screen there are 2 little screws and when the screen gets moved back and forth , they come loose ."], "output": "[['screen', 'loose', '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": ["Downfalls : sharp edges ."], "output": "[['edges', 'Downfalls', 'negative'], ['edges', 'sharp', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it four months when my disc drive refused to open ."], "output": "[['disc drive', 'refused to open', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , after Apple replaced the hard drive I enjoyed another 4 months of my new computer , until it froze this morning -- completely ."], "output": "[['hard drive', 'replaced', 'neutral'], ['hard drive', 'enjoyed', 'neutral'], ['hard drive', 'froze', '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": ["Once again , I was told it was the suspicious power supply problem ."], "output": "[['power supply', 'suspicious', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Unable to boot up this brand new laptop ."], "output": "[['boot up', 'Unable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , all the design tools on Pages and Keynotes makes it much easier to create professional looking documents and presentations ."], "output": "[['Pages', 'easier', 'positive'], ['Pages', 'professional', 'positive'], ['Keynotes', 'easier', 'positive'], ['Keynotes', '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": ["I actually had the hard drive replaced twice , the mother board once , the dvd drive twice , then they FINALLY agreed to replace it , ( ALL OF THIS IN LESS THAN 1 1/2 YEARS !"], "output": "[['hard drive', 'replaced', 'negative'], ['mother board', 'replaced', 'negative'], ['dvd drive', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 feel of the key board , as well as the trackpad ."], "output": "[['key board', 'love', '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": ["Now I have the best of both worlds with all of the power and ease of the Mac !"], "output": "[['power', 'best', 'positive'], ['ease', '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": ["Ease of use is just one of the benefits I love about my Mac ."], "output": "[['use', 'Ease', 'positive'], ['use', 'benefits', 'positive'], ['use', '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": ["Now the machine wo n't connect and Toshiba says that they did replace the connection card in May but they only warranty the repair for 30 days and now I 'm out of warranty even though this has been a constant 5 month occurance since I bought the netbook ."], "output": "[['connection card', 'replace', '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": ["Browsing , also , was no problem for me when I used itunes ( which usually slows down my PC ) ."], "output": "[['Browsing', 'no 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": ["Again , decent comp for the price , and I was in need of one quickly as my other laptop died on me ."], "output": "[['price', '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": ["Toshiba customer services will indirectly deal with your problems by constantly tranferring you from one country to another , and I am not kidding you , I called different hours of the day and you 'll get someone else from another country trying to get you to tell them your life story all over again , since they make it sound like they do n't have your history list of your calls right in front of them ."], "output": "[['Toshiba customer services', 'indirectly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Quality Display I was surprised with the performance and quality of this HP Laptop ."], "output": "[['Quality Display', 'surprised', 'positive'], ['performance', 'surprised', 'positive'], ['quality', '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": ["The battery life also does n't keep up with the claim but still I think macbook is much ahead from the rest of the pack ."], "output": "[['battery life', \"does n't\", 'negative'], ['battery life', 'much ahead', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The internet capabilities are also very strong and picks up signals very easily ."], "output": "[['internet capabilities', 'strong', 'positive'], ['internet capabilities', 'easily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , has High definition quality in the videos ."], "output": "[['High definition quality', '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": ["Another Great thing is the Beast graphics ."], "output": "[['Beast graphics', '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 ease of set up was terrific ."], "output": "[['set up', 'ease', 'positive'], ['set up', '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": ["Everything I have tried has worked and I never have to carry the wall charger cause the battery is so awesome ."], "output": "[['battery', '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": ["Screen size is perfect for portable use in any environment ."], "output": "[['Screen 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": ["I used to build my own desktops from the component parts , and recently my 7 year old Pentium 4 with HT 1 GB ram SATA desktop stopped working ( this was a rock star 7 years ago ) ."], "output": "[['Pentium 4', 'stopped working', 'neutral'], ['1 GB ram', 'stopped working', '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 printing from either word processor is an adventure ."], "output": "[['word processor', 'adventure', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 purchasing this thing , I find out that I need a special interface device to connect my camera , and that it can not be purchased at the store - only on line ."], "output": "[['interface device', 'special', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 included program that is laughable is the chess game ."], "output": "[['included program', 'laughable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , I thought the expese was a little much , but I now realize you get what you pay for ."], "output": "[['expese', '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": ["It works great for general internet use , Microsoft Office apps , home bookkeeping , etc ."], "output": "[['Microsoft Office apps', 'great', 'positive'], ['internet use', '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 price was very good , and the product is top quality ."], "output": "[['price', 'good', 'positive'], ['quality', '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": ["It played various games without problems and ran aero smoothly and flawlessly ."], "output": "[['games', 'without problems', 'neutral'], ['aero', 'smoothly', 'neutral'], ['aero', 'flawlessly', '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": ["After replacing the hard drive the battery stopped working ( 3 months of use ) which was frustrating ."], "output": "[['hard drive', 'replacing', 'neutral'], ['battery', 'stopped 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": ["From the get-go , the M6809 was unsteady in its operation ;"], "output": "[['operation', 'unsteady', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 small enough where I can take it pretty much anywhere , but still has a big enough screen to get everything done ."], "output": "[['screen', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 even has a great webcam , and Skype works very well ."], "output": "[['webcam', 'great', 'positive'], ['Skype', '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": ["This computer I used daily nice compact design ."], "output": "[['design', 'nice compact', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The ATI graphics card is a huge plus , definitely a good value if you need to be able to run some slightly older games that a Intel built-in card would have trouble with , such as Half-Life 2 or even World of Warcraft ."], "output": "[['ATI graphics card', 'huge plus', 'positive'], ['Intel built-in card', 'trouble', 'positive'], ['games', 'older', '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 hard to handle and operate at school ."], "output": "[['handle', 'hard', 'negative'], ['operate', 'hard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 preferred the fit and feel of the 13 inch ."], "output": "[['13 inch', 'preferred', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["power supply went bad after 2 weeks --"], "output": "[['power supply', '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 screen takes some getting use to , because it is smaller than the laptop ."], "output": "[['screen', 'smaller', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 regret buying it before understanding how awful it is to use ."], "output": "[['use', '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 right speaker did not work ."], "output": "[['right speaker', '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": ["Dealing with the support drone on the other end of the chat was sheer torture ."], "output": "[['support', 'sheer torture', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Final Cut Pro on this laptop is so fast and easy , and I can use this to seemlessly transfer all my work to my home computer , which is also a mac ."], "output": "[['Final Cut Pro', 'fast', 'positive'], ['Final Cut Pro', '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 computer runs extremely slowly , whether opening Word or My Computer ."], "output": "[['runs', 'slowly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is nice and the images comes very clear , the keyboard and the fit just feels right ."], "output": "[['screen', 'nice', 'positive'], ['keyboard', 'right', 'positive'], ['fit', '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": ["But sitting on a lap or on a desk in front of you it looks more than big enough ( this could be because Im used to my Lenovo 10 tablet now ) plus this is a great size if I want to unplug the external keyboard , mouse , and monitor to take it with me when I take photos and video ."], "output": "[['size', '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 only objection I have is that after you buy it the windows 7 system is a starter and charges for the upgrade ."], "output": "[['windows 7 system', 'objection', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wheel that turns the volume up and down does n't work in real time ."], "output": "[['wheel', \"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": ["I can not be happier with the service or product ."], "output": "[['service', 'can not be 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": ["I do transcription work on the side , and the flatline keyboard makes typing quick and easy as well ."], "output": "[['flatline keyboard', 'quick', 'positive'], ['flatline keyboard', '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": ["Speakers does n't sound that great ."], "output": "[['Speakers', \"does n't sound that great\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The `` abuse '' is that I pushed the power plug in too hard ."], "output": "[['power plug', 'too hard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The resolution on the screen is almost pure HD ."], "output": "[['resolution on the screen', 'pure HD', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Internet Explorer was very slow from the very beginning ."], "output": "[['Internet Explorer', '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 AC power port becomes loose over time"], "output": "[['AC power port', 'loose', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a user of a PC , I will will admit that the macBook Pro has a better running system in which I found myself `` Getting the job done quicker ."], "output": "[['running system', '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": ["There are no gold key numbers too intall programs , you must use the serial numbers that it does not accept and then things are limited as far a working because they are only good for a short time ."], "output": "[['programs', '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": ["and they replaced the awesome ergonomic small lightweight power supply with a power supply that weighed more than the machine itself ."], "output": "[['power supply', 'lightweight', 'negative'], ['power supply', 'weighed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 that Toshib force and durability unparalleled"], "output": "[['force', 'Enjoy', 'positive'], ['durability', 'Enjoy', 'positive'], ['durability', 'unparalleled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 is great I am running Vista Business and scored a 5.X on the index I have never seen a windows machine have a total score in the 5 's ."], "output": "[['Vista Business', '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 love the size of the screen , although it is still lightweight and very easy to tote around ."], "output": "[['size of the screen', 'love', 'positive'], ['tote', '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 battery is irreplaceable ."], "output": "[['battery', 'irreplaceable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really been big on downloading anything so I was n't too worried about getting a virus , plus I thought I was protected by Norton ."], "output": "[['Norton', 'protected', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The internet was locekd and froze every time it was trying to be used , and the command prompt would not work at all ."], "output": "[['internet', 'locekd', 'negative'], ['internet', 'froze', 'negative'], ['command prompt', '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": ["It 's software and speed enable it to do amazing things ."], "output": "[['software', 'amazing', 'positive'], ['speed', '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": ["Could not keep up with me and finally the hard drive went out ."], "output": "[['hard drive', 'went out', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 most impressed with the programming , including the iPhoto ."], "output": "[['programming', 'impressed', 'positive'], ['iPhoto', '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": ["Speakers too small to be of any real use ."], "output": "[['Speakers', '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": ["I upgraded it 's RAM to 2GB , I am very happy with it ."], "output": "[['RAM', 'upgraded', 'positive'], ['RAM', '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": ["They should have included more memory on their computers if they knew Vista would run slowly ."], "output": "[['memory', 'more', 'negative'], ['Vista', 'slowly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Battery life could be better but overall for the price and Toshiba 's reputation for laptops it 's great !"], "output": "[['Battery life', 'could be better', 'negative'], ['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": ["The battery never held a charge longer than one hour and within two months , stopped holding a charge for more than ten minutes ."], "output": "[['battery', 'never', 'negative'], ['charge', 'longer', 'negative'], ['charge', 'stopped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the warrenty expired the hard drive went bad and it would have cost more to fix then to replace ."], "output": "[['hard drive', '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 neat and organized icon list is a welcome change from cluttered and confusing desktop icons ."], "output": "[['icon list', 'neat', 'positive'], ['icon list', 'organized', 'positive'], ['icon list', 'welcome', 'positive'], ['desktop icons', 'cluttered', 'negative'], ['desktop icons', '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": ["Apparently well -- built and gorgeous to look at , the i5 MacBook Pro is a winning combination of price and performance ."], "output": "[['price', 'winning', 'positive'], ['performance', 'winning', 'positive'], ['built', 'well', 'positive'], ['look', '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 apple care has never failed me , and I expect it to be the same for this computer as well ."], "output": "[['apple care', 'never failed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Toshiba laptop I am using is easier to use than most I have tried ."], "output": "[['use', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 size , keyboard , the functions ."], "output": "[['size', 'love', 'positive'], ['keyboard', 'love', 'positive'], ['functions', '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 mouse is way way way too sensitive ."], "output": "[['mouse', 'too 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": ["Also , I issued a replacement RMA for a few dead pixels in the upper zone of the screen , which is noticable to me ."], "output": "[['screen', 'noticable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 reports the notebook is astonishing in performance , picture quality , and ease of use ."], "output": "[['performance', 'astonishing', 'positive'], ['picture quality', 'astonishing', 'positive'], ['use', 'ease', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the i3 processor does n't seem to run hot and the fan rarely turns on ."], "output": "[['i3 processor', \"does n't seem to run hot\", 'positive'], ['fan', 'rarely turns on', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["See when it comes to laptops you buy it and get just a normal operating system with trials of must need stuff that should come with it ."], "output": "[['operating system', 'normal', '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 do n't understand is that the resolution of the screen is n't high enough for some pages , such as Yahoo ! Mail ."], "output": "[['resolution of the screen', \"is n't high enough\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 convenient when you travel and the battery life is excellent ..."], "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": ["The machine is slow to boot up and occasionally crashes completely ."], "output": "[['boot up', 'slow', 'negative'], ['boot up', 'crashes', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 brightness automatically adjusts ."], "output": "[['screen brightness', 'automatically adjusts', '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": ["Besides the great look , it is a great machine ."], "output": "[['look', '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 sound is a bit quiet if you 're on a plane , this can easily be overcome with a decent pair of head phones ."], "output": "[['sound', 'quiet', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Right size and weight for portability ."], "output": "[['size', 'Right', 'positive'], ['weight', 'Right', 'positive'], ['portability', '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 battery life also does n't keep up with the claim but still I think macbook is much ahead from the rest of the pack ."], "output": "[['battery life', \"does n't keep up with the claim\", 'negative'], ['battery life', 'much ahead', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The reflectiveness of the display is only a minor inconvenience if you work in a controlled-lighting environment like me ( I prefer it dark ) or if you can crank up the brightness ."], "output": "[['display', 'minor inconvenience', 'negative'], ['brightness', 'crank up', '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 with this laptop is that I 've noticed an electronic fuzz sound coming out of the headphone jack when headphones are plugged in ."], "output": "[['electronic fuzz sound', 'complaint', 'negative'], ['headphone jack', '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": ["While it was highly rated , would I like it ? I tried the keyboard at the store , and it seemed ok ."], "output": "[['keyboard', '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": ["Treat yourself to a more expensive , long-lasting laptop of quality like a Sony , Apple , or Toshiba ."], "output": "[['quality', 'long-lasting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 problem with the ordering or shipping by the way ."], "output": "[['shipping', 'No 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": ["And the ram ( the thing that makes it faster ) comes sporting 2 gigs for high performance to handle more stuff at once and surf the web a whole lot faster than before ."], "output": "[['ram', 'faster', 'positive'], ['performance', 'high', 'positive'], ['surf the web', 'faster', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 edit and burn to DVD a lot of video , so I obviously could not live with a non-functioning drive ."], "output": "[['drive', 'could not live', 'negative'], ['drive', 'non-functioning', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 visual !"], "output": "[['visual', 'Fast', 'positive'], ['visual', '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 priced very reasonable and works very well right out of the box ."], "output": "[['priced', 'reasonable', 'positive'], ['works', '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": ["while the keyboard itself is alright , the plate around it is cheap plastic and makes a hollow sound when using the mouse command buttons ."], "output": "[['keyboard', 'alright', 'positive'], ['plate', 'cheap', 'negative'], ['mouse command buttons', 'hollow sound', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 are so many wonderful features and benefits to the new MacBook !"], "output": "[['features', 'wonderful', 'positive'], ['features', 'benefits', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 can say is that the touch pad doesnt work like it should all the time ."], "output": "[['touch pad', 'doesnt 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": ["For some odd reasons the computer does n't recognize the operation system ."], "output": "[['operation system', \"does n't recognize\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The trackpad was easy to learn and navigate ."], "output": "[['trackpad', '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": ["Applications open in seconds and there are no lags , hiccups or awkward moments when you wonder whether your computer is out for tea ."], "output": "[['Applications', 'open in seconds', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 respond that I do not have the old computer and this way I would lose the data on my hard drive ."], "output": "[['hard drive', 'lose', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Again in February my computer completely failed to the point that it could not load Windows so I contacted Acer to get it fixed thru my Warrenty and it took about 3 days fighting on the phone with agents and it seemed as though NONE of them spoke English ."], "output": "[['Windows', 'failed', 'neutral'], ['Windows', 'could not load', '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": ["Even though the computer is larger they did not make the keyboard larger ."], "output": "[['keyboard', 'not', 'negative'], ['keyboard', '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": ["Its not just slow on the internet , its slow in general ."], "output": "[['internet', '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": ["It has just enough RAM to run smoothly and enough memory to satisfy my needs ."], "output": "[['RAM', 'enough', 'positive'], ['memory', 'smoothly', 'positive'], ['memory', '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": ["I acually believe the issue is with the Nvidia grafics card , but still requires a return ."], "output": "[['Nvidia grafics card', '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": ["It is VERY easy to type on and feels great - besides the added feature that the keyboard is lighted ."], "output": "[['keyboard', 'lighted', 'positive'], ['feature', 'added', 'positive'], ['type', 'easy', 'positive'], ['type', '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 feel of this machine compared to the old MacBook is far superior ."], "output": "[['feel', '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": ["In due course , I 'll remove the hard disc from this new MacBook Pro and dump it where it belongs - in the trash ."], "output": "[['hard disc', 'remove', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 break down just as often as PCs do , and the only reason they do n't get viruses , is because no one makes viruses for them , they 're not better in any way , they are worse , try finding virus protection programs for a Mac , they do n't exist ."], "output": "[['virus protection programs for a Mac', 'not better', 'negative'], ['virus protection programs for a Mac', 'worse', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The overall build quality of the unit is excellent and she 'd recommend it to anyone else looking for a netbook ."], "output": "[['build quality', 'excellent', 'positive'], ['build quality', '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 repairs were made quickly though I must say , however the second time they shipped it to the incorrect address and it took nearly a week for them to get it to me ."], "output": "[['shipped', 'incorrect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 i have not had a problem with internet connection or any other problems ."], "output": "[['internet connection', 'fast', 'positive'], ['internet connection', 'not had a 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": ["I 'm really impressed with the quality and performance for the price of the computer ."], "output": "[['quality', 'impressed', 'positive'], ['performance', 'impressed', 'positive'], ['price', '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": ["It is so simple to use , I use it more than my desktop ."], "output": "[['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": ["I also had a problem with the touchpad that caused the mouse pointer to jump all over the screen ."], "output": "[['touchpad', 'problem', 'negative'], ['screen', 'problem', 'neutral'], ['mouse pointer', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["EITHER WAY , THE KEYBOARD IS UNSATISFACTORY ."], "output": "[['KEYBOARD', 'UNSATISFACTORY .', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , I have to say since I bought my Mac , I wo n't ever go back to any Windows ."], "output": "[['Windows', \"wo n't ever go back\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it in to the Apple store and guess what ? They fixed it , no cost out of pocket ."], "output": "[['cost', '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": ["The quality , engineering design and warranty are superior -- covers damage from dropping the laptop ."], "output": "[['quality', 'superior', 'positive'], ['engineering design', 'superior', 'positive'], ['warranty', '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": ["The applications are also very easy to find and maneuver , much easier than any other computer I have ever owned ."], "output": "[['applications', 'easy', 'positive'], ['applications', 'easier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The large screen gives you the option to comfortably watch movies or TV shows on your computer instead of buying an additional TV for your dorm room ."], "output": "[['screen', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 laptop for school , easy to use for beginners in the household ."], "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": ["4 ) Laptop still did not work , blue screen within a week ..."], "output": "[['work', '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 only thing that is n't perfect about this netbook is the speakers , they are not loud at all but I expected that ."], "output": "[['speakers', \"is n't perfect\", 'negative'], ['speakers', 'not loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Of course , I inspected the other netbooks and clearly their hinges are tighter and I even demonstrate the difference between my netbook and others ."], "output": "[['hinges', 'clearly', 'negative'], ['hinges', 'tighter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 n't work when shipped from Walmart.com but went into a store and exchanged for a working laptop ( same make/model ) ."], "output": "[['work', \"Did n't\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 programs ( Keynote , Pages , Numbers ) have an option to save your documents as Microsoft compatible , which really eliminates the need for the actual ."], "output": "[['Numbers', 'eliminates', '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": ["Sure , the initial out of pocket expense is greater , but that should not dissuade anyone from the fact that these machines run like none other on the planet , and when I factor in all the money in that I wasted on Geek Squad and the latest patches to de-corrupt my infested PCs , it probably comes out about even anyhow ."], "output": "[['expense', 'greater', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 thing to do is build your own computer , but if u ca n't company 's like dell who allow you to choose the components are better and for the same price you can get a computer who compares to one of apple $ 2000 systems and if you google `` dell coupons '' you can find codes that take a significant amount off the price ."], "output": "[['components', '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": ["There is no cd drive on the computer , which defeats the purpose of keeping files on a cd ."], "output": "[['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": ["Unfortunately , Apple 's quality has continued to slide ."], "output": "[['quality', 'Unfortunately', 'negative'], ['quality', 'slide', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 believe that the quality of a mac is worth the price ."], "output": "[['quality', 'worth', '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": ["sometimes you will be moving your finger and the pointer will not even move ."], "output": "[['pointer', 'not even move', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The 13 '' Macbook Pro just fits in my budget and with free shipping and no tax to CA this is the best price we can get for a great product ."], "output": "[['shipping', 'free', 'positive'], ['price', 'best', 'positive'], ['budget', 'fits', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 rate this computer at 5 stars , but considering it has a short life span I can only give it 1 and implore anyone looking at laptops to stay away from this machine ."], "output": "[['life span', '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": ["I also love the design , the looks , the feel , and the my toshiba feature is wonderfull ."], "output": "[['design', 'love', 'positive'], ['looks', 'love', 'positive'], ['feel', 'love', 'positive'], ['my toshiba feature', 'wonderfull', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it is very good for college students who just need a reliable , easy to use computer ."], "output": "[['use', 'good', 'positive'], ['use', 'reliable', 'positive'], ['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": ["Only other thing is that if you are using this for document creation Apple doesnt provide any kind of word processor ( such as works for windows ) , but iwork is cheap compared to office ."], "output": "[['iwork', 'cheap', 'positive'], ['word processor', 'doesnt 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": ["It is light and the battery last a very long time ."], "output": "[['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": ["And at one point , they blame me for installing a bad memory stick when I upgrade my memory for the first time during my purchase of the laptop ( I bought the memory stick they recomended ) ."], "output": "[['memory stick', 'bad', '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": ["Externally the keys on my keyboard are falling off , after a few uses the paint is rubbing off the button below the mouse pad and where the heals of my hands sit , and the screen has a terrible glare ."], "output": "[['keys', 'falling off', 'negative'], ['keyboard', 'falling off', 'negative'], ['button below the mouse pad', 'rubbing off', 'negative'], ['screen', 'terrible glare', 'negative'], ['paint', 'rubbing off', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The next time I had an issue my lightscribe would n't work ."], "output": "[['lightscribe', \"would 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 touchpad is extremely sensitive , which is the only drawback ."], "output": "[['touchpad', 'sensitive', 'negative'], ['touchpad', 'drawback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it comes with very useful applications like iphoto that it is the best photo application i have ever had"], "output": "[['applications', 'useful', 'positive'], ['iphoto', 'useful', 'positive'], ['iphoto', 'best', 'positive'], ['photo application', '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 acer one computer that I bought is 17 ince screen and its hard to find lap top bags for it , but I like the big screen on it ."], "output": "[['17 ince screen', 'hard', 'neutral'], ['screen', 'like', 'positive'], ['screen', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 have both OSX and Windows XP running at the same time !"], "output": "[['OSX', 'both', 'positive'], ['Windows XP', 'both', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Microsoft seems to be unable to keep up with repairs for the multitude of windows problems ."], "output": "[['windows', '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": ["You can call HP and they want you to buy more software to fix it ."], "output": "[['software', 'fix', '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 easy to navigate and update programs ."], "output": "[['update programs', 'easy', 'neutral'], ['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": ["All in all , a very disappointing experience except that I learned how good the Geek Squad is and also Customer Service ."], "output": "[['Customer Service', 'disappointing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The laptop is very lightweight , can easily carry around in a knapsack full of text books and it barely adds any weight ."], "output": "[['carry', 'easily', 'positive'], ['weight', 'lightweight', 'positive'], ['weight', 'barely adds', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 did not like the loud noises it made or how the bottom of the computer would get really hot ."], "output": "[['noises', 'not like', 'negative'], ['noises', 'loud', 'negative'], ['bottom of the computer', 'hot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 in the past a Dell laptop and they sent me the items it needed or they sent a repair technician to my house to fix it ."], "output": "[['repair technician', 'fix', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["defective software ."], "output": "[['software', 'defective', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was so challenging to carry and handle ."], "output": "[['carry', 'challenging', 'negative'], ['handle', 'challenging', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cords coming out the right for power plus cords coming out front for headphones/mic plus network connection on left make for a very messy setup with cords going every direction ."], "output": "[['setup', 'messy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Unless you want to be inconvenienced with a non working power supply which you ca n't find a replacement for because they made the attachment so small ."], "output": "[['power supply', 'inconvenienced', 'negative'], ['power supply', 'non 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 is much faster than my desktop which is a Core2 Quad running at 2.83 GHz ."], "output": "[['Core2 Quad', 'faster', '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 good to know that I can mobilize without having to worry about the battery life ."], "output": "[['battery life', 'without having to worry about', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is nice , side view angles are pretty good ."], "output": "[['screen', 'nice', 'positive'], ['screen', '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 fact that the screen reacts to the lighting around you is an added luxury -when you are working around others in dark areas and want privacy or do n't want to bother them with bright lighting , it is very convenient to have a darker , softer lit screen ."], "output": "[['screen', 'added luxury', 'positive'], ['screen', 'softer lit', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["3 weeks went by and the computer keeps crashing and will not open any applications ."], "output": "[['applications', 'crashing', 'neutral'], ['applications', 'not open', '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": ["Looks nice , but has a horribly cheap feel ."], "output": "[['feel', 'horribly cheap', 'negative'], ['Looks', '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 feel of this is better than the Toshiba , too ."], "output": "[['feel', '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 would recommend this laptop to anyone looking to get a new laptop who is willing to spend a little more money to get great quality !"], "output": "[['quality', 'recommend', '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": ["I upgraded the memory and replaced the base Windows 7 Starter to Win 7 Home , and it runs just fine ."], "output": "[['memory', 'upgraded', 'neutral'], ['memory', 'fine', 'neutral'], ['Windows 7 Starter', 'replaced', 'neutral'], ['Win 7 Home', 'fine', 'neutral'], ['runs', '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 am not sure if it was the drive itself , however ;"], "output": "[['drive', '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": ["Also , one of the users mentioned how the edges on the macbook is sharp , if you have money to spend on one of the incase shells , it does n't seem to be a problem ."], "output": "[['edges', 'sharp', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 easy to use , its keyboard easily accommodates large hands , and its weight is fantastic ."], "output": "[['keyboard', 'easily accommodates', 'positive'], ['weight', 'fantastic', 'positive'], ['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": ["Called Acer many times , they want me to pay the shipping to ship it to their repair center - I was very disappointed since it is a brand new computer !"], "output": "[['shipping', 'disappointed', 'negative'], ['repair center', 'disappointed', '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 battery is really long ."], "output": "[['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": ["Had some trouble finding a case that it would fit in ."], "output": "[['case', 'trouble', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 that I have has had issues with the keyboard where it lost half the keyboard functions ."], "output": "[['keyboard', 'issues', 'negative'], ['keyboard functions', 'lost', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 called Sony the 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": ["It is a much more streamlined system for adding programs , using the internet , and doing other things everyone does on a computer ."], "output": "[['programs', 'adding', 'neutral'], ['system', 'streamlined', 'positive'], ['using the internet', 'streamlined', '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 computer froze on several occasion , had buttons that randomely would fall off and even had moments when the computer would refuse to turn on at all ."], "output": "[['buttons', 'fall off', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 even safe mode boots ."], "output": "[['safe mode', '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": ["This is an over-sized , 18-inch laptop ."], "output": "[['18-inch', 'over-sized', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 pay $ 100 for a universal charger for this cheap $ 300 laptop ."], "output": "[['universal charger', '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 powerpoint opened seamlessly in the apple and the mac hooked up to the projector so easily it was almost scary ."], "output": "[['powerpoint', 'seamlessly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["1.You can not change your desktop background ( window 's 7 starter does NOT support that function ) ."], "output": "[['desktop background', 'can not change', 'negative'], [\"window 's 7 starter\", 'NOT support', 'negative'], ['function', 'NOT support', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 after 4 or so months the charger stopped working so I was forced to go out and buy new hardware just to keep this computer running ."], "output": "[['charger', 'stopped working', 'negative'], ['hardware', 'new', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Strengths : Well -- shaped Weaknesses : A bad videocard !"], "output": "[['videocard', 'Weaknesses', 'negative'], ['videocard', 'bad', 'negative'], ['shaped', '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": ["You ca n't even get a satellite card which is why I bought to begin with ."], "output": "[['satellite card', \"ca n't even get\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 REAL touchpad , not the toy I saw in other brands ."], "output": "[['touchpad', 'REAL', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 and purpose is awesome !"], "output": "[['Price', '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": ["Wonderful zooming ."], "output": "[['zooming', '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 screen is huge and colorful , but no LED backlighting ."], "output": "[['screen', 'huge', 'positive'], ['screen', 'colorful', 'positive'], ['screen', 'no LED backlighting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 all honesty , if someone is looking for a quality laptop and willing to pay a little more money for a normal sized laptop than a cheaper and less impressive laptop , then do not buy this computer ."], "output": "[['sized', 'normal', '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 about this computer is 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": ["Worse , for the price I could get a *netbook* that outperforms this machine ."], "output": "[['price', 'Worse', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was also very nice and had a solid feel ."], "output": "[['Keyboard', 'nice', 'positive'], ['Keyboard', '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": ["It did not have all the features I expected it to have ."], "output": "[['features', 'did not have', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 luck , although I waited for hours on the phone-Visited MacHouse , they stated the their call center is down due to too many phonecalls ( difficult to believe ) ."], "output": "[['call center', '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": ["There is a backlit keyboard which is perfect for typing in the dark ."], "output": "[['backlit keyboard', '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": ["It has a lot of memory and a great battery life ."], "output": "[['memory', 'a lot of', 'positive'], ['battery life', '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 spoke with a service rep at Micro Center and his girlfriend is having the same problem with her power adapter , so it 's not just an isolated incident ! ! !"], "output": "[['power adapter', 'problem', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 program , it is superior to windows movie maker ."], "output": "[['program', 'love', 'positive'], ['program', '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": ["He has replaced his hard drive twice and ( of course ) has had to pay for antivirus software every year ."], "output": "[['hard drive', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 purchase opened me to the world of Macbooks , and I am impressed with the intuition of the design , the beauty of the product , and the excellent technological advances associated with it ."], "output": "[['design', 'impressed', 'positive'], ['beauty', '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 price is great for this model , I only plan on using it for media in the entertainment room ."], "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": ["I 've also had to have the keyboard replaced at my expense ."], "output": "[['keyboard', 'replaced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 staff telling me older version did not make the fan noise cause it is a `` different '' computer ."], "output": "[['fan noise', 'did not make', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 out of warranty !"], "output": "[['warranty', 'out 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": ["Crisp screen , great battery life , and plenty of storage ."], "output": "[['screen', 'Crisp', 'positive'], ['battery life', 'great', 'positive'], ['storage', '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": ["Also , my sister got the exact same laptop ( since they were so cheap ) and after 8 months , the screen split in half just from everyday use ."], "output": "[['screen', 'split', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Toshiba Satellite has been more than I expected for the price ."], "output": "[['price', 'more than I expected', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 adjust my mousepad sensitivity , because it is very sensitive ."], "output": "[['mousepad sensitivity', '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": ["Keyboard is plastic and spongey feeling ."], "output": "[['Keyboard', 'plastic', 'negative'], ['Keyboard', 'spongey feeling', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["previous laptops were pc 's , still have them , but the mac osx is a clean and smooth operating system ."], "output": "[['mac osx', 'clean', 'positive'], ['mac osx', 'smooth', 'positive'], ['operating system', 'clean', 'positive'], ['operating system', '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": ["i also love having the extra calculator number set up on the keyboard which most laptops do not have ."], "output": "[['keyboard', '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 love my Apple , it is quick and easy to use ."], "output": "[['use', 'love', 'positive'], ['use', 'quick', 'positive'], ['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": ["The laptop is relatively simple to use , though I bought Macs for Dummies , which is well worth $ 2"], "output": "[['use', 'simple', 'positive'], ['use', '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": ["No tutorials on the display ."], "output": "[['tutorials', '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": ["The touch pad is among the best ."], "output": "[['touch pad', '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": ["We also use Paralles so we can run virtual machines of Windows XP Professional , Windows 7 Home Premium , Windows Server Enterprise 2003 , and Windows Server 2008 Enterprise ."], "output": "[['Paralles', 'use', 'neutral'], ['Windows XP Professional', 'run', 'neutral'], ['Windows 7 Home Premium', 'run', 'neutral'], ['Windows Server Enterprise 2003', 'run', 'neutral'], ['Windows Server 2008 Enterprise', 'run', '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": ["How Toshiba handles the repair seems to vary , some folks indicate that they were charged for even an intial fix , others had the repair done 5 times ."], "output": "[['repair', 'vary', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 staff was so horrible to us ."], "output": "[['staff', '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": ["To be completely fair , the only redeeming factor was the food , which was above average , but could n't make up for all the other deficiencies of Teodora ."], "output": "[['food', 'above average', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 uniformly exceptional , with a very capable kitchen which will proudly whip up whatever you feel like eating , whether it 's on the menu or not ."], "output": "[['food', 'exceptional', 'positive'], ['kitchen', 'capable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 agreed favorite is the orrechiete with sausage and chicken ( usually the waiters are kind enough to split the dish in half so you get to sample both meats ) ."], "output": "[['orrechiete with sausage and chicken', 'favorite', 'positive'], ['waiters', 'kind', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Bagels have an outstanding taste with a terrific texture , both chewy yet not gummy ."], "output": "[['Bagels', 'outstanding', 'positive'], ['Bagels', 'terrific', 'positive'], ['Bagels', 'chewy', 'positive'], ['Bagels', 'gummy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Nevertheless the food itself is pretty 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": ["They did not have mayonnaise , forgot our toast , left out ingredients ( ie cheese in an omelet ) , below hot temperatures and the bacon was so over cooked it crumbled on the plate when you touched it ."], "output": "[['toast', 'forgot', 'negative'], ['bacon', 'over cooked', 'negative'], ['cheese', 'left out', 'neutral'], ['ingredients', 'left out', 'negative'], ['plate', 'over cooked', 'neutral'], ['omelet', 'left out', '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 design and atmosphere is just as good ."], "output": "[['design', '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": ["The seats are uncomfortable if you are sitting against the wall on wooden benches ."], "output": "[['seats', '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": ["My suggestion is to eat family style because you 'll want to try the other dishes ."], "output": "[['eat family style', 'suggestion', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 of all is the warm vibe , the owner is super friendly and service is fast ."], "output": "[['vibe', 'warm', 'positive'], ['owner', 'friendly', 'positive'], ['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": ["Faan 's got a great concept but a little rough on the delivery ."], "output": "[['delivery', 'rough', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 incredible food , to the warm atmosphere , to the friendly service , this downtown neighborhood spot does n't miss a beat ."], "output": "[['food', 'incredible', 'positive'], ['atmosphere', 'warm', '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": ["Great food at REASONABLE prices , makes for an evening that ca n't be beat !"], "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": ["this little place has a cute interior decor and affordable city prices ."], "output": "[['interior decor', 'cute', 'positive'], ['prices', '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": ["Two words : Free wine ."], "output": "[['wine', '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": ["The price is reasonable although the service is poor ."], "output": "[['price', 'reasonable', '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": ["The quantity is also very good , you will come out satisfied ."], "output": "[['quantity', 'good', 'positive'], ['quantity', '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": ["The fried rice is amazing here ."], "output": "[['fried rice', '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": ["Three courses - choices include excellent mussels , puff pastry goat cheese and salad with a delicious dressing , and a hanger steak au poivre that is out of this world ."], "output": "[['mussels', 'excellent', 'positive'], ['puff pastry goat cheese', 'excellent', 'positive'], ['salad with a delicious dressing', 'delicious', 'positive'], ['hanger steak au poivre', '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 place is so cool and the service is prompt and curtious ."], "output": "[['service', 'prompt', 'positive'], ['service', 'curtious', 'positive'], ['place', '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": ["At the end you 're left with a mild broth with noodles that you can slurp out of a cup ."], "output": "[['broth with noodles', 'mild', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 wonder how you can have such a delicious meal for such little money ."], "output": "[['meal', 'delicious', 'positive'], ['money', '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": ["The wine list is excellent ."], "output": "[['wine list', '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": ["Ive been to many Thai restaurants in Manhattan before , and Toons is by far the best Thai food Ive had ( except for my mom 's of course ) ."], "output": "[['Thai 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 is a consistently great place to dine for lunch or dinner ."], "output": "[['dine', '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": ["Nice atmosphere , the service was very pleasant and the desert was good ."], "output": "[['atmosphere', 'Nice', 'positive'], ['service', 'pleasant', 'positive'], ['desert', '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": ["After really enjoying ourselves at the bar we sat down at a table and had dinner ."], "output": "[['bar', 'enjoying', 'positive'], ['table', 'enjoying', 'neutral'], ['dinner', 'enjoying', '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 liked the beer selection !"], "output": "[['beer selection', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 size menu , great service and an unpretentious setting ."], "output": "[['food', 'Great', 'positive'], ['menu', 'good', 'positive'], ['service', 'great', 'positive'], ['setting', 'unpretentious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wine list selection is good and wine-by-the-glass was generously filled to the top ."], "output": "[['Wine list selection', 'good', 'positive'], ['wine-by-the-glass', 'generously filled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 very limited - i think we counted 4 or 5 entrees ."], "output": "[['menu', '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": ["The menu is limited but almost all of the dishes are excellent ."], "output": "[['menu', 'limited', 'negative'], ['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": ["Great bagels , spreads and a good place to hang out in ."], "output": "[['bagels', 'Great', 'positive'], ['spreads', '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": ["Unfortunately , the food is outstanding , but everything else about this restaurant is the pits ."], "output": "[['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": ["We always have a delicious meal and always leave feeling satisfied ."], "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": ["First went here to enjoy their garden terrace ."], "output": "[['garden terrace', '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 pizza was pretty good and huge ."], "output": "[['pizza', 'good', 'positive'], ['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": ["The cuisine from what I 've gathered is authentic Taiwanese , though its very different from what I 've been accustomed to in Taipei ."], "output": "[['cuisine', 'different', '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 almost hesititate to write a review because the atmosphere was so great and I would hate for it too become to crowded ."], "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": ["They are often crowded on the weekends but they are efficient and accurate with their service ."], "output": "[['service', 'efficient', 'positive'], ['service', 'accurate', 'positive'], ['crowded', '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": ["The atmosphere is unheralded , the service impeccable , and the food magnificant ."], "output": "[['atmosphere', 'unheralded', 'positive'], ['service', 'impeccable', 'positive'], ['food', 'magnificant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the special , grilled branzino , that was so infused with bone , it was difficult to eat ."], "output": "[['grilled branzino', 'difficult to 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": ["Right off the L in Brooklyn this is a nice cozy place with good pizza ."], "output": "[['pizza', 'good', 'positive'], ['place', 'nice 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": ["Le Pere Pinard has a $ 15 pre-theater menu that is outstanding ."], "output": "[['pre-theater menu', '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 strong scents coming from the left and right of me negatively affected my taste buds ."], "output": "[['scents', 'strong', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the lobster sandwich and it was FANTASTIC ."], "output": "[['lobster sandwich', '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": ["Though the Spider Roll may look like a challenge to eat , with soft shell crab hanging out of the roll , it is well worth the price you pay for them ."], "output": "[['price', 'well worth', 'positive'], ['shell crab', 'soft', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Deep Fried Skewers are good and still rare to find in NYC ."], "output": "[['Deep Fried Skewers', 'good', 'positive'], ['Deep Fried Skewers', 'rare', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 rice dishes or the different varieties of congee ( rice porridge ) ."], "output": "[['rice dishes', 'recommend', 'positive'], ['congee ( rice porridge )', '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": ["Their tuna tartar appetizer is to die for ."], "output": "[['tuna tartar appetizer', '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": ["An oasis of refinement : Food , though somewhat uneven , often reaches the pinnacles of new American fine cuisine - chef 's passion ( and kitchen 's precise execution ) is most evident in the fish dishes and soups ."], "output": "[['chef', 'passion', 'positive'], ['fish dishes', 'evident', 'positive'], ['soups', 'evident', 'positive'], ['kitchen', 'precise execution', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 love wine and cheese and delicious french fare , you 'll love Artisanal !"], "output": "[['wine', 'love', 'positive'], ['french fare', 'love', 'positive'], ['cheese', '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 love Indian food and consider myself to be quite an expert on it ."], "output": "[['Indian 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 lava cake dessert was incredible and I recommend it ."], "output": "[['lava cake dessert', 'incredible', 'positive'], ['lava cake dessert', '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": ["From the terrible service , to the bland food , not to mention the unaccommodating managers , the overall experience was horrible ."], "output": "[['service', 'terrible', 'negative'], ['food', 'bland', 'negative'], ['managers', 'unaccommodating', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Lahore is a great place to duck into late-night when you need some really tasty food on the cheap -- you 'll likely have trouble finishing the amount of food you get for FOUR DOLLARS ."], "output": "[['food', '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": ["good selection of wines ranging from affordable to high end ."], "output": "[['selection of wines', '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": ["Nice restaurant overall , with classic upscale Italian decor ."], "output": "[['Italian decor', 'classic upscale', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 impressed with the food ."], "output": "[['food', 'Not impressed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 dining experience was wonderful !"], "output": "[['dining experience', '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 selection ( by the glass and bottle ) is wonderful and I always recommend that friends make a reservation if they 're going to be in town ."], "output": "[['wine selection', 'wonderful', 'positive'], ['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": ["Order the panang duck , it 's fantastic ."], "output": "[['panang duck', '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": ["Food is usually very good , though ocasionally I wondered about freshmess of raw vegatables in side orders ."], "output": "[['raw vegatables', 'wondered', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the crappy service from two individuals , it 's great ."], "output": "[['service', '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": ["They have authentic Indian at amazin prices ."], "output": "[['Indian', 'authentic', 'positive'], ['prices', 'amazin', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ambiance -- relaxed and stylish ."], "output": "[['Ambiance', 'relaxed', 'positive'], ['Ambiance', 'stylish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 use fancy ingredients , but even fancy ingredients do n't make for good pizza unless someone knows how to get the crust right ."], "output": "[['ingredients', 'fancy', 'positive'], ['pizza', '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": ["and yes Dal Bukhara is so dam good and so are all the kababs ."], "output": "[['kababs', 'good', 'positive'], ['Dal Bukhara', '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 look forward to eating here again"], "output": "[['eating', 'look forward', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Tuk Tuk is one of those comfortable neighborhood joints where you know you will always have a good meal at a fair price ."], "output": "[['meal', 'good', 'positive'], ['price', 'fair', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 glass of Leaping Lizard , a glass of prosecco , and the mussels had everything happy ."], "output": "[['glass of prosecco', 'happy', 'positive'], ['mussels', 'happy', 'positive'], ['glass of Leaping Lizard', '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": ["Food was average and creme brulee was awful - the sugar was charred , not caramelized and smelled of kerosene ."], "output": "[['Food', 'average', 'neutral'], ['creme brulee', 'awful', 'negative'], ['sugar', 'charred', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 always tastes fresh and served promptly ."], "output": "[['food', 'fresh', 'positive'], ['served', 'promptly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 here is delicious ."], "output": "[['pizza', '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": ["This place is really trendi but they have forgotten about the most important part of a restaurant , the food ."], "output": "[['food', 'forgotten', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Hats off to the chef ."], "output": "[['chef', 'Hats off', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 - they use fresh mozzarella instead of the cheap , frozen , shredded cheese common to most pizzaria 's ."], "output": "[['pizza', 'delicious', 'positive'], ['fresh mozzarella', 'fresh', 'positive'], ['cheese', 'cheap', 'negative'], ['cheese', 'frozen', 'negative'], ['cheese', 'shredded', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 an excellent place to relax and the food is one of the best in the city of New York ."], "output": "[['place', 'excellent', '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": ["service is friendly , and never had a problem walking in and getting a table ."], "output": "[['service', 'friendly', 'positive'], ['getting a table', 'never had a 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": ["The atmosphere was crowded but it was a great bistro-type vibe ."], "output": "[['bistro-type 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": ["First off , the waitress was completely unattentive the 2 times we saw her ( odd in a restaurant with 6 tables ) and got our order wrong ."], "output": "[['waitress', 'unattentive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 bland oily ."], "output": "[['food', 'bland 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": ["What is even better , is that the prices are very affordable as well , and the food is really good ."], "output": "[['prices', 'affordable', '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 fish is fresh but the variety of fish is nothing out of ordinary ."], "output": "[['fish', 'fresh', 'positive'], ['variety of fish', 'ordinary', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 favorite meal is a pesto pizza , the house salad , and a good bottle of wine ."], "output": "[['pesto pizza', 'favorite', 'positive'], ['house salad', 'favorite', 'positive'], ['bottle of wine', 'good', 'positive'], ['meal', '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": ["Ambiance and music funky , which I enjoy ."], "output": "[['Ambiance', 'funky', 'positive'], ['Ambiance', 'enjoy', 'positive'], ['music', 'funky', 'positive'], ['music', '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 food , drinks and service are clearly among the best in the city ."], "output": "[['food', 'best', 'positive'], ['drinks', '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": ["Granted the space is smaller than most , it is the best service you will find in even the largest of restaurants ."], "output": "[['space', 'smaller', 'negative'], ['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": ["I love the atmorphere @ peep !"], "output": "[['atmorphere', '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 attentive and her suggestions of menu items was right on the mark ."], "output": "[['service', 'attentive', 'positive'], ['menu items', '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 other night we had the $ 30 three course meal and everything was delicious - if I could of licked the plate clean I would of ."], "output": "[['three course 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": ["Even after getting pushed out by the no-class Famous Ray 's , Sal has risen again to carry on his father 's uncle 's legacies with a smile , true love for his community , and let 's not forget the Outstanding Pizza !"], "output": "[['Pizza', '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 environment is romantic , but the food is horrible , the service is pathetic , and gabriella lies about everything she could ."], "output": "[['environment', 'romantic', 'positive'], ['food', 'horrible', 'negative'], ['service', 'pathetic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 crawfish boiled and despite making a mess , it was a ton of fun and quite tasty as well ."], "output": "[['crawfish boiled', 'fun', 'positive'], ['crawfish boiled', '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": ["What came to our table was burned beyond recognition and stringy ."], "output": "[['table', 'burned', '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 the Pad Thai and the noodles were sticky ."], "output": "[['Pad Thai', 'sticky', 'negative'], ['noodles', 'sticky', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is rude to the point of being offensive ."], "output": "[['hostess', 'rude', 'negative'], ['hostess', '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": ["If you 're craving for Haru 's great food , especially the House Roll , but ca n't stand the wait building outisde , head across the street to their Sake Bar !"], "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": ["A narrow corridor leads to a tiny space where there are three tiny white tiled counters , a great deal of mess ( stacks of bottles , cans ) and a small counter holding 12-14 entrees ."], "output": "[['corridor', 'narrow', 'negative'], ['space', 'tiny', 'negative'], ['counters', 'tiny', 'negative'], ['entrees', 'small', '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 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": ["All conveniently delivered right to the door ."], "output": "[['delivered', 'conveniently', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ordered the Change Mojito , which was out of this world ."], "output": "[['Change Mojito', '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": ["Okay service ."], "output": "[['service', '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": ["The only thing more wonderful than the food ( which is exceptional ) is the service ."], "output": "[['food', 'exceptional', 'positive'], ['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": ["The anti-pasta was excellent , especially the calamari , as were the filling pasta mains ."], "output": "[['anti-pasta', 'excellent', 'positive'], ['calamari', 'excellent', 'positive'], ['filling pasta mains', '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 waitress suggested glasses of wine that went very well with the food ."], "output": "[['glasses of wine', 'went very well with the food', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 might be all business at the counter when you give your order , but their food says I love you ."], "output": "[['food', 'love', 'positive'], ['counter', 'love', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very particular about sushi and were both please with every choice which included : ceviche mix ( special ) , crab dumplings , assorted sashimi , sushi and rolls , two types of sake , and the banana tempura ."], "output": "[['ceviche mix ( special )', 'please', 'positive'], ['crab dumplings', 'please', 'positive'], ['assorted sashimi', 'please', 'positive'], ['sushi', 'particular', 'positive'], ['rolls', 'please', 'positive'], ['sake', 'please', 'positive'], ['banana tempura', '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": ["Good luck getting a table ."], "output": "[['getting a table', 'Good luck', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The takeout menu says to keep an eye out for an expanded menu offering more italian dishes , I ca n't wait !"], "output": "[['menu', 'expanded', 'positive'], ['italian dishes', '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": ["The pizza is good though ."], "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": ["bottles of wine are cheap and good ."], "output": "[['bottles of wine', 'cheap', 'positive'], ['bottles of 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 have over 100 different beers to offer thier guest so that made my husband very happy and the food was delicious , if I must recommend a dish it must be the pumkin tortelini ."], "output": "[['beers', 'happy', 'positive'], ['food', 'delicious', 'positive'], ['pumkin tortelini', '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": ["You must have the crabmeat lasagna which is out of this world and the chocolate bread pudding for dessert ."], "output": "[['crabmeat lasagna', '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": ["Very good service and very good prices ."], "output": "[['service', 'good', '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": ["The service was impeccable and unobtrusive -- the staff knows what they are there to do -- to know their menu , present your meal , and attend to your needs ."], "output": "[['service', 'impeccable', 'positive'], ['service', 'unobtrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 food was great too !"], "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 most annoying thing , though , is the fact that the servers seem to be trained to drive revenue ."], "output": "[['servers', '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": ["Please try the Filet Mignon , its just the most tender piece ever ."], "output": "[['Filet Mignon', '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": ["the drinks are amazing and half off till 8pm ."], "output": "[['drinks', '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 've been back to nha trang literally a hundred times for the beef cubes - they 're that good ."], "output": "[['beef cubes', '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 were seated promptly as we had reservations , however after that the service was slow ."], "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 food was pretty good , but a little flavorless and the portions very small , including dessert ."], "output": "[['dessert', 'small', '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": ["Lived in Shanghai most of my life and thought the food was comparable to the flagship Green Bo restaurant there ."], "output": "[['food', 'comparable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Cafe St. Bart 's for their food , the ambience and wonderful service ."], "output": "[['food', 'recommend', 'positive'], ['ambience', 'recommend', 'positive'], ['service', 'recommend', 'positive'], ['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": ["All the NYU students love this place so it makes for a fun young atmosphere ."], "output": "[['atmosphere', 'fun young', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 does a great service to the name ( Cantonese that is ... ) ."], "output": "[['food', 'great', 'positive'], ['Cantonese', '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": ["But , nothing stands out about the cooking ."], "output": "[['cooking', 'nothing stands out', '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": ["Joya used to be a cool spot with decent food and a colorful - if not relaxed - atmosphere ."], "output": "[['food', 'decent', 'positive'], ['atmosphere', '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": ["The Prix Fixe menu is worth every penny and you get more than enough ( both in quantity AND quality ) ."], "output": "[['Prix Fixe menu', 'worth', 'positive'], ['quantity', 'more than enough', 'positive'], ['quality', 'more than 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": ["I work near-by , and they have the BEST oatmeal in the neighborhood- not a packaged or quick-cooked item ."], "output": "[['oatmeal', '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": ["Too bad the food was n't of the same heritage ."], "output": "[['food', '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 menu looked good , except for offering the Chilean Sea Bass , but the server does not offer up the specials that were written on the board outside ."], "output": "[['menu', 'good', 'positive'], ['Chilean Sea Bass', 'except', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it literally is a complete hole in the wall , it 's a bit intimidating at first , but you get over that very quickly as soon as the friendly staff welcomes you - do n't hesitate to ask for help with what to get ."], "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": ["When he finally did , he was unable to make a gin and tonic -- could n't find tonic ."], "output": "[['gin and tonic', 'unable', '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 dim sum is ok but does n't taste that fresh , and the little dishes do n't look steamy hot as they should ( also note lack of Chinese here ) ."], "output": "[['dim sum', 'ok', 'negative'], ['little dishes', \"do n't look steamy hot\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 ok , some of the people did n't get what they asked for ."], "output": "[['service', '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": ["If you want good authentic Thai this place is not the place to go ."], "output": "[['Thai', 'good authentic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 getting a reservation even though we saw people seated without one ."], "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": ["Staff is very accomodating ."], "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": ["Very popular style Izakaya ( Sake and small portion of sake-friendly dishes ) ."], "output": "[['dishes', 'sake-friendly', 'positive'], ['portion', 'small', '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 terrific and the service classy , attentive , without being overbearing ."], "output": "[['food', 'terrific', 'positive'], ['service', 'classy', 'positive'], ['service', 'attentive', 'positive'], ['service', 'without being overbearing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 an amazing place to try some roti rolls ."], "output": "[['roti rolls', '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": ["Fresh ingredients and everything is made to order ."], "output": "[['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": ["We have never had any problems with charging the meal or the tip , and the food was delivered quickly , but we live only a few minutes walk from them ."], "output": "[['meal', 'never had any problems', 'positive'], ['food', 'delivered quickly', 'positive'], ['tip', '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": ["Quick and friendly service ."], "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": ["Try the hot dogs too , they 're snappy and delicious ."], "output": "[['hot dogs', 'Try', 'positive'], ['hot dogs', 'snappy', 'positive'], ['hot dogs', '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 noise level was unbearable , conversation impossible ."], "output": "[['noise level', 'unbearable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Personal pans are the perfect size for those hungry nights ."], "output": "[['Personal pans', '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": ["Highly recommended is the Spicy Fried Clam Rolls and Spider Rolls ."], "output": "[['Spicy Fried Clam Rolls', 'recommended', 'positive'], ['Spider Rolls', '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": ["One of the earlier people commenting on the restaurant did not get the that some experimenting is going on with the menu in a positive way ."], "output": "[['menu', '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": ["Odd for Ave B , not just odd , The place attracts an eclectic crowd to say the least ."], "output": "[['place', 'odd', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got back from lunch at Tamarind and it was excellent ."], "output": "[['lunch', '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": ["head and shoulders above its neighboors on east 6 st , taj mahal is also very comparable , in food quality , to the much overpraised ( and underdeserving ) baluchi 's ."], "output": "[['food quality', 'comparable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 we were sitting eating the subpar food the manager proceeded to berate a couple of his employees for putting out the wrong containers for condiments and explained to them how expensive these containers were ."], "output": "[['food', 'subpar', 'negative'], ['containers', 'expensive', '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": ["Great Indian food and the service is incredible ."], "output": "[['Indian food', 'Great', 'positive'], ['service', '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": ["Decor is nice and minimalist , food simple yet very well presented and cooked , and the wine list matches the food very well ."], "output": "[['Decor', 'nice', 'positive'], ['Decor', 'minimalist', 'positive'], ['food', 'simple', 'neutral'], ['food', 'well presented and cooked', 'neutral'], ['wine list', '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": ["We ordered a tuna melt - it came with out cheese which just made it a tuna sandwich ."], "output": "[['tuna melt', 'with out', 'negative'], ['cheese', 'with out', 'neutral'], ['tuna sandwich', 'with out', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 not attentive except that the bill turned up on the table before we were finished ."], "output": "[['waiters', '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 sangria was pretty tasty and good on a hot muggy day ."], "output": "[['sangria', 'tasty', '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": ["For the people who want great food plus great service , Roxy is a place to AVOID !"], "output": "[['food', 'great', 'negative'], ['service', 'great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 best ravioli ever ."], "output": "[['ravioli', '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": ["Ive been here a bunch of times now and the service is always 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": ["Quite frankly , this is some of the worst sushi I have ever tried ."], "output": "[['sushi', '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 food is great , service is ok ."], "output": "[['food', 'great', 'positive'], ['service', '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": ["Spice is great Thai food , love the inexpensive appetizers ."], "output": "[['Thai food', 'great', 'positive'], ['appetizers', 'love', 'positive'], ['appetizers', '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 service was attentive ."], "output": "[['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": ["He not only makes his own homemade mozzarella , but every pie is ultra fresh ."], "output": "[['mozzarella', 'homemade', 'positive'], ['pie', 'ultra 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": ["Fish was overdone ."], "output": "[['Fish', 'overdone', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 you 're sitting in their main dining room ( which has a spectacular , hand-painted high ceiling ) you 'd never know there was a world outside ."], "output": "[['main dining room', 'spectacular', 'positive'], ['ceiling', 'spectacular', 'positive'], ['ceiling', 'hand-painted 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": ["We visited Bread Bar during January restaurant week and were so pleased with the menu selections and service ."], "output": "[['menu selections', 'pleased', 'positive'], ['service', '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": ["also make sure you pay attention to the music being piped in - quite a weird selection ."], "output": "[['music', 'weird', '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 establishment scores big points in presentation and style ."], "output": "[['establishment', 'scores big points', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 not overly efficient ."], "output": "[['wait staff', 'friendly', 'positive'], ['wait staff', 'not overly 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 dim sum however was very good ."], "output": "[['dim sum', '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": ["Service has always been friendly and efficient ."], "output": "[['Service', 'friendly', 'positive'], ['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": ["All we received was an apology as we left to see our show without dinner ."], "output": "[['dinner', 'without', '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 table next to us asked if he crushed the grapes himself when their long overdue bottle of wine finally arrived ."], "output": "[['bottle of wine', 'long overdue', '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": ["Prices are very good ."], "output": "[['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": ["The Dim Sum was so-so , but not spectacular ."], "output": "[['Dim Sum', 'so-so', 'neutral'], ['Dim Sum', 'not 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": ["The food was so-so ."], "output": "[['food', 'so-so', '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 place is larger than most and features adequate seating unlike most joints , and has a bar which deserves a mention ."], "output": "[['seating', 'adequate', 'positive'], ['bar', 'deserves', 'positive'], ['place', 'larger', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Threw my fiance 's surprise 30th birthday dinner here could n't be happier ."], "output": "[['dinner', \"could n't be happier\", '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 - awesome ."], "output": "[['Food', '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": ["May , the owner always has a smile on her and will warmly greet you ."], "output": "[['owner', 'warmly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 some reason , all the seafood on the menu was unavailable except for the Salmon ."], "output": "[['seafood', 'unavailable', 'negative'], ['menu', 'unavailable', 'negative'], ['Salmon', 'except', '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 beverages were excellent , and the dessert was good ."], "output": "[['beverages', 'excellent', 'positive'], ['dessert', '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": ["Next time , we would n't dare ordering anything else other than some simple Asian appetizers and drinks ."], "output": "[['Asian appetizers', 'simple', 'positive'], ['drinks', '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": ["Please if your thinking about it go , and stay the wait you wo n't be disappointed ."], "output": "[['wait', \"wo n't be 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": ["If you 'd like to have a nice light meal with an asian accent , Long Tan is a good place on the slope ."], "output": "[['meal', '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": ["When going out for a nice dinner , I like a nice ambiance as well as very good food ."], "output": "[['dinner', 'nice', 'positive'], ['ambiance', 'nice', '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": ["Highly recommend this as great value for excellent sushi and service ."], "output": "[['sushi', 'excellent', 'positive'], ['service', 'excellent', '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": ["This place would be so much better served by being run by a group that actually understands customer service ."], "output": "[['service', 'would be so much 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": ["A++ The service was good to excellent along with the attitude ."], "output": "[['service', 'good', 'positive'], ['attitude', '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 food is awesome - definitely try the striped bass ."], "output": "[['food', 'awesome', 'positive'], ['striped bass', '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": ["black white shakes came out good also ."], "output": "[['black white shakes', '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 simply the best meal in NYC ."], "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": ["We go on Mondays for the prix fixe and our experience with the food has been comparable to Blue Ribbon ."], "output": "[['food', 'comparable', '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 , they 've got the most amazing pastrami and the soups hit the spot ."], "output": "[['pastrami', 'amazing', 'positive'], ['soups', 'hit the 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": ["Great bagels made the old-fashioned way ."], "output": "[['bagels', '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 some really good , inexpensive sushi ."], "output": "[['sushi', 'good', 'positive'], ['sushi', '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": ["my personal favorite is an everything bagel with lox spread , but all the bagles are unbeliavably good ."], "output": "[['bagel with lox spread', 'favorite', 'positive'], ['bagles', 'unbeliavably 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 would n't even have complained at all if the food at least tasted good but the quality of food was crappy , too ."], "output": "[['quality of food', '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": ["For the next hour and a half we stood in the crowded lobby area of this touristy restaurant listening to all types of explanations of why we were not being seated ."], "output": "[['lobby area', '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": ["The pizza is delicious and the proprietor is one of the nicest in NYC ."], "output": "[['pizza', 'delicious', 'positive'], ['proprietor', '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": ["Also good for client lunch meetings , esp ."], "output": "[['lunch meetings', '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": ["The decor is dark , cool and soothing , while the food 's presentation is spectacular , considering the low prices ."], "output": "[['decor', 'dark', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'soothing', 'positive'], ['prices', 'low', 'positive'], [\"food 's presentation\", '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 Waitstaff were very nice and suggested swordfish for my husband he enjoyed his meal ."], "output": "[['Waitstaff', 'nice', 'positive'], ['swordfish', 'suggested', 'positive'], ['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": ["The setting is casual and romantic ."], "output": "[['setting', 'casual', 'positive'], ['setting', '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": ["Terrible , terrible management - deserves to be shut-down ."], "output": "[['management', 'Terrible', 'negative'], ['management', '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": ["Great friendly service , Fast seating , Fast Delivery , Excellent sushi ."], "output": "[['service', 'Great friendly', 'positive'], ['seating', 'Fast', 'positive'], ['Delivery', 'Fast', 'positive'], ['sushi', '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 Italian food has flavor ( that can be sort of surprising on the UES ) , and the service turns from a nightmare to attentive , they sort of remind me of the NY Yankees of the late 90 's , no matter how bad it look , you knew that there was a rally just around the corner ..."], "output": "[['Italian food', 'surprising', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mizu is home to creative and unique rolls not to found anywhere else ."], "output": "[['rolls', '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": ["Baluchi 's has solid food and a nice decor at reasonable prices ."], "output": "[['food', 'solid', 'positive'], ['decor', 'nice', '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": ["Moules were excellent , lobster ravioli was VERY salty !"], "output": "[['Moules', 'excellent', 'positive'], ['lobster ravioli', 'salty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 cheap eat for NYC , but not for dosa ."], "output": "[['dosa', 'but', 'negative'], ['eat', '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": ["The seafood is amazing , there 's a good wine list , and the ever-changing menu always offers some great surprises ."], "output": "[['seafood', 'amazing', 'positive'], ['wine list', 'good', 'positive'], ['menu', 'ever-changing', 'positive'], ['menu', 'great 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": ["The food was just OK , at least for what food was available ."], "output": "[['food', '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 waitress was very patient with us and the food is phenomenal !"], "output": "[['waitress', 'patient', 'positive'], ['food', '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": ["The ambience was nice , but service was n't so great ."], "output": "[['ambience', 'nice', 'positive'], ['service', \"was n't so great\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Solid wine list , knowledgeable staff , friendly owners and an adventurous , ever-changing menu keep us coming back ."], "output": "[['wine list', 'Solid', 'positive'], ['staff', 'knowledgeable', 'positive'], ['owners', 'friendly', 'positive'], ['menu', 'adventurous', 'positive'], ['menu', 'ever-changing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The people that work there are always so friendly you forget you are in New York sometimes ."], "output": "[['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": ["The location and ambience is Ok but the food is what makes up for it ."], "output": "[['location', 'Ok', 'neutral'], ['ambience', 'Ok', 'neutral'], ['food', 'makes 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 love and I know gourmet food by excellence !"], "output": "[['gourmet food', 'love', 'positive'], ['gourmet food', 'excellence', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 plan to come here again and look forward to trying their assortment of bruschetta , panini 's ... .."], "output": "[['bruschetta', 'look forward', 'positive'], ['panini', 'look forward', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 people in our party felt like something else , and Volare immediately obliged with two great dishes that were not in their regular menu ."], "output": "[['dishes', 'great', 'positive'], ['menu', 'regular', '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": ["He offers subpar service and has no personality ."], "output": "[['service', 'subpar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 remembers me and is very friendly , she knows what my regular is and that 's the fried mini buns with the condensed milk and the assorted fruits on beancurd ."], "output": "[['waitress', 'friendly', 'positive'], ['fried mini buns with the condensed milk and the assorted fruits on beancurd', 'regular', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Diner food at bistro prices is a bummer ... ."], "output": "[['food', 'bummer', 'negative'], ['prices', 'bummer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 we thoroughly enjoyed the food , it was annoying to scream across the table for conversation ."], "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": ["The portions are large and the servers always surprise us with a different starter ."], "output": "[['portions', 'large', 'positive'], ['servers', 'surprise', 'positive'], ['starter', '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": ["delicious bagels , especially when right out of the oven ."], "output": "[['bagels', '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": ["This is one great place to eat pizza more out but not a good place for take-out pizza ."], "output": "[['pizza', 'great', 'positive'], ['take-out pizza', '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": ["Try green curry with vegetables ."], "output": "[['green curry with vegetables', '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": ["First of all , this place is *not* romantic , as claimed by Citysearch 's editorial review ."], "output": "[['place', '*not* romantic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The second you walk through the heavy vault like door , with people anticipating your arrival you get the sense that you are going to have the dining ride of a lifetime ."], "output": "[['door', 'heavy', '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": ["Much more reasonably priced too !"], "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 food was not very tasty , the portioins were tiny even for such a high quality restaurant ."], "output": "[['food', 'not very tasty', 'negative'], ['portioins', '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": ["The Pad Thai is excellent here , as well ."], "output": "[['Pad Thai', '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 do not recommend lunch specials just because it tasts the same with other regular chinese restaurant ."], "output": "[['lunch specials', 'not 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": ["We parked on the block of Nina 's the place looked nice , with people obviously enjoying their pizzas ."], "output": "[['place', 'nice', 'positive'], ['pizzas', 'enjoying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 o.k. , but not any better than what you get at a good neighborhood restaurant ."], "output": "[['food', 'o.k. ,', 'neutral'], ['food', 'not any 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": ["We had the pot-stickers which were great and a tempura dish that was great ."], "output": "[['pot-stickers', 'great', 'positive'], ['tempura dish', '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 think the stuff was better than Disney ."], "output": "[['stuff', '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": ["While the $ 20 entree range is not overly expensive , in New York City , there is definitely better food in that range , and so Sapphire , despite it 's lovely atmosphere , will most likely not be a restaurant to which I will return ."], "output": "[['food', 'better', 'negative'], ['atmosphere', 'lovely', 'positive'], ['entree range', 'not overly 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": ["Orsay , is without a doubt one of the best values for authentic French food in NYC ."], "output": "[['French 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": ["Well , their deliveries take for ever and the food is usually cold ."], "output": "[['deliveries', 'for ever', 'negative'], ['food', '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": ["And really large portions ."], "output": "[['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Thai restaurant with a very friendly staff ."], "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": ["I ordered the smoked salmon and roe appetizer and it was off flavor ."], "output": "[['smoked salmon and roe appetizer', 'off flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 went here for lunch a couple of weeks ago on a Saturday , and I was thoroughly impressed with the food ."], "output": "[['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": ["I recommend the garlic shrimp , okra ( bindi ) , and anything with lamb ."], "output": "[['garlic shrimp', 'recommend', 'positive'], ['lamb', 'recommend', 'positive'], ['okra ( bindi )', '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 great and authentic ."], "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": ["Good for casual dinner with jeans and sneakers ."], "output": "[['casual 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": ["Anyway , the food is good , the price is right and they have a decent wine list ."], "output": "[['food', 'good', 'positive'], ['price', 'right', 'positive'], ['wine list', '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": ["This place has many different styles of pizza and they are all amazing ."], "output": "[['styles of pizza', 'different', 'positive'], ['styles of pizza', '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 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": ["Pair you food with the excellent beers on tap or their well priced wine list ."], "output": "[['beers on tap', 'excellent', 'positive'], ['wine list', 'well', '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": ["If you like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you 'll love it here ."], "output": "[['music', 'like', 'negative'], ['bottle minimun', 'love', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Metrazur has a beautiful spot overlooking the main terminal ."], "output": "[['spot', '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 restaurant is rather small but we were lucky to get a table quickly ."], "output": "[['table', '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": ["Quality of food is excellent and price is cheap , stick to pork , fish , chicken , lamb and vegetables ."], "output": "[['Quality of food', 'excellent', 'positive'], ['price', 'cheap', 'positive'], ['pork', 'cheap', 'positive'], ['fish', 'cheap', 'positive'], ['chicken', 'cheap', 'positive'], ['lamb', 'cheap', 'positive'], ['vegetables', '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": ["The place is a little tight and on a cold day , the seating by the entranceway can be pretty drafty ."], "output": "[['seating', 'drafty', 'negative'], ['place', 'tight', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , they were too big for the bun ."], "output": "[['bun', 'too 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": ["The food is fresh , delicious , and reasonably priced ."], "output": "[['food', 'fresh', 'positive'], ['food', 'delicious', '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": ["Raga stands out with an interesting fusion of French and Indian cooking ."], "output": "[['fusion of French and Indian cooking', 'interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bagels are fabulous ."], "output": "[['bagels', '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": ["Oh yes , and they lie on the phone , claiming they have seating in the garden , then of course the seats are not available ."], "output": "[['seating in the garden', 'lie', 'neutral'], ['seats', 'not 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": ["Although they do the typical what kind of water would you like questions the service was good and overall very relaxing to place to eat ."], "output": "[['service', 'good', 'positive'], ['place', 'relaxing', 'positive'], ['water', 'typical', '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 very good , a great deal , and the place its self was great ."], "output": "[['food', 'good', '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": ["Probably much busier for lunch , it 's seldom crowded for dinner ( too close to downtown ) ."], "output": "[['lunch', 'busier', 'neutral'], ['dinner', 'seldom crowded', '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": ["Their calzones are horrific , bad , vomit-inducing , YUCK ."], "output": "[['calzones', 'horrific', 'negative'], ['calzones', 'bad', 'negative'], ['calzones', 'vomit-inducing', 'negative'], ['calzones', 'YUCK', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 takes forever to get a drink and they almost always forget to bring something ( although they dont forget to charge you for it ."], "output": "[['drink', 'forever', '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 place itself is beautiful the bar scene seems to be happening ."], "output": "[['place', 'beautiful', 'positive'], ['bar scene', 'happening', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Saturday , Nov. 6th I had a group from work come in with about 35 people and the staff was amazing to accomodate us ."], "output": "[['staff', '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 spreads , great beverage selections and bagels really tasty ."], "output": "[['spreads', 'Good', 'positive'], ['beverage selections', 'great', 'positive'], ['bagels', '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": ["Also , top the meal with a delicious and perfect slice of tiramisu ."], "output": "[['tiramisu', 'delicious', 'positive'], ['tiramisu', '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": ["Check out the secret back room ."], "output": "[['secret back room', 'Check 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 's also attached to Angel 's Share , which is a cool , more romantic bar ..."], "output": "[['bar', 'cool', 'positive'], ['bar', '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": ["I am amazed by the poor reviews- I find this place to be standout Italian in an area flooded with Italian- great prices , great atmosphere , good service and a wonderful wine list ."], "output": "[['prices', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['service', 'good', 'positive'], ['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": ["With the theater 2 blocks away we had a delicious meal in a beautiful room ."], "output": "[['meal', 'delicious', 'positive'], ['room', '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 food is great and reasonably priced ."], "output": "[['food', 'great', 'positive'], ['food', '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": ["Over the years the host , Vittorio , and his crew , have always treated me as family -- although with all the business this not-so-little gem does , it amazing he 's even able to remember a consistent but not-so-frequent visitor ."], "output": "[['crew', 'amazing', 'positive'], ['host', '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 restuarant itself is not large , but seems to have several round tables to accomodate large groups hoping to save a buck to eat authentic Taiwanese ."], "output": "[['round tables', 'several', 'positive'], ['Taiwanese', '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 husband said he could 've eaten several more , the portion was fine for me he even exclaimed that the french fries were the best he has had ."], "output": "[['french fries', '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 the type of place to run into old friends and have a late , raucous dinner ."], "output": "[['dinner', 'raucous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 - from the specials to the regular menu-fare , the dishes are never a disappointment ."], "output": "[['food', 'delicious', 'positive'], ['dishes', 'never a disappointment', 'positive'], ['specials', 'delicious', 'positive'], ['specials', 'never a disappointment', 'positive'], ['regular menu-fare', 'delicious', 'positive'], ['regular menu-fare', 'never a disappointment', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The combination of fresh tomato sauce , fresh mozz cheese , basil and the dough they make with imported flour , makes this is one of the better pizza 's in NY ."], "output": "[['fresh tomato sauce', 'fresh', 'positive'], ['fresh mozz cheese', 'fresh', 'positive'], ['pizza', 'better', 'positive'], ['flour', 'imported', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 all of you new to Indian food , try the Paneer Roll , it is a piece of heaven ."], "output": "[['Paneer Roll', 'heaven', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 looked very appetizing and delicious since it came on a variety of fancy plates ."], "output": "[['food', 'appetizing', 'positive'], ['food', 'delicious', 'positive'], ['plates', 'fancy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the fresh mozzerella slices and the Plain Cheese slice are phenomenal ."], "output": "[['fresh mozzerella slices', 'fresh', 'positive'], ['fresh mozzerella slices', 'phenomenal', 'positive'], ['Plain Cheese slice', '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": ["The food is terrible and overall , I would have to say avoid at all costs ."], "output": "[['food', '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": ["It 's constantly open , catering to the Pakistani cabbies lined up on Crosby St. , so there 's more turnover with the food than you 'd expect ( i.e. , surprisingly fresh ) ."], "output": "[['food', 'surprisingly 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": ["I went at 6:00 PM specifically for the pre-theater menu ( $ 19.95 for roasted tomato soup with chevre , steak frites , creme brulee ) and it was marvelous ."], "output": "[['pre-theater menu', 'marvelous', 'positive'], ['roasted tomato soup with chevre', 'marvelous', 'positive'], ['steak frites', 'marvelous', 'positive'], ['creme brulee', 'marvelous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 were attentive , polite and helpful - an impressive feat in such close quarters ."], "output": "[['waitstaff', 'attentive', 'positive'], ['waitstaff', 'polite', 'positive'], ['waitstaff', 'helpful', 'positive'], ['waitstaff', '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": ["- the bread at the beginning is super tasty and makes you want more - the pizza is delicious and comes in personal sizes , however be warned that the Peter 's Favourite pizza with prosciutto and baby arugula is actually a margarite pizza with cold prosciutto and baby arugula on top , like a salad ."], "output": "[['bread', 'super tasty', 'positive'], ['pizza', '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 always found that the waiters will go out of their way to be helpful , despite the fact they are often busy with lots of diners ."], "output": "[['waiters', 'helpful', 'positive'], ['waiters', '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 owner truly caters to all your needs ."], "output": "[['owner', 'caters', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["He takes real pride in his food and his business ."], "output": "[['food', 'pride', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 if you want a nice , enjoyable meal at Montparnasse , go early for the pre-theater prix-fixe ."], "output": "[['meal', 'nice', 'positive'], ['meal', 'enjoyable', 'positive'], ['pre-theater prix-fixe', 'nice', 'positive'], ['pre-theater prix-fixe', '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": ["Over the years , it has always provided a pleasurable dining experience with quality food and wine ."], "output": "[['food', 'quality', 'positive'], ['wine', 'quality', 'positive'], ['dining', '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": ["The photobook menu was a cute touch , certainly helped my group and I pick the fried chicken , pork chop , and noodle dishes that we all ordered ."], "output": "[['menu', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not imagine better Indian food in all of the city ."], "output": "[['Indian food', '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": ["very good breads as well ."], "output": "[['breads', '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": ["Pizza is terrific , as is homemade pasta ."], "output": "[['Pizza', 'terrific', 'positive'], ['homemade pasta', '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": ["This is a wonderful place on all stand points especially value ofr money ."], "output": "[['value ofr money', '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": ["From beginning appetizers , the scallops were incredible , to the delicious chocolate souffle with rasberry mint sorbet , we were delighted by the taste sensations ."], "output": "[['beginning appetizers', 'incredible', 'positive'], ['scallops', 'incredible', 'positive'], ['chocolate souffle with rasberry mint sorbet', 'delicious', 'positive'], ['taste', 'delighted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 goodness , everything from the fish to the rice to the seaweed was absolutely amazing ."], "output": "[['fish', 'amazing', 'positive'], ['rice', 'amazing', 'positive'], ['seaweed', '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 is reliable and the price is moderate ."], "output": "[['food', 'reliable', 'positive'], ['price', 'moderate', '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 ambiance and atmosphere were great , the food and service could have been a lot better ."], "output": "[['ambiance', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['food', 'could have been a lot better', 'negative'], ['service', 'could have been a lot 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 server was really cool and served us our food and drinks with a smile ."], "output": "[['server', '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": ["Planet Thailand has always been a hit with me , I go there usually for the sushi , which is great , the thai food is excellent too ."], "output": "[['sushi', 'great', 'positive'], ['thai 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 sauce on the pizza is sooo good with garlic and fresh tomatoes and they do n't skimp ."], "output": "[['fresh tomatoes', 'fresh', 'positive'], ['sauce on the 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": ["We recently decided to try this location , and to our delight , they have outdoor seating , perfect since I had my yorkie with me ."], "output": "[['outdoor seating', '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 husband had the mesclun , salmon , and ice cream and he enjoyed all 3 courses ."], "output": "[['mesclun', 'enjoyed', 'positive'], ['salmon', 'enjoyed', 'positive'], ['ice cream', 'enjoyed', 'positive'], ['courses', '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 food is usually good but it certainly is n't a relaxing place to go ."], "output": "[['food', 'good', 'positive'], ['place', \"is n't a relaxing\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 friendly and knowledgable staff , fabulous bistro fare and a wonderful jazz brunch with great live jazz ( the chilaquiles were awesome !"], "output": "[['staff', 'friendly', 'positive'], ['staff', 'fabulous', 'positive'], ['bistro fare', 'fabulous', 'positive'], ['chilaquiles', 'awesome', 'positive'], ['jazz brunch', 'wonderful', 'positive'], ['live jazz', '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 prices were fantastic ."], "output": "[['prices', '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 table service could have been a little more attentive but as someone who also works in the service industry , I understood they were busy ."], "output": "[['service', 'busy', '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 not mind-blowing , but to me , thai food never is and never will be ."], "output": "[['thai food', 'mind-blowing', '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 very good as well , considering that we tried the budget selection ( though I wish the pork belly that I ordered was roasted a bit longer , so that fat was more of a melt-in-your-mouth experience ) ."], "output": "[['Food', 'good', 'positive'], ['pork belly', 'melt-in-your-mouth', 'negative'], ['fat', 'longer', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 fact that the pizza tastes so good and is so cheap ."], "output": "[['pizza', 'love', 'positive'], ['pizza', 'good', 'positive'], ['pizza', '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": ["Service was prompt , friendly and great ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'friendly', '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 have n't eat a lamb chop as delicious as that , the salads are really nice dressed with lemon and extra virgnin olive oil ."], "output": "[['lamb chop', 'delicious', 'positive'], ['salads', '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 sushi was awful !"], "output": "[['sushi', '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": ["You can get an excellent meal at most of the many Indian restaurants on nearby Lexington Avenue for the cost of one the dainty dishes here ."], "output": "[['meal', 'excellent', 'positive'], ['dishes', 'dainty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The plain pizza was soggy and the creative wild mushroom ( third generation-Fornini ) pizza we had was drenched with truffle oil in the middle ( again making it soggy ) and nothingon the rest ."], "output": "[['plain pizza', 'soggy', 'negative'], ['truffle oil', 'drenched', '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": ["Late nite omelletes are not good here , there is no variety !"], "output": "[['omelletes', '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": ["After all that , they complained to me about the small tip ."], "output": "[['tip', '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": ["It 's a great place to pick up a cheap lunch or dinner ."], "output": "[['lunch', '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": ["Whenever you need a Sushi fix , Mizu will be there with quality fish and great service ."], "output": "[['fish', 'quality', '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": ["Our waitress was sweet and accomodating , not overbearing ."], "output": "[['waitress', 'sweet', 'positive'], ['waitress', '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": ["I was really disappointed ant wanted to tell everyone not to go eat or even take out food from there ."], "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": ["Despite a slightly limited menu , everything prepared is done to perfection , ultra fresh and a work of food art ."], "output": "[['menu', 'limited', 'negative'], ['food art', 'ultra 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 outdoor atmosphere of sitting on the sidewalk watching the world go by 50 feet away on 6th avenue on a cool evening was wonderful ."], "output": "[['outdoor atmosphere', '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": ["brick oven gallery is My pick for best pizza restaurant anywhere ."], "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": ["Add to that great service and great food at a reasonable price and you have yourself the beginning of a great evening ."], "output": "[['service', 'great', 'positive'], ['food', '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": ["For many people , this may not seem like Aunthentic Thai food because most places in NYC arent quite authentic ."], "output": "[['Thai food', 'authentic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , do n't even let me start with how expensive the bills were !"], "output": "[['bills', '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 the appetizers and salads were fabulous , the steak was mouth watering and the pasta was delicious ! ! !"], "output": "[['appetizers', 'fabulous', 'positive'], ['salads', 'fabulous', 'positive'], ['steak', 'watering', 'positive'], ['pasta', '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": ["Besides having the table we had been promised given to other restaurant patrons twice before we were actually seated , we were served dishes we had n't ordered three times , received one of our orders 20 minutes after the rest of the table had been served ( and that order was undercooked ) , and charged $ 45 more than we should have been on our bill ."], "output": "[['dishes', '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": ["Service is top notch ."], "output": "[['Service', '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": ["The food now is inconsistent ."], "output": "[['food', 'inconsistent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 CAREFUL before you request extra spice ."], "output": "[['spice', 'CAREFUL', '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 octopus eaters were floored by the Octopus salad ."], "output": "[['Octopus salad', 'floored', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 thought that this place is using too much of MSG cooking in the foods ."], "output": "[['MSG cooking', 'too 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": ["And the Tom Kha soup was pathetic ."], "output": "[['Tom Kha soup', 'pathetic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 started out with a Bombay beer which was big enough for two ."], "output": "[['Bombay beer', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 vibrant and eye-pleasing with several semi-private boths on the right side of the dining hall , which are great for a date ."], "output": "[['decor', 'vibrant', 'positive'], ['decor', 'eye-pleasing', 'positive'], ['dining hall', '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 sweet lassi was excellent as was the lamb chettinad and the garlic naan but the rasamalai was forgettable ."], "output": "[['sweet lassi', 'excellent', 'positive'], ['rasamalai', 'forgettable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 been following chef Lyle 's food around New York for 15 years and while remaining classic , his innovations with bistro fare have made us return and return ."], "output": "[['bistro fare', 'innovations', 'positive'], ['food', '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 best thing I tasted were the lambchops ."], "output": "[['lambchops', '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 addition , the food is very good and the prices are reasonable ."], "output": "[['food', 'good', '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": ["Upon entering , we were greeted by the owners , Steven and Frederick , who went out of their way to be more than gracious hosts ."], "output": "[['hosts', '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": ["Been going here since it opened have seen the quality value decrease considerably ."], "output": "[['quality value', 'decrease', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bring service up a notch by offerng complementary amuse bouche to all tables and gave us a small dessert for our celebration ."], "output": "[['amuse bouche', 'complementary', 'positive'], ['dessert', '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": ["Try the crunchy tuna , it is to die for ."], "output": "[['crunchy tuna', 'Try', 'positive'], ['crunchy tuna', '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": ["All in all , this midtown gem instantly became one of my favorite sushi restaurants in the city ."], "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": ["It is a lot of fun with live entertainment and all kinds of Disney type special effects ."], "output": "[['live entertainment', 'fun', 'positive'], ['special effects', '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": ["if you 're looking for perfect traditional sushi , go here - if you 're looking for interesting combinations , try Sushi of gari 's ( east side ) ."], "output": "[['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": ["Be careful of portions - they 're HUGE ."], "output": "[['portions', '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": ["The Steak Tartare is a great bet , they fix it for you at the table ."], "output": "[['Steak Tartare', '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 for large groups and celebrations - our SUPER HAPPY waiter was the entertainment of the evening ."], "output": "[['waiter', 'SUPER 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": ["Plus , on Wednesday nights the house wine is unlimited !"], "output": "[['house wine', 'unlimited', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , in the summer of 2003 , it seems the management has changed and the great big door has been replaced for a glass front ridding itself of the dark romantic getup ."], "output": "[['management', 'changed', 'neutral'], ['door', 'great big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 wo n't go to this place again for a good meal ."], "output": "[['meal', '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": ["Barbecued codfish was gorgeously moist - as if poached - yet the fabulous texture was let down by curiously bland seasoning - a spice rub might have overwhelmed , however herb mix or other sauce would have done much to enhance ."], "output": "[['Barbecued codfish', 'moist', 'positive'], ['seasoning', 'bland', 'negative'], ['spice rub', 'overwhelmed', 'negative'], ['herb mix', 'to enhance', 'negative'], ['sauce', 'to enhance', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dinner , take your date to the HUGE dance floor , probably one of the biggest you 'll see in NY ."], "output": "[['dance floor', 'HUGE', 'positive'], ['dance floor', 'biggest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Taj Mahal offeres gret value and great food ."], "output": "[['value', '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": ["My boyfriend and I recently had an early dinner at Artisanal and was satisfied with our experience ."], "output": "[['dinner', '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": ["Outstanding Bagels , but you get what you pay for ."], "output": "[['Bagels', '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": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best , freshly baked bread !"], "output": "[['crust', 'best', 'positive'], ['bread', 'freshly baked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it on a cold night , the perfect spot to warm up ."], "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": ["Service was warm and attentive , beef carpaachio was exellent ( huge portion ) and pasta was fresh and well-prepared ."], "output": "[['Service', 'warm', 'positive'], ['Service', 'attentive', 'positive'], ['beef carpaachio', 'exellent', 'positive'], ['pasta', 'fresh', 'positive'], ['pasta', 'well-prepared', 'positive'], ['portion', '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": ["Best Italian food I ever had ( and being Italian , that means alot ) ."], "output": "[['Italian 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 will recommend Scopa to all of my friends for a place to go for wonderful Italian food ."], "output": "[['Italian 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": ["Great bar , most gorgeous bartenders you 've ever seen ( specifically the blond lady ) ."], "output": "[['bar', 'Great', 'positive'], ['bartenders', '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": ["I really loved the different and inovated touch that 's the cheff gives to the food ."], "output": "[['food', 'different', 'positive'], ['food', 'inovated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 came out over cooked and the cheese was almost non existant ."], "output": "[['cheese', 'non existant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 terrific meal , and our server guided us toward a very nice wine in our price range , instead of allowing us to purchase a similarly priced wine that was n't as good ."], "output": "[['meal', 'terrific', 'positive'], ['wine', '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": ["The svc can be a bit rude at times , esp if you have big group , but overall the restaurant is a must !"], "output": "[['svc', '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 food is good , especially their more basic dishes , and the drinks are delicious ."], "output": "[['food', 'good', 'positive'], ['dishes', 'good', 'positive'], ['drinks', '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": ["But the main hit was the whole grilled fish ."], "output": "[['whole grilled fish', '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": ["On a hot day it was fabulous to stop in and enjoy lunch ."], "output": "[['lunch', 'fabulous', 'positive'], ['lunch', '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 food is delicious and beautifully prepared along with the friendly and personable service ."], "output": "[['food', 'delicious', 'positive'], ['food', 'beautifully prepared', 'positive'], ['service', '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": ["Pizza here is consistently good ."], "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": ["Would n't recomend it for dinner !"], "output": "[['dinner', 'recomend', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Sauce was watery and the food did n't have much flavor ."], "output": "[['Sauce', 'watery', 'negative'], ['food', \"did n't have much flavor\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 enjoy Sangria ."], "output": "[['Sangria', '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": ["We both opted for a pasta dish and they were served timely and fresh ."], "output": "[['pasta dish', 'served timely', 'positive'], ['pasta dish', 'fresh', 'positive'], ['served', 'timely', 'positive'], ['served', '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": ["First the wrong bread came out with the appetizer , then when i tried to order a second glass of wine for my main course ..."], "output": "[['bread', 'wrong', 'negative'], ['glass of wine', 'second', '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": ["In an area sadly lacking in decent Thai food , this is one of the best spots ."], "output": "[['Thai 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": ["Make reservations but expect to be delayed 15-20 minutes as the hosting staff was having difficulty seating guests who arrived with a reservation because they probably had a lot of walk ins being so close to Time Square ."], "output": "[['reservations', 'delayed', 'negative'], ['seating', 'difficulty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 average or above including some surprising tasty dishes ."], "output": "[['food', 'average or above', 'positive'], ['dishes', '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": ["They do n't seem to place an emphasis on specials or fresh ingredients which to me is necessary for good thai ."], "output": "[['ingredients', 'good', 'negative'], ['thai', '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": ["The crust is thin , the ingredients are fresh and the staff is friendly ."], "output": "[['crust', 'thin', 'positive'], ['staff', 'friendly', '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": ["Also a little more expensive than your average bagel place ."], "output": "[['bagel', 'expensive', '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 undercooked -the sauce watery , and the vegetables raw ."], "output": "[['food', 'undercooked', 'negative'], ['vegetables', 'raw', 'negative'], ['sauce', 'watery', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 fried clams had just enough kick to them to make 'em worth eating ."], "output": "[['fried clams', '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 sauces used are also not that exciting ."], "output": "[['sauces', 'not that exciting', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The secret is the lunch menu which offers a complimentary appetizer with every entree ordered ."], "output": "[['lunch menu', 'secret', 'positive'], ['appetizer', 'complimentary', 'positive'], ['entree', 'complimentary', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The shrimp scampi was excellent and the antipasti were plentiful ."], "output": "[['shrimp scampi', 'excellent', 'positive'], ['antipasti', 'plentiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 $ 10 10-piece dim sum combo , every bite of which was great ."], "output": "[['dim sum combo', '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": ["There is also very limited seating and there can be a substantial wait in getting food at peak times ."], "output": "[['seating', 'limited', 'negative'], ['wait', 'substantial', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 's just a quick martini at the bar ( which I recommend Jeffery 's ) or a mind blowing Roast Chicken , go to Village !"], "output": "[['martini', 'quick', 'neutral'], ['bar', 'recommend', 'neutral'], ['Roast Chicken', 'mind blowing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 long wait for a table outside , but it was a little too hot in the sun anyway so our insde table was very nice ."], "output": "[['table', 'long wait', 'neutral'], ['insde table', 'nice', 'positive'], ['wait', '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": ["The prices are wonderfully low ."], "output": "[['prices', 'wonderfully low', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 disappointed but their true strength lays in their amazingly delicious and cheap lunch specials ."], "output": "[['lunch specials', 'delicious', 'positive'], ['lunch specials', '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": ["So much more than the usual bar food , go there to enjoy the menu while sampling one of their hand-crafted beers ."], "output": "[['menu', 'enjoy', 'positive'], ['hand-crafted beers', 'hand-crafted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 free drink ."], "output": "[['drink', 'No free', '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 is my first time writing a review for a restaurant because the food and service was excellent ."], "output": "[['food', 'excellent', '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": ["Do n't waste money on decor ."], "output": "[['decor', 'waste', '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 back garden open in the summer - cute and French with outdoor seating - what more could you ask for ?"], "output": "[['back garden', 'cute', 'positive'], ['back garden', 'French', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 before eaten 40 pieces of relatively good nigiri ."], "output": "[['nigiri', '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": ["Given the incredible architecture surrounding it , this place has no character ."], "output": "[['architecture', 'incredible', 'positive'], ['place', 'no character', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 place is not a hotspot hangout , the drinks are unique and pack a lot of bang for the buck ."], "output": "[['drinks', '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": ["Their eggplant is so delicate , sweet tender !"], "output": "[['eggplant', 'delicate', 'positive'], ['eggplant', 'sweet 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": ["Each bite of food at Kai was indeed delicious , fresh , and elegant ."], "output": "[['food', 'delicious', 'positive'], ['food', 'fresh', 'positive'], ['food', '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": ["all the food was excellent - considering the quality of food in most moderately priced restaurants is mediocre this was slightly more pricey and well worth it ."], "output": "[['food', 'excellent', 'positive'], ['quality of food', 'mediocre', 'positive'], ['priced', 'moderately', '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 the cod with paella ( spicy and very filling , I 'm a big eater and could only eat half ) while my boyfriend had the classic fish and chips ( again , a big serving - at least 5 pieces of fish and a basketful of fries ) ."], "output": "[['cod with paella', 'spicy', 'negative'], ['cod with paella', 'filling', 'negative'], ['fish and chips', 'classic', 'negative'], ['fish and chips', 'big', 'negative'], ['serving', '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": ["It 's a shame that a nice , convenient place like the Pink Pony can be so ruined by lousy service ."], "output": "[['place', 'convenient', 'positive'], ['service', '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": ["Try the spicy wontons and the salt pepper shrimps ."], "output": "[['spicy wontons', 'Try', 'positive'], ['salt pepper shrimps', '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 fries are yummy ."], "output": "[['fries', '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": ["Friendly and informative staff , very attentive and prompt raw bar service ."], "output": "[['staff', 'Friendly', 'positive'], ['staff', 'informative', 'positive'], ['staff', 'attentive', 'positive'], ['bar service', 'raw', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Taiwanese food in NY !"], "output": "[['Taiwanese 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 is a great stop for 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": ["All the pastas are fantastic and the homemade lasagna is some of the best that I have had in the City ."], "output": "[['pastas', 'fantastic', 'positive'], ['homemade 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": ["And the prices were way to high for what you get ."], "output": "[['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 staff ignored my friends and I the entire time we were there ."], "output": "[['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": ["Yet paired with such rude service , would never recommend for anyone interested in carrying any kind of conversation while there ."], "output": "[['service', '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 in-house lady DJ on Saturday nights has outrageously good taste in music , and moreover , takes requests ."], "output": "[['in-house lady DJ', 'good taste', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , reasonably priced . -- Sara"], "output": "[['wine list', 'Great', '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 hot dogs were cold in the middle and the buns were stale ."], "output": "[['hot dogs', 'cold', 'negative'], ['buns', 'stale', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 food was excellent , it was n't cheap ( though not extremely expensive either ) ."], "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": ["Beef noodle soup is good as well ."], "output": "[['Beef noodle soup', '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": ["Delivery service is great too ."], "output": "[['Delivery 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 's dazzling flavors overwhelm the palate , truly embracing the beauty of authentic Thai cuisine ."], "output": "[['food', 'overwhelm', 'positive'], ['Thai cuisine', 'authentic', 'positive'], ['flavors', 'overwhelm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 recieved prompt service with a smile ."], "output": "[['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": ["They pray to their Food Gods to make them into a good pizza like VT 's ."], "output": "[['pizza', '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": ["The place was quiet and delightful ."], "output": "[['place', 'quiet', 'positive'], ['place', '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 a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes ."], "output": "[['food', 'diamond', 'positive'], ['food', 'delicious', 'positive'], ['food', 'homemade', 'positive'], ['herbs', 'perfect', 'positive'], ['tomatoes', '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 much as I like the food there , I ca n't bring myself to go back ."], "output": "[['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": ["The prices and ambience are especially great considering it 's in the West Village ."], "output": "[['prices', 'great', 'positive'], ['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": ["The soup is pretty good too ."], "output": "[['soup', '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 is so easy to get a reservation at a top place in NYC with a week 's notice ."], "output": "[['reservation', '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": ["not the food , not the ambiance , not the service , I agree with the previous reviews you wait and wait , the wait staff are very rude and when you get in they are looking to get you right out ."], "output": "[['wait staff', '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": ["I always get the Shabu-Shabu dinner and the beef is always fresh ."], "output": "[['beef', '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 pizza was delivered cold and the cheese was n't even fully melted !"], "output": "[['pizza', 'cold', 'negative'], ['cheese', \"was n't even fully melted\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 surprised by how good the food was on our first visit here on a Sunday night ."], "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": ["Nha Trang , while being notorious for utter lack of comfort and decor , horribly slow wait staff and horribly quick meals , is one of the best vietnamese restaurants i 've ever been to . the pho is delicious and comes with very fresh vegtables ."], "output": "[['comfort', 'lack', 'negative'], ['decor', 'lack', 'negative'], ['wait staff', 'horribly slow', 'negative'], ['meals', 'horribly quick', 'negative'], ['pho', 'delicious', 'positive'], ['vegtables', '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": ["On the other hand , if you are not fooled easily , you will find hundreds of restaurants that will give you service and ambiance that is on par with Alain Ducasse , and food that will outshine in presentaion , taste , choice , quality and quantity ."], "output": "[['service', 'on par', 'neutral'], ['ambiance', 'on par', 'neutral'], ['food', 'outshine', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 could rate the people this place would be off the charts - unfortunately - the pizza , sorry - not the best in NYC ."], "output": "[['people', 'best', 'positive'], ['pizza', 'best', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not been home in the last 2 years may skew this reviewer a bit , but the food was tasty and spicy sans the oil that comes floating along at similar venues ."], "output": "[['food', 'tasty', 'positive'], ['food', 'spicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 now very small , the sauces are overly ambitious usually inedible while the service is still good , the restaurant , due to its popularity , seems frantic ."], "output": "[['portions', 'small', 'negative'], ['sauces', 'ambitious', 'negative'], ['sauces', 'inedible', 'negative'], ['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 owner is very friendly and a great guy , go try his pizza , you 'll like it !"], "output": "[['owner', 'friendly', 'positive'], ['owner', 'great', 'positive'], ['pizza', 'try', 'positive'], ['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": ["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": ["With so many good restaurants on the UWS , I do n't need overpriced food , absurdly arrogant wait-staff who do n't recognize they work at a glorified diner , clumsy service , and management that does n't care ."], "output": "[['food', 'overpriced', 'negative'], ['wait-staff', 'arrogant', 'negative'], ['service', 'clumsy', 'negative'], ['management', \"does n't care\", 'negative'], ['diner', 'glorified', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tend to judge a sushi restaurant by its sea urchin , which was heavenly at sushi rose ."], "output": "[['sea urchin', 'heavenly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 a little scatty at times but all is forgiven when the food arrives ."], "output": "[['service', 'scatty', 'negative'], ['food', 'forgiven', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bruscetta is a bit soggy , but the salads were fresh , included a nice mix of greens ( not iceberg ) all dishes are served piping hot from the kitchen ."], "output": "[['bruscetta', 'soggy', 'negative'], ['salads', 'fresh', 'positive'], ['dishes', 'hot', 'positive'], ['mix of greens', '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 atmosphere is n't the greatest , but I suppose that 's how they keep the prices down ."], "output": "[['atmosphere', \"is n't the greatest\", 'neutral'], ['prices', 'down', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pickles were great addition ."], "output": "[['pickles', '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": ["If your favorite Chinese food is General Tao chicken , then this is NOT your place ."], "output": "[['General Tao chicken', 'favorite', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 shrimp appetizers ."], "output": "[['shrimp appetizers', '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": ["Not only is the cuisine the best around , the service has always been attentive and charming ."], "output": "[['cuisine', 'best', 'positive'], ['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 production is a symphony , alot of fun to experience.The food sublime for the most part ."], "output": "[['food', '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": ["Waiters tend to forget drinks completely , food portions are so tiny , two people have trouble sharing one entree ."], "output": "[['Waiters', 'forget', 'negative'], ['food portions', 'tiny', 'negative'], ['drinks', 'forget', 'neutral'], ['entree', 'trouble', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 thing that my wife and I hated was it was so loud and it felt like ' bar ' or ' pub ' ."], "output": "[['bar', 'loud', 'negative'], ['pub', 'loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 are plenty of places to go for a good corned beef sandwich , Katz 's has a charm about it ."], "output": "[['corned beef sandwich', '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": ["However , looking at the table next to ours , we both sort of wished we had ordered pizza , which looked perfect"], "output": "[['pizza', '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": ["Priced at upper intermediate range ."], "output": "[['Priced', 'upper intermediate', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 live in new york city , you 'll find better food at small restaurants outside of time square and spend half the amount ."], "output": "[['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": ["they did n't disappoint , service from the second i arrived at the door was extremely pleasant and attentive with almost one server per table ."], "output": "[['service', 'pleasant', '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": ["I do n't know who they think they are but they have no respect for the residents of the neighborhood ever since they opened their cabaret next door and blasts loud music till three in the morning every weekend during the summer ."], "output": "[['music', 'loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 was the wait staff , which was prompt , knowledgable , and likeable ."], "output": "[['wait staff', 'positive', 'positive'], ['wait staff', 'prompt', 'positive'], ['wait staff', 'knowledgable', 'positive'], ['wait staff', 'likeable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not a vegetarian but , almost all the dishes were great ."], "output": "[['dishes', '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 very impressed by this low-key upper eastsider and their authentically thai cuisine ! ! !"], "output": "[['thai cuisine', 'authentically', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 location , the prices are very reasonable ."], "output": "[['prices', 'reasonable', 'positive'], ['location', 'reasonable', '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 okay and the prices here are mediocre ."], "output": "[['food', 'okay', 'neutral'], ['prices', '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": ["My friend 's food was also the complete opposite of what it 's supposed to taste like ( aND look like ) ."], "output": "[['food', 'opposite', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 been to this place many times , and always have great food , wine , and service ."], "output": "[['food', 'great', 'positive'], ['wine', '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": ["Not a typical pizza joint , but good for a low key and fairly cheap nice sit down dinner ."], "output": "[['dinner', 'cheap 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 corned beef was tender and melted in my mouth ."], "output": "[['corned beef', 'tender', 'positive'], ['corned beef', 'melted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 Chicken pad tai , I 've ever had ."], "output": "[['Chicken pad tai', '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": ["$ 20 for all you can eat sushi can not be beaten ."], "output": "[['sushi', 'can not be beaten', '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": ["Haru serves very fresh fish , has a trendy , modern ambiance , prime location on Park Avenue South and friendly service ."], "output": "[['fish', 'fresh', 'positive'], ['service', 'friendly', 'positive'], ['ambiance', 'trendy', 'positive'], ['ambiance', 'modern', 'positive'], ['location', 'prime', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Warm and friendly in the winter and terrific outdoor seating in the warmer months ."], "output": "[['outdoor seating', '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": ["Very romantic fires - I 've literally spent hours at Lanterna , drinking wine from their extensive wine and enjoying the ambience ."], "output": "[['wine', 'extensive', 'positive'], ['ambience', 'enjoying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got a little tipsy from the sake but is n't that what Saturday nights with the girlfriends are all about ?"], "output": "[['sake', 'tipsy', '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 turkey burger was not cooked at all , my friends salmon was completely raw ."], "output": "[['turkey burger', 'not cooked', 'negative'], ['salmon', 'raw', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 drinks are very inventive , delicious and classy ."], "output": "[['drinks', 'inventive', 'positive'], ['drinks', 'delicious', 'positive'], ['drinks', '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 food , great prices , great service ."], "output": "[['food', 'Great', 'positive'], ['prices', '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": ["Awesome Pizza especially the Margheritta slice ."], "output": "[['Pizza', 'Awesome', 'positive'], ['Margheritta', '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": ["This place , however , has a lot less pretension than Joya and the Thai food is still above average ."], "output": "[['Thai food', 'above average', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ordering from the regular menu , then you would not regret !"], "output": "[['menu', 'regret', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 with lox and mussels ( the best ive ever had , ever ) and had the cod and trout for dinner ."], "output": "[['lox', 'best', 'positive'], ['mussels', '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": ["Food is 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": ["I recommend the meatballs and caprese salad and the beans on toast were a wonderful start to the meal !"], "output": "[['meatballs', 'recommend', 'positive'], ['caprese salad', 'recommend', 'positive'], ['beans on toast', 'wonderful', 'positive'], ['meal', '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": ["This place is incredibly 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": ["I did n't complain , I liked the atmosphere so much ."], "output": "[['atmosphere', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is always good , the tapas are always yummy , especially with the warm pita bread ."], "output": "[['wine', 'good', 'positive'], ['tapas', 'yummy', 'positive'], ['pita bread', 'warm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 when you are seated the waitresses are great , they explain everything on the menu , and the price of the food is really cheap for the service you get ."], "output": "[['waitresses', 'great', 'positive'], ['price', 'cheap', 'positive'], ['food', 'cheap', '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 've been to several places for Dim Sum and this has got to be the WORST ."], "output": "[['Dim Sum', '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 freshest , best variety , and the fastest delivery ."], "output": "[['variety', 'best', 'positive'], ['delivery', '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": ["Go to Volare for 1st class service and terrific food ."], "output": "[['service', '1st class', 'positive'], ['food', '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 sandwiches are dry , tasteless and way overpriced ."], "output": "[['sandwiches', 'dry', 'negative'], ['sandwiches', 'tasteless', 'negative'], ['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": ["The fried rice is really good too ."], "output": "[['fried rice', '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 were well attended to by the enthusiastic staff especially the manager Tony Gaskin who made excellent suggestions for our menu selections ."], "output": "[['staff', 'enthusiastic', 'positive'], ['manager', '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": ["Made my dining experience uncomfortable ."], "output": "[['dining experience', '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": ["A very inviting restaurant , with friendly service ."], "output": "[['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": ["We also had shared a house salad that was fresh ."], "output": "[['house salad', '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 ceiling is amazing !"], "output": "[['ceiling', '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": ["Not a small feat for good french food in the area ."], "output": "[['french 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 space is a bit too small for live music , so on jazz nights , it can be loud and cramped ."], "output": "[['space', 'small', 'negative'], ['jazz nights', 'loud', 'neutral'], ['jazz nights', 'cramped', '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": ["Big Wong gets big Ups for a fine establishment ."], "output": "[['establishment', '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 entree was bland and small , dessert was not inspired ."], "output": "[['entree', 'bland', 'negative'], ['entree', 'small', 'negative'], ['dessert', 'not inspired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 the friendliest that have seen in New York ."], "output": "[['staff', 'friendliest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 exception of our lemon salad that had so much pepper on it that our eyes started watering , the food here was decent , not great ."], "output": "[['food', 'decent', 'neutral'], ['food', 'not great', 'neutral'], ['pepper', '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 Pad thai , lad nar and various other dishes all look good on paper but , I 've had better thai food in less asthetically pleasing places ."], "output": "[['thai food', '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": ["Delicious food at a great price but do not go here on a cold day and sit by the front door ."], "output": "[['food', 'Delicious', 'positive'], ['price', 'great', 'positive'], ['front door', 'cold', '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": ["Overall , I 'm still impressed that the place even exists and the prices are quite decent but then again , its Chinatown ."], "output": "[['prices', '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": ["Pizza was a little soggy ."], "output": "[['Pizza', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 inludes famous scrumptious bombay style chaat such as bhelpuri , sevpuri and samosa chaats , as well as other great indian appetizers ."], "output": "[['bhelpuri', 'scrumptious', 'positive'], ['sevpuri', 'scrumptious', 'positive'], ['samosa chaats', 'scrumptious', 'positive'], ['indian appetizers', 'scrumptious', 'positive'], ['indian appetizers', 'great', 'positive'], ['bombay style chaat', 'famous 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 only problem is that the manager is a complete incompetent ."], "output": "[['manager', 'incompetent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 interesting and has many good values ."], "output": "[['wine list', 'interesting', 'positive'], ['wine list', 'good values', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Definite go if you 're used to good Indian restaurant food from abroad ."], "output": "[['Indian restaurant 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": ["By far , the best pizza in Manhattan ."], "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": ["Decent Thai food in cute - though a bit dank - little Nolita hangout , BUT service terrible ."], "output": "[['Thai food', 'Decent', 'positive'], ['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": ["The food is mostly made from scratch , fresh and well prepared ."], "output": "[['food', 'fresh', 'positive'], ['food', 'well 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": ["NO more reservations , expensive tips and annoying stuff ."], "output": "[['reservations', 'NO more', 'positive'], ['tips', 'expensive', 'positive'], ['stuff', 'annoying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["$ 20 gets you unlimited sushi of a very high quality -- I even took a friend here from Japan who said it was one of the best sushi places in the US that he has been to ."], "output": "[['sushi', 'unlimited', 'positive'], ['sushi places', 'best', 'positive'], ['quality', '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": ["Sushi was n't anything spectacular for the price ."], "output": "[['Sushi', '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": ["But they do n't have a toaster , which is strange ."], "output": "[['toaster', 'strange', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 good food i 'd recommend it , but not for a fun night out ."], "output": "[['food', 'good', 'positive'], ['food', '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 menu choices are similar but the taste lacked more flavor than it looked ."], "output": "[['taste', 'lacked', 'negative'], ['menu choices', 'similar', 'neutral'], ['flavor', 'lacked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 must for all the Dosa lovers ."], "output": "[['Dosa', '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": ["The portions are HUGE , so it might be good to order three things to split ( rather than one appetizer and entree per person ) for two people ."], "output": "[['portions', '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": ["The appetizers are just OK and the main courses were decidedly subpar ."], "output": "[['appetizers', 'OK', 'neutral'], ['main courses', 'subpar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The exotic food is beautifully presented and is a delight in delicious combinations ."], "output": "[['exotic food', 'beautifully presented', 'positive'], ['exotic food', '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": ["The staff is very attentive and we can almost always get a table ."], "output": "[['staff', '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": ["Try the mediterranean salad , it is a true experience for your taste buds ! !"], "output": "[['mediterranean salad', '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": ["People are always friendly ."], "output": "[['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": ["The cream cheeses are out of this world and I love that coffee ! !"], "output": "[['cream cheeses', 'out of this world', 'positive'], ['coffee', '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": ["From the entrees to the sides to the drinks , everything was creatively prepared yet still simple ."], "output": "[['entrees', 'creatively prepared', 'positive'], ['entrees', 'simple', 'positive'], ['sides', 'creatively prepared', 'positive'], ['sides', 'simple', 'positive'], ['drinks', 'creatively prepared', 'positive'], ['drinks', '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": ["Service was prompt and courteous ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'courteous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not above ordinary and the beef version had cheap ( undercooked ) beef ."], "output": "[['beef version', 'cheap', 'negative'], ['beef version', 'undercooked', 'negative'], ['beef', 'cheap', 'negative'], ['beef', '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": ["Chance is a small cozy restaurant , with a romantic feel to it , the decor is great ."], "output": "[['decor', '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 wine and beer are served , but the house varities are actually quite good ."], "output": "[['house varities', '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 split a tasty vegetable samosa and the malai tikka wrap ."], "output": "[['vegetable samosa', 'tasty', 'positive'], ['malai tikka wrap', '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": ["Knowledge of the chef and the waitress are below average ."], "output": "[['chef', 'below average', 'negative'], ['waitress', '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": ["Decent wine selection too ."], "output": "[['wine selection', '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": ["I have to say I have never had a disapointing meal here ."], "output": "[['meal', 'never had a disapointing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a casual neighborhood bistro that has great food and excellent service , this is the place ."], "output": "[['food', 'great', '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": ["great place to go for a drink too because they have 100 kinds of beer ."], "output": "[['drink', '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": ["Meanwhile , the bartender continued to pour champagne from his reserve after we had finished our bottle and we enjoyed an amuse of turnip soup with pureed basil , gratis ."], "output": "[['turnip soup with pureed basil', '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 food was well prepared and the service impecable ."], "output": "[['food', 'well prepared', 'positive'], ['service', 'impecable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 best dish is thh Thai spiced curry noodles with shrimp - a dish that would cost $ 23.95 is most places , but it is $ 16 here ."], "output": "[['dish', 'best', 'positive'], ['Thai spiced curry noodles with shrimp', '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": ["Good , dark atmosphere and the music is a nice touch ."], "output": "[['atmosphere', 'Good', 'positive'], ['atmosphere', 'dark', 'positive'], ['music', 'nice touch', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 thai is definitely not great -- bland and undistinguished ."], "output": "[['thai', 'not great', 'negative'], ['thai', 'bland', 'negative'], ['thai', 'undistinguished', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 for groups , great for a date , great for early brunch or a nightcap ."], "output": "[['brunch', 'great', 'positive'], ['nightcap', '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": ["Our friendly server made great food suggestions and also sent both the sommelier and the fromager to the table to help suggest different pairings for wine and cheese ."], "output": "[['food suggestions', 'great', '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": ["While the food was good ( certainly no Il Mulino ) the service was horrendous ."], "output": "[['food', 'good', 'positive'], ['service', 'horrendous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not what one would expect from a joint in this price category ."], "output": "[['Service', 'not what one would expect', 'negative'], ['price category', 'expect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 recommend reservations on weekends though ."], "output": "[['reservations', '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": ["Great pizza for lunch place ."], "output": "[['pizza', '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 a group of 8 and well seved ."], "output": "[['seved', '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 LOVE their spicy scallop roll , and my boyfriend consistently gets the sesame chicken ."], "output": "[['scallop roll', '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": ["Best dish is nori-wrapped tuna ."], "output": "[['nori-wrapped tuna', '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 food was absolutely amazing ! !"], "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": ["An excellent alternative to fast food joints and ordering in but , the food was slightly disappointing ."], "output": "[['food', 'excellent', 'negative'], ['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": ["Mermaid Inn is an overall good restaurant with really good seafood ."], "output": "[['seafood', '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 is also attentive and friendly ."], "output": "[['staff', '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": ["That is a problem since we paid about 20 bucks a dish , and had to order 5 dishes to get a decent taste ."], "output": "[['taste', '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": ["They were such a rip-off ( $ 8.95 for four small meat patties in steamed buns ) and not worth trying ."], "output": "[['meat patties in steamed buns', 'rip-off', 'negative'], ['meat patties in steamed buns', 'not worth trying', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 pizzas are terrific and the price is even better !"], "output": "[['pizzas', 'terrific', 'positive'], ['price', '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": ["It is about FOOD and Ambiance , and imagine how dreadful it will be it we only had to listen to an idle engine ."], "output": "[['FOOD', 'dreadful', 'negative'], ['Ambiance', '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 food was good too ."], "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": ["Admittedly , this is not the place for gigantic pieces of fish overflowing the plate ( and thank goodness , in my opinion ) but for simple , elegant sushi there is no better place in New York or anywhere in the US ."], "output": "[['sushi', 'simple', 'positive'], ['sushi', '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": ["The menu seemed to have a wide variety of dishes for seafood lovers and interesting ways of preparing them ."], "output": "[['menu', 'wide', 'positive'], ['variety of dishes', 'wide', 'positive'], ['seafood', 'interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The white bean brushetta to start was incredible and the pasta was phenomenal ."], "output": "[['white bean brushetta', 'incredible', 'positive'], ['pasta', '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": ["The rest of the menu is limited by everything is 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": ["Great food , great lay out and awesome service ."], "output": "[['food', 'great', 'positive'], ['lay out', 'great', 'positive'], ['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": ["We walked in on a Wednesday night and were seated promptly ."], "output": "[['seated', 'promptly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 freindly , they make it feel like you 're eating in a freindly little european town ."], "output": "[['wait staff', 'freindly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 are all very busy , it 's not outstanding service , but I 've never been dealt with rudely ."], "output": "[['waitstaff', '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": ["The flavors are great , and the menu is extensive ."], "output": "[['flavors', 'great', 'positive'], ['menu', '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": ["The food has been consistant for years and it never lets you down ."], "output": "[['food', 'consistant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 forget what you read under me , the atmosphere is n't that bad either ."], "output": "[['atmosphere', \"is n't that bad\", '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": ["We could n't carry our conversation as we were routinely interrupted by waitress and servants asking us to order and hinting that we 're taking too much time -- amazing , we just sat down ."], "output": "[['waitress', 'interrupted', 'negative'], ['servants', 'interrupted', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["sometimes i get good food and ok service ."], "output": "[['food', 'good', 'positive'], ['service', '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": ["It 's a place for people who pay a lot for mediocre food , noise and a chance to be with their fellow bridge and tunnel folks ."], "output": "[['food', 'mediocre', 'neutral'], ['noise', '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": ["After complaining about the chicken dish , the manager came over to tell us that , no one had ever complained before , and that we just did n't know what the dish was supposed to taste like ."], "output": "[['chicken dish', 'complaining', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 spicy and delicious ."], "output": "[['food', 'spicy', '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": ["Bartender was unable to tear himself away from friends at bar ."], "output": "[['Bartender', 'unable to tear', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Anyways , if you 're in the neighborhood to eat good food , I would n't waste my time trying to find something , rather go across the street to Tamari ."], "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 was my frist time at Cafe St. Bart 's and I must say how delicous the food and the service was ."], "output": "[['food', 'delicous', 'positive'], ['service', 'delicous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 would think we 'd get an apology or complimentary drinks - instead , we got a snobby waiter would n't even take our order for 15 minutes and gave us lip when we asked him to do so ."], "output": "[['waiter', 'snobby', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 actually gave 10 % tip ( which we have never done despite mediocre food and service ) , because we felt totally ripped off ."], "output": "[['food', 'mediocre', 'neutral'], ['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": ["We were looking forward to nice glass of Sangria when we arrived ."], "output": "[['glass of Sangria', '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 would highly recommend requesting a table by the window ."], "output": "[['table by the window', '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": ["While we enjoyed the food , we were highly disappointed by the poor service ( waiter was not quite competent and SLOW service ) and lack of remorse ."], "output": "[['food', 'enjoyed', 'positive'], ['service', 'poor', 'negative'], ['waiter', 'not quite competent', '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": ["We 've been to Grocery three times and not once has an item on the menu disappointed ."], "output": "[['menu', '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": ["A touch more jalapeno heat for contrast and it would have been very good indeed ."], "output": "[['jalapeno', '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 ate out in the back patio , which is worth it as it 's cool and the music is hear well there ."], "output": "[['back patio', 'worth', 'positive'], ['back patio', 'cool', 'positive'], ['music', '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": ["Guacamole+shrimp appetizer was really great , we both had the filet , very good , did n't much like the frites that came with , but the filet was so good , neither of us cared ."], "output": "[['Guacamole+shrimp appetizer', 'great', 'positive'], ['filet', 'good', 'positive'], ['filet', '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": ["Nothing fancy but really good food with pretty reasonable price ."], "output": "[['food', 'good', '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": ["While I quite liked the food and the ambience , I 'm not quite sure if it they really deserve it the Michelin rating they have displayed so prooudly in the window ."], "output": "[['food', 'liked', 'positive'], ['ambience', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 worth the prices ."], "output": "[['prices', '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": ["From the moment you enter till the moment you walk out the friendly and helpful staff was was just Fantastic ."], "output": "[['staff', 'friendly', 'positive'], ['staff', 'helpful', 'positive'], ['staff', '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": ["Service was good and food is wonderful ."], "output": "[['Service', 'good', '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": ["The quality of food at this restaurant accompanied by fantastic live jazz makes this place a perfect 10 !"], "output": "[['quality of food', 'perfect', 'positive'], ['live jazz', '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": ["If your visiting , you 'll enjoy the ambiance and the fact that it 's in Time Sq ..."], "output": "[['ambiance', '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": ["Service and food is what any one would expect when spending that type of money ."], "output": "[['Service', 'expect', 'neutral'], ['food', '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": ["LOVE the atmosphere - felt like I was in Paris ."], "output": "[['atmosphere', '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": ["Every course was better than the next ."], "output": "[['course', '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 staff is incredibly helpful and attentive ."], "output": "[['staff', 'helpful', 'positive'], ['staff', '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 Yellowtail was particularly good as well ."], "output": "[['Yellowtail', '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 ate clams oreganta and spectacular salad with perfectly marinated cucumbers and tomatoes with lots of shrimp and basil ."], "output": "[['salad with perfectly marinated cucumbers and tomatoes with lots of shrimp and basil', '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 menu changed , portions were even smaller than before , a lentil dish was salty beyond edibility , a basmati rice dish lacked flavor ."], "output": "[['menu', 'changed', 'negative'], ['portions', 'smaller', 'negative'], ['lentil dish', 'salty', 'negative'], ['basmati rice dish', 'lacked flavor', 'negative'], ['flavor', 'lacked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Patroon features a nice cigar bar and has great staff ."], "output": "[['cigar bar', 'nice', '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": ["Very affordable and excellent ambient !"], "output": "[['ambient', 'affordable', 'positive'], ['ambient', '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": ["More important , the sushi rivals the best in Tokyo ."], "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": ["Why do people rave about the ambience ."], "output": "[['ambience', 'rave', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fluke sashimi drizzled with jalapeno-lime olive oil , the fruit of the oil nicely highlighting the fish 's sweetness ."], "output": "[['fruit of the oil', 'nicely', 'positive'], ['fish', 'sweetness', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 sushi experience ."], "output": "[['sushi', '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": ["If you 're looking for a great meal at a decent price , go to Del Frisco 's !"], "output": "[['meal', 'great', 'positive'], ['price', '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": ["Try the congee and the donut like deep fried dough they call Ow Ley Soh , a delicious and sweet tasting bread ."], "output": "[['congee', 'Try', 'positive'], ['bread', 'delicious', 'positive'], ['bread', 'sweet tasting', 'positive'], ['donut like deep fried dough they call Ow Ley Soh', 'delicious', 'positive'], ['donut like deep fried dough they call Ow Ley Soh', '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 food was delicious and the waiter was incredibly helpful and attentive ( considering we were the only ones there for the first hour ) ."], "output": "[['food', 'delicious', 'positive'], ['waiter', 'helpful', 'positive'], ['waiter', '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 place was real empty but that was because this was the first Sunday they ever opened ."], "output": "[['place', '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": ["This little place definitely exceeded my expectations and you sure get a lot of food for your money ."], "output": "[['food', 'lot', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ambience is delightful , service impeccable ."], "output": "[['Ambience', 'delightful', 'positive'], ['service', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 get the sense that the people there care about their restaurant and about your experience and that is very nice ."], "output": "[['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": ["Both are delicious , the cooks are friendly and are willing to take a moment and speak to you and shake your hand ."], "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": ["The staff was accomodating , the food was absolutely delicious and the place is lovely ."], "output": "[['staff', 'accomodating', 'positive'], ['food', 'delicious', 'positive'], ['place', '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": ["my picks are : - Scallion Pancake ( fried with vegetable juice , very special and tasty ) - Guizhou Chicken - Shredded Squid Family Style ( one of my personal favorites ) - Sichuan Spicy Soft Shell Crab - Shuizhu Fish ( this one is for hardcore Sichuan food fans , I would n't recommend to my American friends as it 's very spicy ."], "output": "[['Scallion Pancake', 'special', 'positive'], ['Scallion Pancake', 'tasty', 'positive'], ['Shredded Squid Family Style', 'favorites', 'positive'], ['Shuizhu Fish', 'spicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 smell like they stuff them with old canned vegetables like the spinach mushroom calzone ."], "output": "[['spinach mushroom calzone', 'old', 'negative'], ['canned vegetables', 'old', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 great deal for 6 Blue Point oysters and a beer or glass of wine for $ 8 !"], "output": "[['Blue Point oysters', 'great', 'neutral'], ['beer', 'great', 'neutral'], ['glass of wine', '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": ["I really liked the noodle dishes at Rice Avenue compared to their Green Curry dish ."], "output": "[['noodle dishes', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 for whatever reason , prices are about twice as high ."], "output": "[['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": ["I am relatively new to the area and tried Pick a bgel on 2nd and was disappointed with the service and I thought the food was overated and on the pricey side ."], "output": "[['service', 'disappointed', 'negative'], ['food', 'overated', 'negative'], ['food', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 atmoshere and worth every bit ."], "output": "[['atmoshere', '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 was knowledgeable and full of personality ."], "output": "[['staff', 'knowledgeable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 complaint would be that at an average cost of $ 12- $ 15 per meal , I 'd like not to have to worry about finding a seat !"], "output": "[['cost', 'complaint', 'negative'], ['seat', 'not to have to worry', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 tower is an amazing dessert as well ."], "output": "[['banana tower', 'amazing', 'positive'], ['dessert', '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": ["Excellent atmosphere , delicious dishes good and friendly service ."], "output": "[['atmosphere', 'Excellent', 'positive'], ['dishes', 'delicious', 'positive'], ['service', 'good', '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": ["A cool place to hang with your friends for a couple of healthy drinks and desserts ."], "output": "[['place', 'cool', 'positive'], ['drinks', 'healthy', 'positive'], ['desserts', '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": ["I like Mamoun 's food as well , but side by side , Kati Rolls just produce tastier food hands down ."], "output": "[['food', 'like', 'positive'], ['food', 'tastier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 a bit slow , but harkens back to my years growing up in Napoli , Italy where things are not rushed and when you sit down for dinner the table is yours all night ."], "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": ["A cool bar with great food , and tons of excellent beer ."], "output": "[['bar', 'cool', 'positive'], ['food', 'great', 'positive'], ['beer', '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": ["Be sure to try the seasonal , and always delicious , specials ."], "output": "[['specials', 'try', 'positive'], ['specials', 'seasonal', 'positive'], ['specials', '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 ambience is authentic and relaxing and we have always received attentive and prompt service ."], "output": "[['ambience', 'authentic', 'positive'], ['ambience', 'relaxing', 'positive'], ['service', 'attentive', '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": ["Fresh , authentic , french cuisine in substantial portions ."], "output": "[['french cuisine', 'Fresh', 'positive'], ['french cuisine', 'authentic', 'positive'], ['portions', 'substantial', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got screwed up , she acted put upon ."], "output": "[['Drinks', 'screwed up', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 vegetarian entree ( Abby 's treasure ) was actually quite a surprise - it was delicious and had wintermelon covering an assortment of fresh mushrooms and vegetables ."], "output": "[['vegetarian entree', 'surprise', 'positive'], ['vegetarian entree', 'delicious', 'positive'], [\"Abby 's treasure\", 'surprise', 'positive'], [\"Abby 's treasure\", 'delicious', 'positive'], ['assortment of fresh mushrooms and vegetables', '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 the pizza is way to expensive ."], "output": "[['pizza', '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": ["And the staff is also young , energeic and hot ! ! ! !"], "output": "[['staff', 'young', 'positive'], ['staff', 'energeic', 'positive'], ['staff', '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": ["Even better , they know how to cook French classics like Steak au Poivre and Onglet without burning it to death or overcooking it ."], "output": "[['Steak au Poivre', 'better', 'positive'], ['Onglet', '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": ["We had a wonderful meal at Naples 45 a month ago on a visit to NYC ."], "output": "[['meal', '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": ["Good drink ."], "output": "[['drink', '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": ["Even though I made the reservation at 3pm for the same night through Dinnerbroker , we were seated at a table with one of the best view !"], "output": "[['table', '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 did n't take a look at the rest menu , but the oysters were fantastic ."], "output": "[['oysters', '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 grilled cheese at home afterwards was better . ! !"], "output": "[['grilled cheese', '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": ["Great service , great food ."], "output": "[['service', '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": ["sometimes i get bad food and bad service , sometimes i get good good and bad service ."], "output": "[['food', 'bad', 'negative'], ['service', 'bad', 'negative'], ['service', 'bad', 'negative'], ['good', '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": ["In summer-eat outside on a terrace ( another great feature of Suan ) ! ! !"], "output": "[['terrace', '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 the perfect restaurant for NY life style , it got cool design , awesome drinks and food and lot 's of good looking people eating and hanging at the pink bar ..."], "output": "[['design', 'cool', 'positive'], ['drinks', 'awesome', 'positive'], ['food', 'awesome', 'positive'], ['bar', 'pink', '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": ["Good , fast service ."], "output": "[['service', 'Good', 'positive'], ['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": ["I was in love with Pongsri on 48th , but compared to Suan it is slow in service and overpriced ."], "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": ["My friends and I experienced amazing cheese and a delicious , new summer menu at Artisanal last night ."], "output": "[['cheese', 'amazing', 'positive'], ['menu', 'delicious', 'positive'], ['menu', '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 's charmingly small and that leads to an atmoshere that is extremely cozy and romantic , even ."], "output": "[['atmoshere', 'cozy', 'positive'], ['atmoshere', '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": ["Love the Jazz bands on Fri and Sat ."], "output": "[['Jazz bands', '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 ok ."], "output": "[['service', '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": ["Do n't expect to sit down inside though , there are only a few tables and they are always full ."], "output": "[['tables', 'few', 'negative'], ['tables', 'full', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 accomodating , the ambiance is exciting and yet relaxed , and the food is out of this world !"], "output": "[['staff', 'accomodating', 'positive'], ['ambiance', 'exciting', 'positive'], ['ambiance', 'relaxed', 'positive'], ['food', '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 food was delicious ( I had a halibut special , my husband had steak ) , and the service was top-notch ."], "output": "[['food', 'delicious', 'positive'], ['halibut special', 'delicious', 'positive'], ['steak', 'delicious', 'positive'], ['service', '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": ["The manager claimed that he could not compensate us for anything on the bill which just shows the lack of sophistication from the entire group ."], "output": "[['manager', 'lack of sophistication', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 only place you can get yummy authentic japanese comfort food ."], "output": "[['japanese comfort food', 'yummy 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": ["We took advanatage of the half price sushi deal on saturday so it was well worth it ."], "output": "[['half price sushi deal', '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 staff are attentive , and have smiles on their faces ."], "output": "[['staff', '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": ["Largest and freshest pieces of sushi , and delicious !"], "output": "[['pieces of sushi', 'Largest', 'positive'], ['pieces of sushi', 'freshest', 'positive'], ['pieces of 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": ["Even the pasta is delicious here ( a rarity in New York pizza restaurants ) ."], "output": "[['pasta', '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": ["but when we looked at the menu , there were n't a lot of choices , most of them were dumplings in the appetizer section ."], "output": "[['menu', \"were n't a lot of choices\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wait staff is blantently unappreciative of your business but its the best pie on the UWS !"], "output": "[['Wait staff', 'unappreciative', 'negative'], ['pie', '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 ingredients taste fresher , the crust is thinner and crispier , the slice is less oily , and it 's never burnt like it occasionally is at Joe 's ."], "output": "[['ingredients', 'fresher', 'positive'], ['crust', 'thinner', 'positive'], ['crust', 'crispier', 'positive'], ['slice', 'less oily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fish is so very fresh ."], "output": "[['Fish', '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 prices were CHEAP compared to the quality of service and food ."], "output": "[['prices', '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": ["Top spot in town for Vietnamese classics , better than places that cost a lot more ."], "output": "[['Vietnamese classics', '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": ["less wait time for me !"], "output": "[['wait time', 'less', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 really blah , and not at all hip or happening ."], "output": "[['decor', 'blah', 'negative'], ['decor', 'not at all hip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 come from a family of pizzeria owners , and I 'm almost ashamed to say that the pizza in Fornino 's blows my families receipies away ."], "output": "[['pizza', 'ashamed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 sandwich is good and the spaghetti with Scallops and Shrimp is great ."], "output": "[['lobster sandwich', 'good', 'positive'], ['spaghetti with Scallops and Shrimp', '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 authentic ."], "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": ["The dim sum is delectable while the prices are quite easy on the wallet ."], "output": "[['dim sum', 'delectable', 'positive'], ['prices', '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 only tried a simple dish of spinach ravioli in a light oil and garlic sauce , but it actually faired better than most NYC Italian joints I 've tried similar dishes at ."], "output": "[['spinach ravioli in a light oil and garlic sauce', '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 worst excuse for Japanese food I 've ever encountered ."], "output": "[['Japanese food', '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": ["We had Pam 's special fried fish and it was amazing ."], "output": "[[\"Pam 's special fried fish\", '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": ["My boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque ."], "output": "[['New England Chowder', 'good', 'positive'], ['Lobster Bisque', 'award', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 enough wines by the glass either ."], "output": "[['wines by the glass', 'Not enough', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it 's a little pricey for the food because it was not as spectacular as the view ."], "output": "[['food', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 worried we would have trouble getting in , but somehow managed to have a short wait ."], "output": "[['wait', 'short', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the fried shrimp which are huge and loved it ."], "output": "[['fried shrimp', 'huge', 'positive'], ['fried shrimp', '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 service is awful -- the last time I was there ( and I do mean the last time ) we were told that they needed our table so we would have to leave ."], "output": "[['service', '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": ["Try the green curry ! ! !"], "output": "[['green curry', '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": ["We had the scallops as an appetizer and they were delicious and the sauce was wonderful ."], "output": "[['scallops', 'delicious', 'positive'], ['appetizer', 'delicious', 'positive'], ['sauce', '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 also seated promptly at the time of our reservation and the service was very quick and professional ."], "output": "[['service', 'quick', 'positive'], ['service', '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": ["The food there are sastifying ."], "output": "[['food', 'sastifying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 visiting this restaurant and having dinner and drinks !"], "output": "[['dinner', 'recommend', 'positive'], ['drinks', '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 wine selection , Gigondas is worth the price , and the house champagne is a great value ."], "output": "[['wine selection', 'Great', 'positive'], ['Gigondas', 'worth the price', 'positive'], ['house champagne', 'great value', 'positive'], ['price', 'worth', '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": ["at night , but it 's hard to hear your own conversation with everyone else competing for that same luxury - the music playing in the background is also voluminous ."], "output": "[['music', 'voluminous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 particularly love their yellowfun tuna and their mussel selection ."], "output": "[['yellowfun tuna', 'love', 'positive'], ['mussel selection', '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 love to visit Murrays for my bagel fix ."], "output": "[['bagel', '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 made early dinner reservations and were thoroughly impressed , reminds me of my grandfather , its old school Italian scenery with lots of fun stuff to admire ."], "output": "[['scenery', 'fun', 'positive'], ['dinner reservations', 'early', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cheese plate is a varied delight and great bargain at $ 10 ."], "output": "[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 servers are very attentive , friendly and quite attractive ."], "output": "[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive'], ['servers', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 average ."], "output": "[['Service', '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": ["But they 've done a really nice job of offering all the typical pizzeria faves plus some terrific specials like the Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual ) ."], "output": "[['Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual )', 'terrific', 'positive'], ['specials', '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 steak is good , the fish is good and the sushi was surprisingly great ."], "output": "[['steak', 'good', 'positive'], ['fish', 'good', 'positive'], ['sushi', '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 poor , restaurant poorly lit , staff not very attentive and I would have rather eaten at a Mcdonald 's than this joint ."], "output": "[['service', 'poor', 'negative'], ['staff', 'not 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": ["My GF and I still choose to eat there a lot because of diverse cocktails , the chill decor , and the decent sushi ."], "output": "[['cocktails', 'diverse', 'positive'], ['decor', 'chill', 'positive'], ['sushi', '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": ["We ended the dinner with a surprisingly light and flaky apple tarte tatin ."], "output": "[['apple tarte tatin', 'flaky', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The buffet had a nice selection ."], "output": "[['buffet', 'nice', 'positive'], ['selection', '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": ["Waitstaff are very friendly ."], "output": "[['Waitstaff', '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": ["Service was slow had to wait to order and get food although not crowded ."], "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 food was below average , the service was pathetic , there was no ambience at all ."], "output": "[['food', 'below average', 'negative'], ['service', 'pathetic', 'negative'], ['ambience', '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": ["I REALLY ENJOYED THE SHOWS PUT ON BY THE ACTORS ."], "output": "[['SHOWS', 'ENJOYED', 'positive'], ['ACTORS', '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 was efficient courteous ."], "output": "[['service', 'efficient courteous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The miso soup lacked flavor and the fish was unfortunately not as well prepared as in the past ."], "output": "[['miso soup', 'lacked flavor', 'negative'], ['fish', 'unfortunately', 'negative'], ['flavor', 'lacked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the best bagels I 've had ."], "output": "[['bagels', '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": ["Toons has recently been redone , so it 's now a very attractive space ."], "output": "[['space', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 prices are nothing special , the portions are huge ."], "output": "[['prices', 'special', 'neutral'], ['portions', 'special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a nice quiet location to go eat a good meal , relax , be able to talk and have a very good time ."], "output": "[['location', 'nice quiet', 'positive'], ['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": ["However , I think this place is a good hang out spot ."], "output": "[['spot', '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 wine list is extensive and impressive ."], "output": "[['wine list', 'extensive', 'positive'], ['wine list', '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": ["While the staff at this little bistro is very friendly , I have never experienced more incompetency ."], "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 quail was fantastic and unique and the pastas were full of flavor ."], "output": "[['quail', 'fantastic', 'positive'], ['quail', 'unique', 'positive'], ['pastas', 'full', '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": ["The staff is courteous and friendly ."], "output": "[['staff', 'courteous', '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": ["Aside from the rushed service , we were very impressed with the food and the drinks ."], "output": "[['service', 'rushed', 'negative'], ['food', 'impressed', 'positive'], ['drinks', '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": ["I would highly recommend this place to anyone who is looking for a fine Indian dining experience that is definitely a value for your dollar ."], "output": "[['Indian dining experience', '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": ["This big draw is the all you can sushi here for $ 19.95 !"], "output": "[['sushi', '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": ["Some of the workers ignore me and talk to the female customers , other times , they 've skipped my order ."], "output": "[['workers', 'ignore', 'negative'], ['order', 'skipped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The specials are usually quite good too ."], "output": "[['specials', '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 've the best desserts and mixed drinks as well as snack foods ."], "output": "[['desserts', 'best', 'positive'], ['mixed drinks', 'best', 'positive'], ['snack foods', '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": ["Really cool stauff inside ."], "output": "[['stauff', '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": ["While the new restaurant still features much of the same classical furniture that made Tiffin so attractive , the menu has been overhauled ."], "output": "[['classical furniture', 'classical', 'positive'], ['menu', 'overhauled', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 burger I have had in the Village ."], "output": "[['burger', '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": ["Only drawback - they wo n't toast your bagel , and they do n't make eggs for the bagel ."], "output": "[['bagel', 'drawback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always we had a great glass of wine while we waited ."], "output": "[['glass 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 wait staff is pleasant , fun , and for the most part gorgeous ( in the wonderful aesthetic beautification way , not in that she's-way-cuter-than-me-that-b @ # $ * way ) ."], "output": "[['wait staff', 'pleasant', 'positive'], ['wait staff', 'fun', 'positive'], ['wait staff', '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": ["Of course this atmosphere is lacking , but what do you expect from a 24 hour bagel place anyways ?"], "output": "[['atmosphere', '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": ["Service was very good and warm ."], "output": "[['Service', 'good', 'positive'], ['Service', 'warm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really ca n't top the setting for a romantic dinner in NYC ."], "output": "[['dinner', '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": ["Food was good and the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went ."], "output": "[['Food', 'good', 'positive'], ['view', '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 food is decent at best , and the ambience , well , it 's a matter of opinion , some may consider it to be a sweet thing , I thought it was just annoying ."], "output": "[['food', '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 service was a bit slow , but they were very friendly ."], "output": "[['service', 'slow', 'negative'], ['service', '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": ["Leon is an East Village gem : casual but hip , with well prepared basic French bistro fare , good specials , a warm and lively atmosphere ."], "output": "[['specials', 'good', 'positive'], ['atmosphere', 'warm', 'positive'], ['atmosphere', 'lively', 'positive'], ['French bistro fare', 'well 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 food is above average for midtown and sligtly better than some of the other Heartland Breweries in the city ."], "output": "[['food', 'above average', 'positive'], ['food', '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": ["Thius is a must for anyone who loves Shabu-Shabu ."], "output": "[['Shabu-Shabu', 'loves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 absolutely horrible !"], "output": "[['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": ["Similar to other Indian restaurants , they use the dinner special to attract customers at the door ."], "output": "[['dinner special', 'attract', '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 people with carts of food do n't understand you because they do n't speak English , their job is to give you the delicious food you point at ."], "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": ["The crackling calamari salad , which is usually a cheap disaster at many restaurants , is crispy and lightly dressed ."], "output": "[['crackling calamari salad', 'crispy', 'positive'], ['crackling calamari salad', 'lightly dressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 greatest sushi place , but excellent for a $ 19.95 all you can eat ."], "output": "[['sushi place', 'Not the greatest', 'negative'], ['sushi place', 'excellent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Shockingly easy to throw a group dinner here : simple contract , deposit only to hold the date the entire 2nd fl mezz for our grp of 20 ."], "output": "[['group dinner', 'easy', '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 Thai ice tea was amazingly smooth and yummy !"], "output": "[['Thai ice tea', 'smooth', 'positive'], ['Thai ice tea', '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": ["Drinks way over priced ."], "output": "[['Drinks', 'over priced', 'negative'], ['priced', 'over', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 downside to the place is the nazi-like guy running it who constantly complains about the noise level ."], "output": "[['noise level', 'downside', 'negative'], ['guy', 'downside', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Moderate prices ."], "output": "[['prices', 'Moderate', '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 I 've had some the best meals of my life at minnow ."], "output": "[['meals', '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": ["Most importantly , food is 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": ["Great roofdeck , nice group of 30 somethings , but no music , kind of quiet ."], "output": "[['roofdeck', 'Great', 'positive'], ['music', 'no', 'negative'], ['music', 'quiet', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , service was as plain as sesame crusted Salmon I had ."], "output": "[['service', 'plain', 'neutral'], ['sesame crusted Salmon', 'plain', '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 great to go for a quick lunch either alone or with a friend ."], "output": "[['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 food was mediocre at best but it was the horrible service that made me vow never to go back ."], "output": "[['food', 'mediocre', 'neutral'], ['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": ["You get what you pay for and with that logic in mind , Spice is a great place to grab some cheap eats and drinks in a beautiful setting ."], "output": "[['eats', 'cheap', 'positive'], ['drinks', 'cheap', 'positive'], ['setting', '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 service was terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ."], "output": "[['service', '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": ["Other than being a little crowded and a bit overpriced , the atmosphere is filled with energy ( and the beautiful people of course ) and the food was surprising good !"], "output": "[['atmosphere', 'energy', 'positive'], ['people', 'beautiful', 'positive'], ['food', 'surprising 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 music is the best among all the Indian restaurants I have visited ."], "output": "[['music', '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 bread and lamb chops I had before the meal were quite good , however ."], "output": "[['bread', 'good', 'positive'], ['lamb chops', '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": ["Rao 's has the best service and atmosphere in NYC ."], "output": "[['service', 'best', 'positive'], ['atmosphere', '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 never brought us complimentary noodles , ignored repeated requests for sugar , and threw our dishes on the table ."], "output": "[['noodles', 'complimentary', 'negative'], ['sugar', 'ignored', 'negative'], ['dishes', 'threw', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dumplings served amid clean , chic decor ."], "output": "[['dumplings', 'Excellent', 'positive'], ['decor', 'clean', 'positive'], ['decor', 'chic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The kitchen however , is almost always slow ."], "output": "[['kitchen', '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": ["Cute place , nice wait staff but would never go there again ."], "output": "[['wait staff', 'nice', 'positive'], ['place', 'Cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["people are rude bit again it 's new york !"], "output": "[['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": ["The plain slice is great and if you get toppings , the whole slice is topped with them , not sparsely sprinkled on like some places ."], "output": "[['plain slice', '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": ["Service was also horrible and the ambience is not that great ."], "output": "[['Service', 'horrible', 'negative'], ['ambience', 'not that great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 great , takeout is good too ."], "output": "[['Service', 'great', 'positive'], ['takeout', '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": ["Everything is excellent , the menu is quite extensive , and you eat with a view on both sides of the city ."], "output": "[['menu', '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": ["For the quality of food , a little too expensive ."], "output": "[['quality of food', '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": ["Here 's to the fake fish tanks too ..."], "output": "[['fish tanks', '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": ["I 've never had bad service and the fish is fresh and delicious ."], "output": "[['service', 'never had bad', 'positive'], ['fish', 'fresh', 'positive'], ['fish', '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": ["we decided to eat in tea room which was small and cute ."], "output": "[['tea room', 'small', 'positive'], ['tea room', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 an amazing meal and experience !"], "output": "[['meal', '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": ["Unique apppetizers ."], "output": "[['apppetizers', '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 staff has always been attentive and kind , and I 've always been amazed at how they 've handled all the various different group sizes that come in ."], "output": "[['staff', 'attentive', 'positive'], ['staff', 'kind', 'positive'], ['staff', '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": ["IT is the best deal in town for a Monday night dinner at a fine restaurant ."], "output": "[['dinner', '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 wait here is long for dim sum , but if you do n't like sharing tables or if the typical raucous dim sum atmosphere is not your gig , this is a sleek ( for Chinatown ) alternative ."], "output": "[['wait', 'long', 'negative'], ['dim sum', 'long', 'neutral'], ['dim sum atmosphere', 'typical raucous', '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 place has good potential , but needs a significant amount of work before we can justify spending that much money on indian food you can get everywhere else ."], "output": "[['money', '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": ["Everything is always cooked to perfection , the service is excellent , the decor cool and understated ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Thai food is good ."], "output": "[['Thai 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": ["Great selection of wine , and seafood ."], "output": "[['selection of wine', 'Great', 'positive'], ['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": ["Acceptable prices ."], "output": "[['prices', '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": ["As I made the title , it 's an affordable restaurant for great taste ."], "output": "[['taste', '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 not worth the price !"], "output": "[['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": ["Orsay , is a very pleasant throw back to traditional French food , and French service as well ."], "output": "[['French food', 'pleasant', 'positive'], ['French food', 'traditional', 'positive'], ['service', 'pleasant', 'positive'], ['service', '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": ["It 's easy to get a table for a large group and you do n't get hustled out ."], "output": "[['table', '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": ["Great food at reasonable prices ."], "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": ["Salads are a delicious way to begin the meal ."], "output": "[['Salads', '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 ordered tamarind duck and my wife ordered noodles with ground beef , and we were both delighted by the way the dishes evoked Thai flavors in unexpected ways ."], "output": "[['tamarind duck', 'delighted', 'positive'], ['noodles with ground beef', 'delighted', 'positive'], ['dishes', 'delighted', 'positive'], ['Thai flavors', 'delighted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 about $ 9 for an entree for dinner and even less for lunch ."], "output": "[['prices', 'less', 'positive'], ['entree', 'less', 'positive'], ['dinner', 'less', 'neutral'], ['lunch', 'less', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Should you happen to be impressed by the cuisine definitely try it ."], "output": "[['cuisine', 'impressed', 'positive'], ['cuisine', '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 had the black cod with yuzu sauce , which was wonderful ."], "output": "[['black cod with yuzu sauce', '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": ["Prices too high for this cramped and unappealing resturant ."], "output": "[['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": ["Total hipster-wannabe attitude in an otherwise sweet spot ."], "output": "[['spot', '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": ["Everything , from the soft bread , soggy salad , and 50 minute wait time , with an incredibly rude service to deliver below average food ."], "output": "[['service', 'rude', '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": ["The sicilian is my favorite it is moist not dry like most places but all their pizza is great !"], "output": "[['pizza', 'great', 'positive'], ['sicilian', 'favorite', 'positive'], ['sicilian', 'moist not dry', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 prices are a bit expensive for what you get in quality and portion size ."], "output": "[['menu prices', '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 was amazing , and the service was prompt and helpful , but not over-bearing or rushed ."], "output": "[['food', 'amazing', 'positive'], ['service', 'prompt', 'positive'], ['service', 'helpful', 'positive'], ['service', 'not over-bearing or rushed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 delivered by a busboy , not waiter ) We got no cheese offered for the pasta , our water and wine glasses remained EMPTY our entire meal , when we would have easily spent another $ 20 on wine ."], "output": "[['water and wine glasses', '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 takeout is great too since they give high quality tupperware as well ."], "output": "[['takeout', '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 not fresh , the sauces were bland and very oily ."], "output": "[['food', 'not fresh', 'negative'], ['sauces', 'bland', 'negative'], ['sauces', '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": ["This is definitely an excellent date spot because of the ambiance and on the weekends the night scene is more than alive ."], "output": "[['night scene', 'alive', 'positive'], ['spot', '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": ["Again , the waitress was awesome ."], "output": "[['waitress', '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 loved everythig about it-especially the shows and actors ."], "output": "[['shows', 'loved', 'positive'], ['actors', '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 service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals ."], "output": "[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['food', 'tasty', 'positive'], ['hot sauce', '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": ["Scalina Fedeli reminded me why service is so integral to fine dining ."], "output": "[['service', 'integral', 'positive'], ['dining', '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 recommend the thai popcorn : )"], "output": "[['thai popcorn', '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": ["Everything looks great , the drinks , the decor , the food , even the people ."], "output": "[['drinks', 'great', 'positive'], ['decor', '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": ["The parathas and kebabs are made when ordered ensuring a level of freshness that is unsurpassed ."], "output": "[['parathas', 'unsurpassed', 'positive'], ['kebabs', 'unsurpassed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The tuna and wasabe potatoes are excellent ."], "output": "[['tuna', 'excellent', 'positive'], ['wasabe potatoes', '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 only disappointment was the coat check girls who did n't seem to know what a customer is on a realtively non-busy night ( for the coat check girls ) ."], "output": "[['coat check girls', '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": ["We had great desserts ( including the best cannoli I 've ever had ) and then they offered an after dinner drink , on the house ."], "output": "[['desserts', 'great', 'positive'], ['cannoli', '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 crowd , good outdoor seating , with a hip japanese vibe ."], "output": "[['outdoor seating', 'good', 'positive'], ['vibe', '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": ["We asked to be moved ( which took half an hour ) , and then were seated in a high traffic area in the back , even though the rest of the room was practically empty ."], "output": "[['room', 'empty', '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 , their popularity has yet to slow down , and I still find myself drawn to their ambiance and delectable reputation ."], "output": "[['ambiance', 'drawn', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Where tanks in other Chinatown restaurants display a lurking myriad of sad-looking marine life in their murky waters , the tanks at Ping 's are clear as glass with healthy-looking creatures who do not yet know that they will be part of some dim sum lover 's brunch ."], "output": "[['tanks', 'sad-looking', 'positive'], ['tanks', 'clear', 'positive'], ['dim sum', 'healthy-looking', '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 Halibut was too salty , dessert was so so ( do n't waste any of your calories ) and service was poor ."], "output": "[['Halibut', 'salty', 'negative'], ['dessert', 'so so', '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": ["The view is spectacular , and the food is great ."], "output": "[['view', 'spectacular', '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": ["Good bagels and good cream cheese ."], "output": "[['bagels', 'good', 'positive'], ['cream cheese', '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 is wonderful , tasty and filling , and the service is professional and friendly ."], "output": "[['food', 'wonderful', 'positive'], ['food', 'tasty', 'positive'], ['food', 'filling', 'positive'], ['service', 'professional', '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": ["It is also extremely well priced ."], "output": "[['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": ["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 LOVED THE SHOWS ."], "output": "[['SHOWS', '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": ["We could have made a meal of the yummy dumplings from the dumpling menu ."], "output": "[['dumplings', '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": ["Then , get ripped on free box wine ."], "output": "[['box wine', '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": ["My wife and I ate here earlier this week and have not stopped ranting and raving about the food ."], "output": "[['food', 'ranting', 'positive'], ['food', 'raving', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 itself was just ok - nothing spectacular - but the service was awful ."], "output": "[['food', 'ok', 'neutral'], ['service', '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 pizza is yummy and I like the atmoshpere ."], "output": "[['pizza', 'yummy', 'positive'], ['atmoshpere', '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": ["Also , do n't plan on asking for your favorite roll , if it 's not on the menu , you ca n't have it ."], "output": "[['roll', 'favorite', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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": ["those rolls were big , but not good and sashimi was n't fresh ."], "output": "[['sashimi', \"was n't 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": ["try the spicy shrimp appetizer ( again , not the greatest value in the world but worth the price ) and the lamb vindaloo is great ."], "output": "[['shrimp appetizer', 'try', 'positive'], ['shrimp appetizer', 'spicy', 'positive'], ['shrimp appetizer', 'worth the price', 'positive'], ['lamb vindaloo', '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 good not great not worth the wait or another visit"], "output": "[['wait', '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": ["I have had so many dinners here and it 's always been perfect - on a date with my husband , with my mom , with girlfriends and larger groups ."], "output": "[['dinners', '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 menu has lots of options : I hope to go back to try those potato pancakes ."], "output": "[['menu', 'lots', 'positive'], ['potato pancakes', '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 staff is n't the friendliest or most competent , and I am stickler for service , but everything else about this place makes up for it ."], "output": "[['staff', 'friendliest', 'negative'], ['staff', 'competent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 will usually only order one primi and one secondi and split them , as they tend to offer large portions ."], "output": "[['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delicious crab cakes too ."], "output": "[['crab cakes', '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 have been coming here for years and have nothing but good things to say about the service and the great staff at La Lanterna ."], "output": "[['service', 'good', '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": ["The bruschetta and panini 's are so yummy !"], "output": "[['bruschetta', 'yummy', 'positive'], ['panini', '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": ["Always popular , always full , always a wait ."], "output": "[['wait', 'always', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the omakase is to showcase technique and variety , serving almost 40 % of items BBQ-ed and a spicy tuna roll wrapped with not-so-fresh nori seems to be a rather limp performance ."], "output": "[['nori', 'not-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 ca n't wait for summer , when they serve outside on their gigantic patio ."], "output": "[['patio', '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": ["Best Pastrami I ever had and great portion without being ridiculous ."], "output": "[['Pastrami', 'Best', 'positive'], ['portion', '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 first 2 courses were very good , but the chocolate sampler was too rich for me and the dessert wine far too sweet ."], "output": "[['courses', 'good', 'positive'], ['chocolate sampler', 'too rich', 'negative'], ['dessert wine', '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": ["Butter was melted , white wine warm , cheese oozing everywhere ."], "output": "[['Butter', 'melted', 'negative'], ['white wine', 'warm', 'negative'], ['cheese', 'oozing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 party in their private room and they made it truly memorable and were very helpful in the planning ."], "output": "[['private room', 'truly memorable', '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 can not be the ambience , because the place is very cramped and some guests have to sit in an aisle ."], "output": "[['place', 'cramped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 disappointed with the pre-fixe menu of only 2 choices per course ( other restaurants offer 3 choices ) and ended up ordering a la carte ."], "output": "[['pre-fixe menu', 'disappointed', 'negative'], ['choices per course', 'disappointed', '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": ["Authentic Pakistani food ."], "output": "[['Pakistani 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": ["The staff has always been friendly without seeming grating , and the chef has greeted us on a couple of occasions ."], "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 eggplant parmesan is also great , and my friend who grew up in Manhattan claims that no one serves a better baked ziti with meatsauce ."], "output": "[['eggplant parmesan', 'great', 'positive'], ['baked ziti with meatsauce', '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": ["Quality ingredients preparation all around , and a very fair price for NYC ."], "output": "[['ingredients', 'Quality', 'positive'], ['price', 'fair', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good - prompt , attentive and non-intrusive ."], "output": "[['Service', 'good', 'positive'], ['Service', 'prompt', 'positive'], ['Service', 'attentive', 'positive'], ['Service', 'non-intrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 entree of hot pot with seafood was full of imitation crabmeat with a couple pieces of shrimp and squid , and was unnecessarily heated with a burner ."], "output": "[['crabmeat', 'unnecessarily', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 such a crappy part of town to find a good value for lunch , this place is great ."], "output": "[['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": ["In fact , while leaving the place we saw two people looking at the menu , and I could n't help telling them that the food was horrible ."], "output": "[['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": ["Even though the restaurant was packed , we were seated promptly and even asked for a table upstairs with no problems ."], "output": "[['seated', 'promptly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 friendly , prices are good - delivery time was a little slow , but for the way this pizza tastes , I 'm willing to overlook it ."], "output": "[['Service', 'friendly', 'positive'], ['prices', 'good', 'positive'], ['delivery time', '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 can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you do n't like ."], "output": "[['food', 'pricey', 'negative'], ['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": ["The service is excellent , the decor is great , and the food is delicious and comes in large portions ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'great', 'positive'], ['food', 'delicious', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 excellent service"], "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": ["I LOVE their Thai noodles with shrimp and chicken and coconut juice is the MUST !"], "output": "[['Thai noodles with shrimp and chicken and coconut juice', 'LOVE', 'positive'], ['Thai noodles with shrimp and chicken and coconut juice', '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": ["The pizza was really good ."], "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 only possible drawback to this last point is that as of the date of this posting , the additional menu items are only written in Chinese ."], "output": "[['menu items', 'drawback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Kosher dills are the perfect compliment for your unforgetable sandwich and they give you plenty of them ."], "output": "[['Kosher dills', 'perfect', 'positive'], ['sandwich', 'unforgetable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 cheap and the waiters are nice ."], "output": "[['food', 'cheap', '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 food there is so good that even to order out the wait is incredible ."], "output": "[['food', 'good', 'positive'], ['wait', 'incredible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 sushi , Kamikaze and other Rolls are fresh and well presented ."], "output": "[['sushi', 'fresh', 'positive'], ['sushi', 'well presented', 'positive'], ['Kamikaze', 'fresh', 'positive'], ['Kamikaze', 'well presented', 'positive'], ['Rolls', 'fresh', 'positive'], ['Rolls', 'well presented', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 authentic Thai food , look no further than Toons ."], "output": "[['Thai 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": ["The highlight of the night was the mayonaisse for my side of fries I received from one of the food runners , which is not good considering the bill was nearly $ 100 ."], "output": "[['mayonaisse', 'highlight', 'negative'], ['food runners', 'not 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": ["I choose to go with one of the special , the braised lamb shank in red wine , which was excellent ."], "output": "[['braised lamb shank in red wine', 'excellent', 'positive'], ['special', '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": ["Small servings for main entree , i had salmon ( wasnt impressed ) girlfriend had chicken , it was good ."], "output": "[['salmon', 'wasnt impressed', 'negative'], ['chicken', 'good', 'positive'], ['servings', '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 food is very good for it 's price , better than most fried dumplings I 've had ."], "output": "[['food', 'good', 'positive'], ['food', 'better', 'positive'], ['fried dumplings', '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": ["Obv caviar is top of the line but the rest of the menu is so diverse it gives you a chance to taste so manydifferent varietys ."], "output": "[['Obv caviar', 'top of the line', 'positive'], ['menu', 'diverse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ate here a week ago and found most dishes average at best and too expensive ."], "output": "[['dishes', 'average', 'negative'], ['dishes', 'too 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": ["Still , try it once , since if you end up loving the food , it could be one of your best dining experiences ."], "output": "[['food', 'loving', 'neutral'], ['dining experiences', '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": ["Other guests enjoyed pizza , santa fe chopped salad and fish and chips ."], "output": "[['pizza', 'enjoyed', 'positive'], ['santa fe chopped salad', 'enjoyed', 'positive'], ['fish and chips', '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": ["not only does make the best pizza in NY , maybe anywhere ."], "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 spicy Tuna roll is huge and probably the best that I 've had at this price range ."], "output": "[['Tuna roll', 'huge', 'positive'], ['price range', '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": ["Our waiter and all of the people helping him were attentive and genuine ."], "output": "[['waiter', 'attentive', 'positive'], ['waiter', 'genuine', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 BISTRO which means : simple dishes and wine served efficiently in a bustling atmosphere ."], "output": "[['place', 'BISTRO', 'positive'], ['dishes', 'simple', 'positive'], ['wine', 'served efficiently', 'positive'], ['atmosphere', 'bustling', 'positive'], ['served', 'efficiently', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the best comfort food places in the city ."], "output": "[['comfort 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 had a huge pastrami sandwich on a roll ."], "output": "[['pastrami sandwich', '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": ["Though you will undoubtedly be seated at a table with what seems like barely enough room ( no matter what the size of your party ) , the warm atomosphere is worth the cramped quarters- you 'll have fun and forgot about the tight spot you 're in ."], "output": "[['table', 'enough', 'negative'], ['atomosphere', 'warm', 'positive'], ['room', 'enough', 'negative'], ['spot', 'tight', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 not fresh and the rice tasted old and stale ."], "output": "[['fish', 'not fresh', 'negative'], ['rice', 'old', 'negative'], ['rice', 'stale', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Besides , when you have bad service , that 's less money you have to tip ."], "output": "[['service', 'bad', 'negative'], ['money', 'less', 'negative'], ['tip', '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 wine list is also really nice ."], "output": "[['wine list', '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 devine , oysters where a sensual as they come , and the price ca n't be beat ! ! !"], "output": "[['Service', 'devine', 'positive'], ['oysters', 'sensual', 'positive'], ['price', \"ca n't be 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": ["Compared to Ess-a , Tal offers a less doughy bagel !"], "output": "[['bagel', 'less doughy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ballato 's is consistently delicious authentic italian food ."], "output": "[['italian food', 'delicious 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": ["The service was attentive , yet discreet ."], "output": "[['service', 'attentive', 'positive'], ['service', 'discreet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 offer the same menu but have creative drinks that are loaded with alcohol and cheeky names -- but they do cost you ."], "output": "[['menu', 'same', 'neutral'], ['drinks', '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": ["We went to eat at the Jekyll and Hyde restaurant on Friday night and really enjoyed the fun atmosphere and good food ."], "output": "[['atmosphere', 'enjoyed', 'positive'], ['atmosphere', 'fun', 'positive'], ['food', 'enjoyed', '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": ["Unless you are eating in the Pizzeria side of this place , and are not in a rush , this place is a bad idea ."], "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": ["Ambiance is barely romantic but management tries ."], "output": "[['Ambiance', 'barely romantic', 'negative'], ['management', 'tries', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 warn the reader that the portions sizes are very small ( especially the appetizers ) , so if you plan to eat until you are full and do not intend to order the chef 's special tasting menu , prepare to order and pay for an appetizer ( 1 dish for each person because the portions are not for sharing ) , a main entree , and the cold udon at the end of the meal ."], "output": "[['portions', 'small', 'negative'], ['appetizers', '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": ["After we got our sashimi order , I could not believe how small the portions were !"], "output": "[['sashimi', 'small', 'neutral'], ['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": ["Nothing better than buying a snapple for $ 3.25 too ."], "output": "[['snapple', '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 dosas are skimpy , unattractive and drip with grease , and personally I 'd drink popcorn topping before I 'd eat another one of these ."], "output": "[['dosas', 'skimpy', 'negative'], ['dosas', 'unattractive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and the food was delicious ."], "output": "[['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": ["If I wanted to deal with a crappy scene and annoying customers I 'd go out in Manhattan ."], "output": "[['scene', 'crappy', 'negative'], ['customers', '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": ["Until you realize that their five minutes is meaningless and your wait may be anywhere from two to twenty minutes it may be frustrating ."], "output": "[['wait', '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": ["Thalia is a beautiful restaurant with beautiful people serving you , but the food does n't quite match up ."], "output": "[['people serving', 'beautiful', 'positive'], ['food', \"does n't quite match up\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The fillings may be unconventional but the dosa batter is definitely authentic and the combinations very tasty ."], "output": "[['fillings', 'unconventional', 'neutral'], ['dosa batter', '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": ["This is the perfect spot for meeting friends , having lunch , dinner , pre-theatre or after-theatre drinks !"], "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": ["The mussaman curry that I ordered was as thin as water and aside from the poorly fried tofu that I ordered in it , they graciously provided me with ONE piece of poorly cooked potato ."], "output": "[['mussaman curry', 'thin', 'negative'], ['fried tofu', 'poorly', 'negative'], ['potato', 'poorly 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": ["Well , this place is so Ghetto its not even funny ."], "output": "[['place', 'Ghetto', 'negative'], ['place', 'not even funny', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 would like to thank Marcelo and Grace for a wonderful dining experience ! ! !"], "output": "[['dining', '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": ["Found service above average , but that could be because we were 13 of us ."], "output": "[['service', 'above average', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Bagels are ok , but be sure not to make any special requests !"], "output": "[['Bagels', '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": ["fine dining restaurant quality ."], "output": "[['quality', '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": ["Overall a disappointing experience for that price category ."], "output": "[['price', '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": ["The food was exceptional ."], "output": "[['food', '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": ["The portions are small but being that the food was so good makes up for that ."], "output": "[['portions', 'small', 'negative'], ['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": ["( and I have eaten my share ) Which impresses me for having such a large amount of people to serve ."], "output": "[['serve', 'impresses', 'positive'], ['serve', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , the setting is nice ."], "output": "[['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": ["Slightly above average wines start at $ 70+ with only one selection listed at $ 30+ ."], "output": "[['wines', 'above 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": ["Their whitefish salad is excellent -- all whitefish with a little mayo ."], "output": "[['whitefish salad', 'excellent', 'positive'], ['whitefish', 'all', 'positive'], ['mayo', '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": ["The chicken parm was edible but had canned tomato sauce and boxed pasta and the chicken with portobello mushrooms consisted of dry , inedible chicken with terrible sauce ."], "output": "[['chicken', 'edible', 'negative'], ['chicken', 'dry', 'negative'], ['tomato sauce', 'edible', 'negative'], ['pasta', 'edible', 'negative'], ['sauce', '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": ["I recommend this place to everyone who asks me where to go for a good meal ."], "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": ["The waitresses are nice -- also you can just get counter service sit ."], "output": "[['waitresses', '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 only friendly staff member was the guy at the bar ."], "output": "[['staff member', '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": ["You can certainly find restaurants that offer a superior fine dining experience , but for superb food at reasonable prices , La Villa ca n't be beat ."], "output": "[['food', 'superb', '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": ["I can not imagine a friendlier staff working in a restaurant ."], "output": "[['staff', 'friendlier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 suggest to ask to be seated upstairs if you are looking to be a little cozy ."], "output": "[['upstairs', '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 red curry is weak and tasteless , the pad thai is stuck together and lumpy , the rice is often overcooked , and the seafood is pretty sketchy ."], "output": "[['red curry', 'weak', 'negative'], ['red curry', 'tasteless', 'negative'], ['pad thai', 'stuck', 'negative'], ['pad thai', 'lumpy', 'negative'], ['rice', 'overcooked', 'negative'], ['seafood', 'sketchy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and can easily hike up an otherwise reasonably priced meal ."], "output": "[['wine list', 'extensive', 'positive'], ['meal', '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": ["Saul is pretty good , but definitely not great ."], "output": "[['Saul', 'good', 'neutral'], ['Saul', 'not 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": ["I would recommend Roxy 's for that , but not for their food ."], "output": "[['food', '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": ["It is nearly impossible to get a table , so if you ever have the chance to go here for dinner , DO NOT pass it up ."], "output": "[['table', '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": ["Their pad penang is delicious and everything else is fantastic ."], "output": "[['pad penang', '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 puke green walls leave a lot to be desired , but the food is very good ."], "output": "[['food', 'good', 'positive'], ['walls', '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": ["The flavors are very fresh and pretty unobtrusive , nothing flashy ."], "output": "[['flavors', 'fresh', 'positive'], ['flavors', 'unobtrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Cafe Noir dont get me wrong , it is jsut that the people who work there are evil and incompetent ! !"], "output": "[['people', 'evil', 'negative'], ['people', 'incompetent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hanger steak was like rubber and the tuna was flavorless not to mention it tasted like it had just been thawed ."], "output": "[['hanger steak', 'rubber', 'negative'], ['tuna', 'flavorless', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 son loves pizza and we have a certified Neapolitan pizzaria in our home city ( Seattle ) , we liked this nearly as much - and the differences were more about personal preference than any reflection on either restaurant ."], "output": "[['pizza', 'loves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 and soft as well as good lunch food ."], "output": "[['lunch food', 'big', 'positive'], ['lunch food', 'soft', 'positive'], ['lunch 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": ["No food snobs allowed , this place is for people who appreciate 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": ["I liked the food at this quasi-thai restaurant ."], "output": "[['food', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 for the bar , this is another bad idea ."], "output": "[['bar', '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 barebecued salmon is elegantly spiced and not at all dry ."], "output": "[['barebecued salmon', 'elegantly spiced', 'positive'], ['barebecued salmon', 'not at all dry', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The highly spiced chai tea was great too ."], "output": "[['chai tea', 'highly spiced', 'positive'], ['chai tea', '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": ["Seriously , this is the best all you can eat in town- As everyone says , the Spicy Tuna hand rolls are the best- have 4 of these , and you 've broken even ."], "output": "[['Spicy Tuna hand rolls', '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": ["While Sapphire is certainly not lacking in ambiance , and probably has the best decor of any Indian restaurant I have been to in New York City , the food was not what I had hoped for ."], "output": "[['food', 'best', 'negative'], ['ambiance', 'lacking', 'positive'], ['decor', '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 would highly recommend this place to anyone looking for a casual atmosphere that whisks you away to the left bank of the river Seine ."], "output": "[['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": ["His wife Tanya , the hostess , completes the comforting atmosphere by being delightfully warm and gracious ."], "output": "[['hostess', 'delightfully warm', 'positive'], ['hostess', 'gracious', 'positive'], ['atmosphere', 'comforting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a longtime fan of Holy Basil in the East Village , and while I do believe their food has slightly slipped in quality , I have been hesitant to be disloyal ."], "output": "[['quality', 'slipped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 part about LS is the late night atmosphere , delightfully free of the BTs ."], "output": "[['atmosphere', 'delightfully', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 there is very attentive and down to earth ."], "output": "[['staff', 'attentive', 'positive'], ['staff', 'down to earth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 do n't go to Mizu for excellent service , you go for the large amounts of food , the amiable atmosphere , and the hole-in-the-wall feeling of the place ."], "output": "[['service', 'excellent', 'negative'], ['food', 'large', 'positive'], ['atmosphere', 'amiable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 decent even when this small place is packed ."], "output": "[['service', 'decent', 'positive'], ['place', 'small', 'negative'], ['place', 'packed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 best sushi in new york city - hands down ."], "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": ["Great value for the quality ingredients ."], "output": "[['ingredients', '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": ["The Thali was small , thoroughly unremarkable , and $ 14.95 ."], "output": "[['Thali', 'small', 'negative'], ['Thali', 'unremarkable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Truly the mark of an attentive waiter ."], "output": "[['waiter', '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 here is rather good , but only if you like to wait for it ."], "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": ["I got an excellent piece of cheesecake and we had several other nice pastries ."], "output": "[['cheesecake', 'excellent', 'positive'], ['pastries', '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 staff is very kind and well trained , they 're fast , they are always prompt to jump behind the bar and fix drinks , they know details of every item in the menu and make excellent recomendations ."], "output": "[['staff', 'kind', 'positive'], ['staff', 'well trained', 'positive'], ['staff', 'fast', 'positive'], ['staff', '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 food is inventive but still keeps traditional indian flavoring ."], "output": "[['food', 'inventive', 'positive'], ['food', '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 decor in this place is very diner-ish and the kind of place you expect in the East Village - not romantic , just simple , small and sparse ."], "output": "[['decor', 'diner-ish', 'positive'], ['place', 'simple', 'positive'], ['place', 'small', 'positive'], ['place', 'sparse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 cute place and could be good but they need to get their act together ."], "output": "[['place', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lox is always fresh too ."], "output": "[['lox', '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": ["So all I 'm trying to say is this restaurant is by far the best thai food restaurant I 've ever been to ."], "output": "[['thai 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": ["Food was OK - fish was cooked well ."], "output": "[['Food', 'OK', 'neutral'], ['fish', 'cooked 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 duck confit is always amazing and the foie gras terrine with figs was out of this world ."], "output": "[['foie gras terrine with figs', 'out of this world', 'positive'], ['duck confit', '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 whole set up is truly unprofessional and I wish Cafe Noir would get some good staff , because despite the current one this is a great place ."], "output": "[['staff', '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": ["The staff offers impeccable service ."], "output": "[['staff', 'impeccable', 'positive'], ['service', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 our great experience by having Gulab Jamun ( dessert ) recommended by the waiter ."], "output": "[['Gulab Jamun ( dessert )', '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 place is sleek , modern and playful and i will return again frequently ."], "output": "[['place', 'sleek', 'positive'], ['place', 'modern', 'positive'], ['place', 'playful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The brioche and lollies as party favors is a cute and sweet touch to a most memorable meal ."], "output": "[['brioche and lollies', 'cute', 'positive'], ['brioche and lollies', 'sweet', 'positive'], ['meal', 'memorable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 attentive , yet unimposing , the food was far better than many notorious restaurants in Midtown and the wine list is extensive and well priced ."], "output": "[['food', 'better', 'positive'], ['wine list', 'extensive', 'positive'], ['wine list', 'well priced', '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": ["Salads were fantastic ."], "output": "[['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": ["The owners and employees are friendly and their pizza is fantastic ."], "output": "[['owners', 'friendly', 'positive'], ['employees', 'friendly', 'positive'], ['pizza', '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 yummy , especially their cooked-to-perfection mussels in spicy tomato sauce and their shoestring crispy fries ."], "output": "[['food', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'cooked-to-perfection', 'positive'], ['fries', 'yummy', 'positive'], ['fries', '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": ["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": ["The staff is excellent , special : that girl behind the bar , european chic ."], "output": "[['staff', 'excellent', 'positive'], ['bar', 'special', '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 bad , the food took to forever to come , we sat on the upper level ."], "output": "[['service', 'bad', 'negative'], ['food', '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 a menu that rarely changes , e xcept for one or two specials , the quality and care they put in thier food in evident ."], "output": "[['quality', 'evident', 'positive'], ['care', 'evident', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dimsum , not super overpriced noodles ."], "output": "[['noodles', 'not super overpriced', '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 fine and they allow you to enjoy the view ."], "output": "[['service', 'fine', 'positive'], ['view', '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": ["We , there were four of us , arrived at noon - the place was empty - and the staff acted like we were imposing on them and they were very rude ."], "output": "[['staff', '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": ["delicious simple food in nice outdoor atmosphere ."], "output": "[['food', 'delicious simple', 'positive'], ['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": ["The only fallback on this restaurant is the prices ."], "output": "[['prices', 'fallback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and sour soup was unbearably hot and tasted of only pepper and nothing else ."], "output": "[['soup', 'unbearably hot', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 ."], "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": ["Their wines by the glass are a great accompaniment and you can eat like a king with wine for under $ 30 ."], "output": "[['wines by the glass', '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 the the correct ambience and an excellent staff to make you feel like a guest and a friend at the same time ."], "output": "[['ambience', 'correct', 'positive'], ['staff', '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 atmosphere is much better than Sripraphai ( more modern and sleek ) ."], "output": "[['atmosphere', 'better', 'positive'], ['atmosphere', 'modern', 'positive'], ['atmosphere', 'sleek', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 outstanding and the service is quick , friendly and very professional ."], "output": "[['food', 'outstanding', 'positive'], ['service', 'quick', 'positive'], ['service', 'friendly', 'positive'], ['service', '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": ["The bagels always warm , soft on the inside , crispy on the outside and enormous in size ."], "output": "[['bagels', 'warm', 'positive'], ['bagels', 'soft', 'positive'], ['bagels', 'crispy', 'positive'], ['bagels', 'enormous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 late dinner at Lucky Stike , a great name for a joint if ever I saw one ."], "output": "[['dinner', '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": ["Service is fast and friendly ."], "output": "[['Service', 'fast', '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": ["And they have these home made potato chips at the bar that are the most delicious things in the world !"], "output": "[['potato chips', 'delicious', 'positive'], ['bar', 'delicious', '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 husband and I enjoyed each of the 6 taste size portions and left completely full ."], "output": "[['portions', '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": ["We all ate pasta entre'es , which were great ."], "output": "[[\"pasta entre'es\", '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 steak was excellent and one of the best I have had ( I tasted the butter intitally but in no way did it overwhelm the flavor of the meat ) ."], "output": "[['steak', 'excellent', 'positive'], ['steak', '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 was boring and expensive ."], "output": "[['food', 'boring', 'negative'], ['food', '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 ambience is pretty and nice for conversation , so a casual lunch here would probably be best ."], "output": "[['ambience', 'pretty', 'positive'], ['ambience', 'nice', 'positive'], ['lunch', '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": ["Terrific menu full of unique rolls and special dishes ."], "output": "[['menu', 'Terrific', 'positive'], ['rolls', 'unique', 'positive'], ['dishes', 'special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 ok but could be better ."], "output": "[['service', 'ok', 'negative'], ['service', 'could be 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": ["We love the food , drinks , and atmosphere !"], "output": "[['food', 'love', 'positive'], ['drinks', 'love', 'positive'], ['atmosphere', '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 was here a few weeks back and we had the worst customer service experience at a restaurant ever ."], "output": "[['customer 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": ["Took my mom for Mother 's Day , and the maitre d ' was pretty rude ."], "output": "[[\"maitre d '\", '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 vibe is very relaxed and cozy , service was great and the food was excellent !"], "output": "[['vibe', 'relaxed', 'positive'], ['vibe', 'cozy', 'positive'], ['service', 'great', '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": ["The service was friendly and the atmosphere was casual ."], "output": "[['service', 'friendly', '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": ["I recommend their Pad See Ew , Pork Chops or Tofu plates ."], "output": "[['Pad See Ew', 'recommend', 'positive'], ['Pork Chops', 'recommend', 'positive'], ['Tofu plates', '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": ["this is the best secret place in midtown ' , I heard that from the bartender , after having brilliant food ( try steak with portobello mushrooms ) and drinks on the bar last Tuesday ."], "output": "[['food', 'brilliant', 'positive'], ['drinks', 'brilliant', 'positive'], ['steak with portobello mushrooms', 'brilliant', 'positive'], ['steak with portobello mushrooms', '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 service was excellent - friendly and attentive ."], "output": "[['service', 'excellent', '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 dinner menu is diverse and top-notch as well ."], "output": "[['dinner menu', 'diverse', 'positive'], ['dinner menu', '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 do n't like Indian food too much and this was delicious , however you want to factor that into the equation ."], "output": "[['Indian food', \"do n't 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": ["at taj , vegetarians can rejoice-all the dishes are manna from heaven ."], "output": "[['dishes', 'heaven', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Jimmy 's is hands down the hottest night spot in the Bronx ."], "output": "[['spot', 'hottest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The $ 300 bill was a bit steep , but the experience was great ."], "output": "[['bill', 'steep', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ambiance , nice little bar , good bartender , Francois , and good service ."], "output": "[['bar', 'nice', 'positive'], ['bartender', 'good', 'positive'], ['service', 'good', 'positive'], ['ambiance', '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 calamari comes with an incredible sauce , and the duck noodles are yummy as well ."], "output": "[['sauce', 'incredible', 'positive'], ['duck noodles', '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 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": ["Simple comfort food and what hot and large portions ."], "output": "[['comfort food', 'Simple comfort', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bagels are also reasonably priced for NYC ."], "output": "[['bagels', '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": ["Decor leaves something to be desired ."], "output": "[['Decor', '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": ["Also , specify if you like your food spicy- its rather bland if you do n't ."], "output": "[['food', 'bland', '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": ["Our waiter was fine , the place looks nice in that not-trying-too-hard way , but at those prices , a little more should be expected of your food ."], "output": "[['waiter', 'fine', 'positive'], ['place', 'fine', 'positive'], ['food', 'more should be expected', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 been to this restaurant more than a dozen times and when I 'm craving for Pho , Lemon grass chicken or Beef Cube on rice , this is the place to go ."], "output": "[['Pho', 'craving', 'positive'], ['Lemon grass chicken', 'craving', 'positive'], ['Beef Cube on rice', 'craving', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 yes , and if you are a fan of Indian oldies film stars , there are plenty of portraits of Indian actors and actresses in classic black white that adorn the walls , some of which , I would love to know where they obtained ."], "output": "[['portraits', '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": ["The food is spectacular , from the appitizers to the main course , and then of course the desserts , ( WOW ) you 'll need no more ."], "output": "[['food', 'spectacular', 'positive'], ['appitizers', 'spectacular', 'positive'], ['main course', 'spectacular', 'positive'], ['desserts', '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": ["My fish was delicious in an incredible curry sauce ."], "output": "[['fish', 'delicious', 'positive'], ['curry sauce', '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": ["If you are in search of the most authentic NYC deli experience look no further than the famous and historic Katz 's Deli down on the Lower East Side ."], "output": "[['deli', '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": ["Even upon delivery , their juicy pork buns are quite good . ."], "output": "[['pork buns', '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 to good Thai food , but terrible delivery ."], "output": "[['Thai food', 'Average to good', 'positive'], ['delivery', '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": ["Joe 's Pizza used to have the best slice until this pizzeria opened up ."], "output": "[['slice', '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": ["And they provided a delicious dessert on the house !"], "output": "[['dessert', '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 are still living in the dark ages and do not have an answering machine , so if you want to make a reservation you are limited ."], "output": "[['reservation', '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": ["The food is amazing , rich pastas and fresh doughy pizza ."], "output": "[['food', 'amazing', 'positive'], ['pastas', 'rich', 'positive'], ['pizza', 'fresh doughy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good , but not what I would consider out of this world ."], "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": ["Try the Pad Thai , it 's fabulous and their prices are so cheap !"], "output": "[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'fabulous', 'positive'], ['Pad Thai', 'cheap', 'positive'], ['prices', '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": ["Food is great and inexpensive ."], "output": "[['Food', 'great', 'positive'], ['Food', '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": ["Dessert - ca n't be missed , so save room ! ! !"], "output": "[['Dessert', \"ca n't be missed\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ingredients are organic which is a real plus for me ."], "output": "[['Ingredients', 'organic', 'positive'], ['Ingredients', 'plus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 so bad I actually refused to pay for my food ."], "output": "[['food', '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 recommend this spot to anyone who enjoys fine cuisine at reasonable prices ."], "output": "[['cuisine', 'fine', '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 staff was very attentive , the ambience lovely , and the food superb ."], "output": "[['staff', 'attentive', 'positive'], ['ambience', 'lovely', '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": ["I love when restaurants think using fancy expensive ingrediants makes the food fine cuisine , even with no idea how to use them ."], "output": "[['ingrediants', 'expensive', 'positive'], ['cuisine', 'fine', 'positive'], ['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 Pizza and wine were excellent -the service too -- but what really MADE this place was the backyard dining area ."], "output": "[['Pizza', 'excellent', 'positive'], ['wine', 'excellent', '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": ["The service was superb , they treat you like family ."], "output": "[['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": ["We all had the tasting menu and unlike some of the other reviews , I felt there was more than enough food ."], "output": "[['food', 'more than 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 menu may be small , but everything on it is delicious ."], "output": "[['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": ["They had scrapped the bottom of the vessel in which they make the rice -RESULT - WE HAD LARGE CHUNKS OF BURNT RICE IN OUR SERVING BOWL ."], "output": "[['RICE', '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": ["Warm , comfortable surroundings , nice appointments ( witness the etched glass and brickwork separating the dining rooms ) ."], "output": "[['surroundings', 'Warm', 'positive'], ['surroundings', 'comfortable', 'positive'], ['dining rooms', '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": ["The well mannered , pleasant staff that Tony has in his employ ."], "output": "[['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": ["All I can say is $ 2 pints during happy hour and the some of the cheapest oysters you 'll find in the city , though the quality is some of the best ."], "output": "[['oysters', 'cheapest', 'positive'], ['quality', '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 would never wait for a table to eat , it just is not THAT great ."], "output": "[['table', 'never wait', '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": ["We concluded with tiramisu chocolate cake , both were delicious ."], "output": "[['tiramisu chocolate cake', '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 counter service is bad ."], "output": "[['counter 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": ["Service here was great , food was fantastic ."], "output": "[['Service', 'great', 'positive'], ['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": ["The sauce is delicious and the crust is perfect ."], "output": "[['sauce', 'delicious', '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": ["You will pay a lot for the decore , but the food is no better or worse than a lot of other Chinese and Asian fusion places in NY ."], "output": "[['decore', 'pay a lot', 'negative'], ['food', 'no better or worse', '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 have some great entrees here as well ."], "output": "[['entrees', '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 not consistently excellent -- just decent ."], "output": "[['service', 'not consistently excellent', 'neutral'], ['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": ["The food , served in small tasting portions ( as an option ) is very good with each dish being better than the next ."], "output": "[['food', 'good', 'positive'], ['portions', 'small', 'positive'], ['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": ["I had the mango chicken and i ca n't go on to tell you how delicious that was and the presentation was beautiful ."], "output": "[['mango chicken', 'delicious', 'positive'], ['presentation', '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": ["Food and service was okay ."], "output": "[['Food', 'okay', 'neutral'], ['service', '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": ["The best pad thai i 've ever had ."], "output": "[['pad thai', '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 pizza and fantastic service ."], "output": "[['pizza', 'Great', '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": ["While this is a pretty place in that overly cute French way , the food was insultingly horrible ."], "output": "[['place', 'pretty', 'positive'], ['food', 'insultingly 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 went there for lunch and it was not as good as I expected from the reviews I read ."], "output": "[['lunch', 'not as good as I expected', '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 wine list is n't great , and the desserts are shipped in from Bruno 's down the street , which is not as good as it used to be ."], "output": "[['wine list', \"is n't great\", 'negative'], ['desserts', 'not as 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": ["Their coffee is quite good too !"], "output": "[['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": ["great wine list ( italian ) , good food , service was INITIALLY fine ."], "output": "[['wine list', 'great', '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": ["Despite the fact that the space is large , they 've overcrowded the floor with tables ."], "output": "[['space', 'large', 'positive'], ['tables', 'overcrowded', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not helpful in the least and will give you the grand run around so by the time the event date rolls around you will not only regret chosing this place , but also become hostile !"], "output": "[['place', 'hostile', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Normally that would be improper , however they were all delicious and my host did not complain ."], "output": "[['host', 'delicious', '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": ["Taxan delicious !"], "output": "[['Taxan', '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": ["Unlike other places in NYC where the sandwiches you want only come as a triple-decker , here you can get what you want in a reasonably-sized portion ( and price ) ."], "output": "[['portion', 'reasonably-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": ["Restaurant snobs need not bother , this is a small , neighborhood kind of place ."], "output": "[['place', '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": ["They could n't even make a salad that was appealing ."], "output": "[['salad', 'appealing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Of course the reason its so packed is because the food is so 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": ["Staffs are not that friendly , but the taste covers all ."], "output": "[['Staffs', 'not that friendly', 'negative'], ['taste', 'covers all', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 ."], "output": "[['waiter', '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": ["Their Margarita is best I 've had since I 've returned from Naples !"], "output": "[['Margarita', '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": ["Their sake list was extensive , but we were looking for Purple Haze , which was n't listed but made for us upon request !"], "output": "[['sake 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": ["The tables are crammed way too close , the menu is typical of any Italian restaurant , and the wine list is simply overpriced ."], "output": "[['tables', 'crammed', 'negative'], ['tables', 'too close', 'negative'], ['menu', 'typical', 'neutral'], ['wine list', '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": ["The food was actually awful ."], "output": "[['food', '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": ["They are served with a free appetizer and the portions are perfect for lunch ."], "output": "[['appetizer', 'free', 'positive'], ['portions', '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": ["There is actually space to breathe and the decor sets the tone for an intimate dinner ."], "output": "[['dinner', 'intimate', '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": ["We went around 9:30 on a Friday and it had died down a bit by then so 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": ["My husband and I both ordered the Steak , medium ."], "output": "[['Steak', 'medium', '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 place has realy fresh sushi and a nice large menu of Japanese classic cuisine ."], "output": "[['sushi', 'fresh', 'positive'], ['menu', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 average and the prices are anything but ."], "output": "[['sushi', '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": ["My wife and I also enjoyed the spinach , the Shanghai low mein , and other attractions ."], "output": "[['spinach', 'enjoyed', 'positive'], ['Shanghai low mein', '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": ["Turned out there was full service upstairs and sat down ."], "output": "[['service', '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": ["If you have a dumpling fetish i suggest you try some here !"], "output": "[['dumpling', '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 food is consistently wonderful - I 've been coming here for years , and the owner has always been accomodating and friendly ."], "output": "[['food', 'wonderful', 'positive'], ['owner', 'accomodating', '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": ["The waiters and owners were nonchalant about this and promised to call the exterminator but were n't as dismayed or apologetic as I would have expected ."], "output": "[['waiters', 'nonchalant', 'negative'], ['owners', 'nonchalant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was 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": ["Aside from the Sea Urchin , the chef recommended an assortment of fish including Fatty Yellow Tail , Boton Shrimp , Blue Fin Torro ( Fatty Tuna ) , Sea Eel , etc ."], "output": "[['assortment of fish', 'recommended', 'neutral'], ['Fatty Yellow Tail', 'recommended', 'neutral'], ['Boton Shrimp', 'recommended', 'neutral'], ['Sea Eel', 'recommended', 'neutral'], ['Sea Urchin', 'recommended', 'neutral'], ['Blue Fin Torro ( Fatty Tuna )', 'recommended', '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 're also friendlier here , especially the owner , Kenny ."], "output": "[['owner', 'friendlier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 room is not particularly comfortable , once you 're seated you 'll forget about everything except what 's on your plate ."], "output": "[['room', 'not particularly comfortable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is minimal the food is not phenomenal , but some dishes are quite good , such as the eggplant parmesan , veal in carozza chicken saltimbocca ."], "output": "[['ambiance', 'minimal', 'positive'], ['food', 'not phenomenal', 'negative'], ['dishes', 'good', 'positive'], ['eggplant parmesan', 'good', 'positive'], ['veal in carozza chicken saltimbocca', '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 bar has various selections and the mixed drink special is a catcher ! 2 for 1 's ."], "output": "[['bar', 'various', 'positive'], ['mixed drink special', 'catcher', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the course of the past 3 months , the chef and staff changed and it was not for the better ."], "output": "[['chef', 'changed', 'negative'], ['staff', 'changed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ambience , it 's very dark and original ."], "output": "[['ambience', 'like', 'positive'], ['ambience', 'dark', 'positive'], ['ambience', 'original', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , not worth the money ."], "output": "[['money', '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": ["This place is not worth the prices ."], "output": "[['prices', '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": ["Pick a bagel has the best bagels in the city ."], "output": "[['bagels', '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": ["Yes you have to wait to be seated and because its small there is no waiting area and the seat at the bar was all taken ."], "output": "[['waiting area', 'no', 'negative'], ['seat', 'all taken', 'negative'], ['bar', 'small', '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 last two times I ordered from here my food was soo spicy that I could barely eat it , and the spice took away from the flavor of the dish ."], "output": "[['food', 'spicy', 'negative'], ['dish', 'barely', 'negative'], ['spice', 'took 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 fried dumplings are GREAT !"], "output": "[['fried dumplings', '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 figured we never had Argentinian Pizza before so we grabbed our lunch there , sharing a large Pelligrino , a pizza of two of their specials , one was goat cheese the other blue cheese , and both were excellent ."], "output": "[['Pelligrino', 'large', 'positive'], ['goat cheese', 'excellent', 'positive'], ['blue cheese', '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 ' kamasutra ' and ' bombay cosmopolitan ' are excellent and will have you tipsy in no time ."], "output": "[['kamasutra', 'excellent', 'positive'], ['bombay cosmopolitan', '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 is the perfect date spot for Williamsburg couples ."], "output": "[['date 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": ["The dim sum here is only so-so ."], "output": "[['dim sum', 'so-so', '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": ["Service was slow , but the people were friendly ."], "output": "[['Service', 'slow', 'negative'], ['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": ["The steak was very fatty and the sauce was overpowering and not very tasty ."], "output": "[['steak', 'fatty', 'negative'], ['sauce', 'overpowering', 'negative'], ['sauce', 'not very tasty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 makes you feel at home , the food is great and the atmosphere is WONDERFUL !"], "output": "[['staff', 'great', 'positive'], ['food', 'great', '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 food is alright - some stuff is good - some is not ( like the steak dish which tends to be dry ) ."], "output": "[['steak dish', 'dry', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 diverse menu so its something for everybody ."], "output": "[['menu', 'diverse', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 too busy ordering sushi for dinner and then laying it out to eat on the bar to even bring me my check ."], "output": "[['staff', '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": ["The bagel was huge ."], "output": "[['bagel', 'huge', '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 staff has been nice , but they seemed really stressed and the unisex bathroom needs to be cleaned more often ."], "output": "[['bathroom', 'needs to be cleaned', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 the only thing good about this restaurant ."], "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": ["Service -- friendly and attentive ."], "output": "[['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": ["Great food , great decor , great service ."], "output": "[['food', 'Great', 'positive'], ['decor', '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": ["And , atlhough tables opened up next to us and we ASKED for a slightly larger space , they left us awkardly seated ."], "output": "[['space', 'larger', '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 palak paneer was standard , and I was not a fan of the malai kofta ."], "output": "[['palak paneer', 'standard', '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 've dined at Alain Ducasse 's restaurant in Monte Carlo for half the price for the same excellent dining experience ."], "output": "[['dining', '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": ["There was no ambiance ."], "output": "[['ambiance', '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": ["Save your money and do n't waste your calories , go to Margharita 's on Washington Street instead , they have amazing food and the BEST service ."], "output": "[['food', 'amazing', '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": ["The only weird thing was if we got a bottle , the waitress would have simply multiplied the glass price X4 , which makes no sense whatsoever ."], "output": "[['waitress', '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": ["They sell special sushi , everything have a topping , sauce and etc ."], "output": "[['sushi', 'special', 'positive'], ['sauce', 'special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 small and intimate and you may feel a little crowded , but the service is excellent and it 's great for friends out , a romantic date , or a special occassion ."], "output": "[['service', 'excellent', 'positive'], ['place', 'small', 'negative'], ['place', 'intimate', 'negative'], ['place', '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": ["The service was excellent and the food was delicious ."], "output": "[['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": ["Service was also 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": ["I took my girlfriend there for her birthday last night and we had a relaxing , really good meal ."], "output": "[['meal', 'relaxing', 'positive'], ['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": ["I 'm happy to have Nosh in the neighborhood and the food is very comforting ."], "output": "[['food', 'comforting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 atmosphere , combination of all the hottest music dress code is relatively strict except on Fridays ."], "output": "[['atmosphere', 'Good', 'positive'], ['music', 'hottest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 food ."], "output": "[['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": ["I would highly recommend Nina 's to anyone who wants to have a romantic dinner in a heart warming surrounding filled with candles and family pictures ."], "output": "[['dinner', 'romantic', 'positive'], ['surrounding', 'heart warming', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 something smooth about sipping sake upper east side style ."], "output": "[['sake', '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": ["It 's a nice place to relax and have conversation ."], "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": ["Best Reuben sandwich ever !"], "output": "[['Reuben sandwich', '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": ["Lucky Strike is a great casual place to just grab a bite to eat ."], "output": "[['place', 'great 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": ["Going to Volare is like going to your favorite aunt 's house for dinner , assuming that your aunt is a great Italian cook ."], "output": "[['dinner', '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": ["The sushi has been from average to below average , the wait service has always been subpar the atmosphere goes from nice to really irritating ( if you sit in the area beyond the kitchen , the acousitcs are horrid , everything echoes is extremely loud ) ."], "output": "[['sushi', 'below average', 'negative'], ['wait service', 'subpar', 'negative'], ['area', 'loud', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Frites were delicious if a bit on the thick side ."], "output": "[['Frites', '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 would recommend putting your name down and then getting a drink at a local bar first though because of the wait time ."], "output": "[['drink', 'recommend', 'neutral'], ['bar', '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 fell in love with the egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork ."], "output": "[['egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork', '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": ["Overall , the best bagel in town ."], "output": "[['bagel', '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": ["Light , refreshing summer rolls ( not fried ) remind me of Vietnamese places in Paris ."], "output": "[['summer rolls', '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": ["The sushi seemed pretty fresh and was adequately proportioned ."], "output": "[['sushi', 'fresh', 'positive'], ['sushi', 'proportioned', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was a bit slow ."], "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": ["Spreads and toppings are great - though a bit pricey ."], "output": "[['Spreads', 'great', 'positive'], ['Spreads', 'pricey', 'positive'], ['toppings', 'great', 'positive'], ['toppings', 'pricey', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was very cozy and cute ."], "output": "[['Indoor', 'cozy', 'positive'], ['Indoor', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 3 hour brunch- they definitely do not rush you- and they kept the unlimited mimosas flowing the whole time ."], "output": "[['mimosas', 'unlimited', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 food was excellent , but the entire experience was very cool ."], "output": "[['service', 'excellent', '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": ["The service is good and the resturant is clean ."], "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 cafe itself was really nice with comfortable outdoor chairs and tables , but the service could have been better ."], "output": "[['cafe', 'nice', 'positive'], ['outdoor chairs', 'comfortable', 'positive'], ['tables', 'comfortable', 'positive'], ['service', '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": ["I 've rarely had a problem with slow staff in the 10 years I 've been going ."], "output": "[['staff', 'slow', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ."], "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": ["Although we were looking for regular lettuce and some walnuts the salads we got were great ."], "output": "[['salads', 'great', 'positive'], ['lettuce', 'great', 'neutral'], ['walnuts', '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": ["Excellent lunch buffet for only $ 6.95 ."], "output": "[['lunch buffet', '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": ["Ambience is so cute and quaint , good for business although we were there on vacation ."], "output": "[['Ambience', 'cute', 'positive'], ['Ambience', 'quaint', 'positive'], ['Ambience', '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 portion sizes here are huge , and the sushi is good ."], "output": "[['portion sizes', 'huge', 'positive'], ['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": ["Good food at the restaurant ( a bit expensive , but great if you want to impress your date ) ."], "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": ["I highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service ."], "output": "[['caviar', 'delicious top grade', '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 have eaten there 3-4 times and the food was always 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": ["Grilled whole fish wonderful , great spicing ."], "output": "[['fish', 'wonderful', 'positive'], ['fish', '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 years , I thought Tuscan cuisine was the best , but Salvatore converted me to the hearty Neapolitan fare on my first visit ."], "output": "[['Neapolitan fare', 'hearty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 as well ."], "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": ["Another plus is most of the entrees are approx ."], "output": "[['entrees', 'plus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 moment we walked in they were more than accomodating even though the place was packed ."], "output": "[['place', 'packed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , service and value exceptional everytime I have been there ."], "output": "[['food', 'exceptional', 'positive'], ['service', 'exceptional', 'positive'], ['value', '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": ["We ate at this Thai place following the reviews but very unhappy with the foods ."], "output": "[['foods', 'unhappy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 definitely good , but I left a bit disappointed ."], "output": "[['food', 'good', 'positive'], ['food', '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 drinks are a saving grace , but service staff , please , get over yourselves ."], "output": "[['drinks', 'saving grace', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a downside if you 're ordering in -- the delivery guys have MAJOR attitude ."], "output": "[['delivery guys', 'downside', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The all-Italian staff is warm and engaging from the start ."], "output": "[['staff', 'warm', 'positive'], ['staff', 'engaging', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 exceptionally reasonable for food of this caliber ."], "output": "[['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 filet mignon dish was superb !"], "output": "[['filet mignon dish', '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 been a regular due to the consistently good food and ease of getting a table ."], "output": "[['food', 'good', 'positive'], ['getting a table', 'ease', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 n't expect to like Nosh as much as I did , but the pastrami on challah sandwich I had was otherworldly , the soups are like Mom 's , and the knishes give Yonah Schimmel 's a run for its money ."], "output": "[['pastrami on challah sandwich', '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": ["The atmosphere is nothing special , but it feels like a Sushi establishment in Tokyo ."], "output": "[['atmosphere', 'nothing special', '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": ["Cozy romantic atomosphere with only around 15 tables at most ."], "output": "[['atomosphere', 'Cozy 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 place is worth going even if only for their beer ."], "output": "[['beer', 'worth going', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 was so fun , and the prices were great , on top of the fact that the food was really tasty ."], "output": "[['ambience', 'fun', 'positive'], ['prices', 'great', 'positive'], ['food', '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 sandwhiches are out of this world !"], "output": "[['sandwhiches', '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": ["Decor is charming ."], "output": "[['Decor', '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 food was very well prepared ."], "output": "[['food', 'well 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": ["Good , because hey , it 's more food , but bad because dim sum is supposed to be smaller portions so you can try out more dishes and smaller so that each dish is cheap ."], "output": "[['dim sum', 'bad', 'negative'], ['dim sum', 'smaller', 'negative'], ['food', 'more', 'positive'], ['portions', 'smaller', 'negative'], ['dishes', 'cheap', 'neutral'], ['dish', 'cheap', '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 most people can attest to spending over $ 50 on drinks in New York bars and hardly feeling a thing , the drinks here are plentiful and unique ."], "output": "[['drinks', 'plentiful', 'positive'], ['drinks', '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": ["Complimentary stuff kept coming , and when the waiter saw me opening a gift , I received my dessert on a plate that had Happy Birthday written on it , with a candlevery nice touch , and attentive staff ."], "output": "[['stuff', 'Complimentary', 'positive'], ['staff', '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 arrived 20 minutes after I called , cold and soggy ."], "output": "[['food', 'cold', 'negative'], ['food', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 go for the pre-theatre menu , it 's an even greater deal ."], "output": "[['pre-theatre menu', '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": ["If you are someone who appreciates simplicity , elegance , and wonderfully presented and tasting seafood and vegetables regardless of portion size , Kai is your place ."], "output": "[['seafood', 'wonderfully presented', 'positive'], ['seafood', 'tasting', 'positive'], ['vegetables', 'wonderfully presented', 'positive'], ['vegetables', 'tasting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 usually just get some of the dinner specials and they are very reasonably priced and very tasty ."], "output": "[['dinner specials', 'reasonably priced', 'positive'], ['dinner specials', 'tasty', '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": ["Horrible food and horrible service ."], "output": "[['food', 'Horrible', 'negative'], ['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": ["They treated us well and the food was extremely fresh and well-prepared ."], "output": "[['food', 'fresh', 'positive'], ['food', 'well-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": ["Their exotic salad is basic ly a delicious little green salad with a peanut sauce that is perfect before their sweet basil fried tofu ."], "output": "[['exotic salad', 'delicious', 'positive'], ['green salad', 'delicious little', 'positive'], ['peanut sauce', '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": ["Even if the food was n't this good , the garden is a great place to sit outside and relax ."], "output": "[['food', \"was n't this good\", 'positive'], ['garden', 'great', '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": ["Volare virgins or weekly regulars , everyone gets treated the same and you ca n't ask for more than that when the service is this friendly ."], "output": "[['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 food came out wrong , the waiter was no where to be found and the wine showed up at the end of the meal ."], "output": "[['food', 'wrong', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 steak were seasoned and cooked to perfection , and the lamb sandwhich is great for heartier appetites ."], "output": "[['chicken', 'seasoned', 'positive'], ['chicken', 'perfection', 'positive'], ['steak', 'seasoned', 'positive'], ['steak', 'perfection', 'positive'], ['lamb sandwhich', '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 great and the service was even better ."], "output": "[['food', '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": ["While this can hardly be called a restaurant , it is possibly the best deal in Manhatten : $ 4 for a plate heaped with rice and 2-3 entrees ."], "output": "[['rice', 'best', 'positive'], ['entrees', '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": ["Traditional French decour was pleasant though the hall was rather noisy - the restaurant was full and we had to raise our voices to be able to maintain a conversation ."], "output": "[['Traditional French decour', 'pleasant', 'positive'], ['hall', 'noisy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 son and his girlfriend both wanted cheeseburgers and they were huge !"], "output": "[['cheeseburgers', '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": ["I really recommend the very simple Unda ( Egg ) rolls ."], "output": "[['Unda ( Egg ) rolls', 'recommend', 'positive'], ['Unda ( Egg ) rolls', '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": ["Very good wine choices ."], "output": "[['wine choices', '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 only Thai place I go too in NYC , it 's wonderful , and live relaxed Jazz on certain nights ."], "output": "[['Jazz', '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": ["We were seated and ignored by waitstaff ."], "output": "[['waitstaff', '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": ["Tasty steak , pork loin , the works ."], "output": "[['steak', 'Tasty', 'positive'], ['pork loin', '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 'd highly recommend it for a special occasion -- it provides and intimate setting and nice service ."], "output": "[['setting', 'intimate', 'positive'], ['service', '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 burger was great , also ."], "output": "[['burger', '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 did give a 15 % discount at the end , was n't enough , as they knew the service was horrible ."], "output": "[['discount', \"was n't enough\", 'negative'], ['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": ["The pizza was great ."], "output": "[['pizza', '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 had never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ."], "output": "[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', '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": ["however , it 's the service that leaves a bad taste in my mouth ."], "output": "[['service', 'bad 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": ["The price was extremely reasonable for the appetizers and food we ate ."], "output": "[['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": ["Do n't dine at Tamarind for the vegetarian dishes , they are simply not up to par with the non-veg selections ."], "output": "[['vegetarian dishes', 'not up to 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": ["They need a kick out of it but until then the sushi is pretty good and the place is consistent ."], "output": "[['sushi', 'good', 'positive'], ['place', 'consistent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to wait only a few times during lunch but this place is definitely worth the wait ."], "output": "[['wait', 'worth', 'positive'], ['wait', '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": ["All in all the food was above average and I would return to see how they operate with four or less dinners ."], "output": "[['food', 'above average', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delicious food , excellent service , and a pretty atmosphere make this a great choice for dinner and the $ 5.99 lunch buffet makes it an even better choice for lunch !"], "output": "[['food', 'Delicious', 'positive'], ['service', 'excellent', 'positive'], ['atmosphere', 'pretty', 'positive'], ['lunch buffet', 'better', 'positive'], ['dinner', 'great', 'positive'], ['lunch', '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 appetizers , I recommend the shrimp fritters and dumplings ."], "output": "[['shrimp fritters', 'recommend', 'positive'], ['dumplings', '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": ["Such nice people working here - but I have to review the food ."], "output": "[['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": ["The restaurant is dark and not very attractive and then you have spot lights shining on you putting you in the worst light possible , reaching for sunglasses ."], "output": "[['spot lights', '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": ["Great wine , great food ."], "output": "[['wine', '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": ["The service was mediocre , and the lack of air conditioning made for a less than comfortable meal ."], "output": "[['service', 'mediocre', 'neutral'], ['air conditioning', 'lack', 'negative'], ['meal', 'comfortable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 staff always surprise me with the new heights they are taken to ."], "output": "[['food', 'surprise', 'positive'], ['staff', '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": ["honestly the worst sushi my husband and i had in our entire lives ."], "output": "[['sushi', '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": ["However , if you want great food at a great price and do n't mind the decor , you ca n't beat this place ."], "output": "[['food', 'great', 'positive'], ['price', 'great', 'positive'], ['decor', \"do n't mind\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 makes this restaurant special are the authentic sichuan cooking and being the only one in NYC that offers authentic chongqing hotpot ."], "output": "[['sichuan cooking', 'authentic', 'positive'], ['chongqing hotpot', '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": ["Interesting other dishes for a change include chicken in curry sauce and salmon caserole ."], "output": "[['dishes', 'Interesting', 'positive'], ['salmon caserole', 'Interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 my favorites though was the Angry Lobster , a cold lobster salad that was magnificent ."], "output": "[['Angry Lobster', 'favorites', 'positive'], ['cold lobster salad', 'magnificent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ask for Usha , the nicest bartender in manhattan ."], "output": "[['bartender', '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": ["The service is outstanding and my crab-cake eggs benedict could not have been better ."], "output": "[['service', 'outstanding', 'positive'], ['crab-cake eggs benedict', 'could not have been 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 place 's decor and hidden bathrooms made for a good laugh ."], "output": "[['decor', 'good laugh', 'positive'], ['bathrooms', 'good laugh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 location is good and the fact that Hutner College is near and their prices are very reasonable , makes students go back to Suan again and again ."], "output": "[['location', 'good', '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": ["Deliveries often take up to an hour and the prices are higher than most other pizzerias in the area ."], "output": "[['prices', '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": ["Because of the delicate thin crust , take-out pies get soggy in their boxes ."], "output": "[['take-out pies', 'soggy', 'negative'], ['crust', 'delicate', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always very crowded and popular ."], "output": "[['place', 'crowded', 'positive'], ['place', 'popular', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 changes frequently but the basic dishes are always available ."], "output": "[['selection', 'changes frequently', 'neutral'], ['basic dishes', '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 to say that if this what makes it easier to get a saet a lunch -- I dont mind ."], "output": "[['lunch', 'easier', '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": ["We were told that they were booked solid and no other table was available ."], "output": "[['table', 'available', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 dealing with subpar pizza all over the Kensington neighborhood - I 've found little toninos ."], "output": "[['pizza', 'subpar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 table has a pot of boiling water sunken into its surface , and you get platters of thin sliced meats , various vegetables , and rice and glass noodles ."], "output": "[['meats', 'thin', 'neutral'], ['vegetables', 'various', '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": ["Judging from previous posts this used to be a good place , but not any longer ."], "output": "[['place', '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": ["We , there were four of us , arrived at noon - the place was empty - and the staff acted like we were imposing on them and they were very rude ."], "output": "[['staff', '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 food was lousy - too sweet or too salty and the portions tiny ."], "output": "[['food', 'lousy', 'negative'], ['food', 'too sweet', 'negative'], ['food', 'too salty', 'negative'], ['portions', '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": ["Avoid this 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": ["I have eaten at Saul , many times , the food is always consistently , outrageously 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": ["Saul is the best restaurant on Smith Street and in Brooklyn ."], "output": "[['Saul', '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 duck confit is always amazing and the foie gras terrine with figs was out of this world ."], "output": "[['foie gras terrine with figs', 'out of this world', 'positive'], ['duck confit', '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 interesting and has many good values ."], "output": "[['wine list', 'interesting', 'positive'], ['wine list', 'good values', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very disappointed with this restaurant ."], "output": "[['restaurant', '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": ["Food was okay , nothing great ."], "output": "[['Food', 'okay', 'neutral'], ['Food', 'nothing 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": ["Chow fun was dry ; pork shu mai was more than usually greasy and had to share a table with loud and rude family ."], "output": "[['Chow fun', 'dry', 'negative'], ['pork shu mai', '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": ["I/we will never go back to this place again ."], "output": "[['place', 'never go back', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 devine , oysters where a sensual as they come , and the price ca n't be beat ! ! !"], "output": "[['Service', 'devine', 'positive'], ['oysters', 'sensual', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always cooked to perfection , the service is excellent , the decor cool and understated ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 duck breast special on my last visit and it was incredible ."], "output": "[['duck breast special', '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 only thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree ."], "output": "[['Grilled Chicken special with Edamame Puree', '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 never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ."], "output": "[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', '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": ["Their sake list was extensive , but we were looking for Purple Haze , which was n't listed but made for us upon request !"], "output": "[['sake 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": ["We went around 9:30 on a Friday and it had died down a bit by then so 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": ["Food awesome ."], "output": "[['Food', '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": ["Service friendly and attentive ."], "output": "[['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 is decent ."], "output": "[['food', '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": ["This place has got to be the best japanese restaurant in the new york area ."], "output": "[['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": ["Food is 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": ["Service is top notch ."], "output": "[['Service', '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": ["We took advanatage of the half price sushi deal on saturday so it was well worth it ."], "output": "[['half price sushi deal', '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": ["In the evening , this place attracted a well dressed , with it , NY crowd ."], "output": "[['crowd', 'attracted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["$ 6 and there is much tasty food , all of it fresh and continually refilled ."], "output": "[['food', 'tasty', 'positive'], ['food', 'fresh', 'positive'], ['food', 'refilled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not a vegetarian but , almost all the dishes were great ."], "output": "[['dishes', '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 is rather good , but only if you like to wait for it ."], "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": ["I like the somosas , chai , and the chole , but the dhosas and dhal were kinda disappointing ."], "output": "[['somosas', 'like', 'positive'], ['chai', 'like', 'positive'], ['chole', 'like', 'positive'], ['dhosas', 'disappointing', 'negative'], ['dhal', '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": ["The service varys from day to day- sometimes they 're very nice , and sometimes not ."], "output": "[['service', 'varys', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , specify if you like your food spicy- its rather bland if you do n't ."], "output": "[['food', '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 ambience is pretty and nice for conversation , so a casual lunch here would probably be best ."], "output": "[['ambience', 'pretty', '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": ["The lava cake dessert was incredible and I recommend it ."], "output": "[['lava cake dessert', 'incredible', 'positive'], ['lava cake dessert', '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": ["Once you step into Cosette , you 're miraculously in a small , off-the-beaten path Parisian bistro ."], "output": "[['Cosette', 'off-the-beaten', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tiny restaurant is as cozy as it gets , with that certain Parisian flair ."], "output": "[['restaurant', 'tiny', 'positive'], ['restaurant', '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 pizza was delivered cold and the cheese was n't even fully melted !"], "output": "[['pizza', 'cold', 'negative'], ['cheese', \"was n't even fully melted\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 overpriced and soggy ."], "output": "[['pizza', 'overpriced', 'negative'], ['pizza', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 use fancy ingredients , but even fancy ingredients do n't make for good pizza unless someone knows how to get the crust right ."], "output": "[['ingredients', 'fancy', 'positive'], ['pizza', '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 think I 've had some the best meals of my life at minnow ."], "output": "[['meals', '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 seafood is amazing , there 's a good wine list , and the ever-changing menu always offers some great surprises ."], "output": "[['seafood', 'amazing', 'positive'], ['wine list', 'good', 'positive'], ['menu', 'ever-changing', 'positive'], ['menu', 'great 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": ["The combination of super-fresh ingredients in the dishes are unusual but really delicious ."], "output": "[['ingredients', 'super-fresh', 'positive'], ['ingredients', '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": ["Best Pastrami I ever had and great portion without being ridiculous ."], "output": "[['Pastrami', 'Best', 'positive'], ['portion', '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 wife had the fried shrimp which are huge and loved it ."], "output": "[['fried shrimp', 'huge', 'positive'], ['fried shrimp', '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": ["As a Japanese native , I 've lived in the Tristate area for over 8 years , but I was just so amazed at this place ."], "output": "[['place', '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": ["The signs , the specials menus , food , and even all the waitstaff are ALL TOTALLY Japanese ."], "output": "[['signs', 'Japanese', 'positive'], ['specials menus', 'Japanese', 'positive'], ['food', 'Japanese', 'positive'], ['waitstaff', 'Japanese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 worth an one-hour drive ."], "output": "[['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": ["My wife and I always enjoy the young , not always well trained but nevertheless friendly , staff , all of whom have a story ."], "output": "[['staff', 'enjoy', 'positive'], ['staff', 'young', 'positive'], ['staff', 'not always well trained', '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": ["Decent wine at reasonable prices ."], "output": "[['wine', '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": ["This is by far my favorite place in the neighborhood ."], "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": ["The service is excellent , the decor is great , and the food is delicious and comes in large portions ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'great', 'positive'], ['food', 'delicious', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 partial to the Gnocchi ."], "output": "[['Gnocchi', 'partial', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 incredibly 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": ["The hostess is rude to the point of being offensive ."], "output": "[['hostess', 'rude', 'negative'], ['hostess', '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": ["We have been to this place many times , and always have great food , wine , and service ."], "output": "[['food', 'great', 'positive'], ['wine', '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": ["We were worried we would have trouble getting in , but somehow managed to have a short wait ."], "output": "[['wait', 'short', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always we had a great glass of wine while we waited ."], "output": "[['glass 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": ["When we sat , we got great and fast service ."], "output": "[['service', 'great', 'positive'], ['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": ["The people that work there are always so friendly you forget you are in New York sometimes ."], "output": "[['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": ["Make sure you try this place as often as you can ."], "output": "[['place', '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 is a fun restaurant to go to ."], "output": "[['restaurant', '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": ["The pizza is yummy and I like the atmoshpere ."], "output": "[['pizza', 'yummy', 'positive'], ['atmoshpere', '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": ["But the pizza is way to expensive ."], "output": "[['pizza', '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": ["Sauce was watery and the food did n't have much flavor ."], "output": "[['Sauce', 'watery', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 great ."], "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 waitress was very patient with us and the food is phenomenal !"], "output": "[['waitress', 'patient', 'positive'], ['food', '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": ["Service was prompt , friendly and great ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'friendly', '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 pizza and fantastic service ."], "output": "[['pizza', 'Great', '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": ["There was a small wait , but shorter than I expected ."], "output": "[['wait', 'small', 'positive'], ['wait', 'shorter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 best sushi in new york city - hands down ."], "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": ["Planet Thailand has always been a hit with me , I go there usually for the sushi , which is great , the thai food is excellent too ."], "output": "[['sushi', 'great', 'positive'], ['thai food', 'excellent', 'positive'], ['Planet Thailand', '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": ["With the great variety on the menu , I eat here often and never get bored ."], "output": "[['menu', 'great 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": ["The atmosphere is n't the greatest , but I suppose that 's how they keep the prices down ."], "output": "[['atmosphere', \"is n't the greatest\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 crunchy tuna , it is to die for ."], "output": "[['crunchy tuna', 'Try', 'positive'], ['crunchy tuna', '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": ["First went here to enjoy their garden terrace ."], "output": "[['garden terrace', '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 food was amazing , and the service was prompt and helpful , but not over-bearing or rushed ."], "output": "[['food', 'amazing', 'positive'], ['service', 'prompt', 'positive'], ['service', 'helpful', 'positive'], ['service', 'not over-bearing or rushed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 Tartare is a great bet , they fix it for you at the table ."], "output": "[['Steak Tartare', '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 may be a bit packed on weekends , but the vibe is good and it is the best French food you will find in the area ."], "output": "[['vibe', 'good', 'positive'], ['French 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": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best , freshly baked bread !"], "output": "[['crust', '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": ["Not sure where the previous reviewer , lonk , dined , but Saul is in a great neighborhood and has great food !"], "output": "[['neighborhood', '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": ["I 'd highly recommend it for a special occasion -- it provides and intimate setting and nice service ."], "output": "[['setting', 'intimate', 'positive'], ['service', '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 'm not sure where the other reviewers ate but it seems as if we visited two different restaurants because my friends and I all enjoy Mizu very much ... and we 're repeat customers ."], "output": "[['Mizu', '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": ["Moules were excellent , lobster ravioli was VERY salty !"], "output": "[['Moules', 'excellent', 'positive'], ['lobster ravioli', 'salty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Took my mom for Mother 's Day , and the maitre d ' was pretty rude ."], "output": "[[\"maitre d '\", '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": ["Tiny dessert was $ 8.00 ... just plain overpriced for what it is ."], "output": "[['dessert', 'Tiny', 'negative'], ['dessert', '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": ["The drinks are always well made and wine selection is fairly priced ."], "output": "[['drinks', 'well made', 'positive'], ['wine selection', '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": ["Try their chef 's specials -- they are to die for ."], "output": "[[\"chef 's specials\", 'Try', 'positive'], [\"chef 's specials\", '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": ["Downstairs lounge is always a good attraction"], "output": "[['Downstairs lounge', 'good attraction', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Raga 's is a romantic , cozy restaurant ."], "output": "[[\"Raga 's\", 'romantic', 'positive'], [\"Raga 's\", '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 exotic food is beautifully presented and is a delight in delicious combinations ."], "output": "[['exotic food', 'beautifully presented', 'positive'], ['exotic food', '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": ["The staff is incredibly helpful and attentive ."], "output": "[['staff', 'helpful', 'positive'], ['staff', '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 bar is very well stocked with interesting beers and well priced wines ."], "output": "[['bar', 'well stocked', 'positive'], ['beers', 'interesting', 'positive'], ['wines', 'well 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": ["Rude service , medicore food ... there are tons of restaurants in NY ... stay away from this one"], "output": "[['service', 'Rude', 'negative'], ['food', 'medicore', '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 a great time at Jekyll and Hyde !"], "output": "[['Jekyll and Hyde', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 loved everythig about it-especially the shows and actors ."], "output": "[['shows', 'loved', 'positive'], ['actors', '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": ["Our server was very helpful and friendly ."], "output": "[['server', 'helpful', '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 food was good too ."], "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 outdoor atmosphere of sitting on the sidewalk watching the world go by 50 feet away on 6th avenue on a cool evening was wonderful ."], "output": "[['outdoor atmosphere', '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 service , great food ."], "output": "[['service', '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": ["Two complaints -- their appetizer selection stinks , it would be nice to get some mozzarella sticks on the menu ."], "output": "[['appetizer selection', 'complaints', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wait staff is blantently unappreciative of your business but its the best pie on the UWS !"], "output": "[['Wait staff', 'unappreciative', 'negative'], ['pie', '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": ["By far the best salad I have had in a fast food restaurant ."], "output": "[['salad', '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": ["fine dining restaurant quality ."], "output": "[['dining', '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": ["On a recent Sunday afternoon , a friend and I accidently found this great restaurant on our way to see the pulitzer prize winning play DOUBT ."], "output": "[['restaurant', '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 chicken pot pie is exceptional , the cheeseburger huge and delictable , and the service professional wan warm ."], "output": "[['chicken pot pie', 'exceptional', 'positive'], ['cheeseburger', 'huge', 'positive'], ['cheeseburger', 'delictable', 'positive'], ['service', 'professional', 'positive'], ['service', 'warm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 no nonsense ."], "output": "[['staff', 'no nonsense', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 lived upstate for a while I would buy freeze the bagels and they would still be better than any else ."], "output": "[['bagels', '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": ["Worth visiting the 1st Ave spot because it is the original store ."], "output": "[['1st Ave spot', 'Worth visiting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["He served me an Uni Hand roll , which I never had before , and let me tell you ... IT WAS HEAVEN !"], "output": "[['Uni Hand roll', 'HEAVEN', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sake menu should not be overlooked !"], "output": "[['sake menu', 'overlooked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good - prompt , attentive and non-intrusive ."], "output": "[['Service', 'good', 'positive'], ['Service', 'prompt', 'positive'], ['Service', 'attentive', 'positive'], ['Service', 'non-intrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good as well , considering that we tried the budget selection ( though I wish the pork belly that I ordered was roasted a bit longer , so that fat was more of a melt-in-your-mouth experience ) ."], "output": "[['Food', '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": ["Traditional French decour was pleasant though the hall was rather noisy - the restaurant was full and we had to raise our voices to be able to maintain a conversation ."], "output": "[['Traditional French decour', 'pleasant', 'positive'], ['hall', 'noisy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 been to at Cafe Spice probably 5-8 times , it is probably still the best Indian restaurant around Union Square ."], "output": "[['Cafe Spice', '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": ["To sum it up : Service varies from good to mediorce , depending on which waiter you get ; generally it is just average Ok ."], "output": "[['Service', 'varies', '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": ["Seating is always prompt , though the restaurant does fill up in the evening ."], "output": "[['Seating', '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": ["Food is usually very good , though ocasionally I wondered about freshmess of raw vegatables in side orders ."], "output": "[['Food', 'good', 'positive'], ['raw vegatables in side orders', 'wondered about freshmess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 vibrant and eye-pleasing with several semi-private boths on the right side of the dining hall , which are great for a date ."], "output": "[['decor', 'vibrant', 'positive'], ['decor', 'eye-pleasing', 'positive'], ['semi-private boths', 'eye-pleasing', 'positive'], ['semi-private boths', '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 simply the best meal in NYC ."], "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": ["If we were to move from the upper east side , we would genuinely miss this restaurant ."], "output": "[['restaurant', '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": ["The restaurant is cute but not upscale ."], "output": "[['restaurant', 'cute', 'neutral'], ['restaurant', 'not 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": ["The food is a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes ."], "output": "[['food', 'diamond', 'positive'], ['balance of herbs and tomatoes', '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 had a great time at the Jekyll and hyde Pub last night ."], "output": "[['Jekyll and hyde Pub', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really enjoying ourselves at the bar we sat down at a table and had dinner ."], "output": "[['bar', 'enjoying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The server was really cool and served us our food and drinks with a smile ."], "output": "[['server', '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 place 's decor and hidden bathrooms made for a good laugh ."], "output": "[['decor', 'good laugh', 'positive'], ['hidden bathrooms', 'good laugh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 visiting this restaurant and having dinner and drinks !"], "output": "[['restaurant', '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": ["If you are the type of person who likes being scared and entertained , this is a great place to go and eat ."], "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 have over 100 different beers to offer thier guest so that made my husband very happy and the food was delicious , if I must recommend a dish it must be the pumkin tortelini ."], "output": "[['beers', 'happy', 'positive'], ['food', 'delicious', 'positive'], ['pumkin tortelini', '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 entertainment was great they have shows that go on through out the dinner ."], "output": "[['entertainment', '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 bagel was huge ."], "output": "[['bagel', '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 was my frist time at Cafe St. Bart 's and I must say how delicious the food and the service was ."], "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": ["Other guests enjoyed pizza , santa fe chopped salad and fish and chips ."], "output": "[['pizza', 'enjoyed', 'positive'], ['santa fe chopped salad', 'enjoyed', 'positive'], ['fish and chips', '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 highly recommend Cafe St. Bart 's for their food , the ambience and wonderful service ."], "output": "[['food', 'recommend', 'positive'], ['ambience', 'recommend', 'positive'], ['service', 'recommend', 'positive'], ['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": ["All the staff is absolutely professional ! !"], "output": "[['staff', '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": ["This restaurant was way overhyped ."], "output": "[['restaurant', 'overhyped', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 chow fun and chow see was really bland and oily ."], "output": "[['chow fun and chow see', 'bland', 'negative'], ['chow fun and chow see', '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": ["The service was the only thing good about this restaurant ."], "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": ["It 's boring on the inside , and our sushi was pretty below average ... the tuna was soggy and the other rolls had no flavor ."], "output": "[['sushi', 'below average', 'negative'], ['tuna', 'soggy', 'negative'], ['rolls', 'no flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 pad penang is delicious and everything else is fantastic ."], "output": "[['pad penang', '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 price is reasonable although the service is poor ."], "output": "[['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": ["fresh restaurant was amazing ... ... .. food was delicious and of course fresh ."], "output": "[['fresh restaurant', 'fresh', 'positive'], ['fresh restaurant', 'amazing', 'positive'], ['food', 'delicious', 'positive'], ['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": ["Hats off to the chef ."], "output": "[['chef', 'Hats off', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the salads are delicious , both refreshing and very spicy ."], "output": "[['salads', 'delicious', 'positive'], ['salads', 'refreshing', 'positive'], ['salads', 'spicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Pam 's special fried fish and it was amazing ."], "output": "[[\"Pam 's special fried fish\", '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": ["Great vibe , lots of people ."], "output": "[['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": ["I did n't complain , I liked the atmosphere so much ."], "output": "[['atmosphere', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ambience is so cute and quaint , good for business although we were there on vacation ."], "output": "[['Ambience', 'cute', 'positive'], ['Ambience', 'quaint', 'positive'], ['Ambience', '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": ["Although we were looking for regular lettuce and some walnuts the salads we got were great ."], "output": "[['salads', '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": ["Ingredients are organic which is a real plus for me ."], "output": "[['Ingredients', 'organic', 'positive'], ['Ingredients', 'plus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 some really good , inexpensive sushi ."], "output": "[['sushi', 'good', 'positive'], ['sushi', '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 Tuna roll is huge and probably the best that I 've had at this price range ."], "output": "[['spicy Tuna roll', 'huge', '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": ["The Yellowtail was particularly good as well ."], "output": "[['Yellowtail', '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 reservations about the all you can eat deal , however -- the choices are fairly limited and you can probably order more food than you can eat for less than $ 18 by just going off the menu ."], "output": "[['all you can eat deal', '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": ["Big Wong gets big Ups for a fine establishment ."], "output": "[['Big Wong', 'big Ups', 'positive'], ['Big Wong', '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": ["They have it all -- great price , food , and service ."], "output": "[['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": ["The atmosphere is noisy and the waiters are literally walking around doing things as fast as they can ."], "output": "[['atmosphere', 'noisy', 'negative'], ['waiters', '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": ["This place is always very crowded and popular ."], "output": "[['place', 'crowded', 'positive'], ['place', 'popular', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a very nice Caesar Salad while my wife had arugula and goat cheese ... .both very tasty ."], "output": "[['Caesar Salad', 'Enjoyed', 'positive'], ['Caesar Salad', 'nice', 'positive'], ['arugula and goat cheese', '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": ["We both opted for a pasta dish and they were served timely and fresh ."], "output": "[['pasta dish', 'served timely', 'positive'], ['pasta dish', '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": ["We concluded with tiramisu chocolate cake , both were delicious ."], "output": "[['tiramisu chocolate cake', '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 recently went to this restaurant with some co-workers for lunch and had an amazing time ."], "output": "[['restaurant', 'amazing time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["sometimes i get good food and ok service ."], "output": "[['food', 'good', 'positive'], ['service', '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": ["sometimes i get bad food and bad service , sometimes i get good good and bad service ."], "output": "[['food', 'bad', 'negative'], ['service', 'bad', 'negative'], ['good', '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 evaluated on those terms Pastis is simply wonderful ."], "output": "[['Pastis', '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": ["Mine was a little burnt but still delicious with goat cheese and panchetta ( raddichio was kind of bitter though ) ."], "output": "[['raddichio', 'bitter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got the mushroom pizza which tasted better ."], "output": "[['mushroom pizza', '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 sangria was pretty tasty and good on a hot muggy day ."], "output": "[['sangria', 'tasty', '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": ["Kind of a small place but I guess if they are not too busy might be able to fit a group or kids ."], "output": "[['place', 'small', '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 started out with a Bombay beer which was big enough for two ."], "output": "[['Bombay beer', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 slow , but the people were friendly ."], "output": "[['Service', 'slow', 'negative'], ['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": ["The food is authentic Italian - delicious !"], "output": "[['food', 'authentic Italian', '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": ["Pizza is terrific , as is homemade pasta ."], "output": "[['Pizza', 'terrific', 'positive'], ['homemade pasta', '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": ["Ambience is delightful , service impeccable ."], "output": "[['Ambience', 'delightful', 'positive'], ['service', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 still mad that i had to pay for lousy food ."], "output": "[['food', '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": ["The hanger steak was like rubber and the tuna was flavorless not to mention it tasted like it had just been thawed ."], "output": "[['hanger steak', 'rubber', 'negative'], ['tuna', 'flavorless', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 also horrible and the ambience is not that great ."], "output": "[['Service', 'horrible', 'negative'], ['ambience', 'not that great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 small cute restaurant ."], "output": "[['restaurant', 'small cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 absolutely 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": ["We wo n't go to this place again for a good meal ."], "output": "[['meal', '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": ["However , I think this place is a good hang out spot ."], "output": "[['place', '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 Pizza and wine were excellent -- the service too -- but what really MADE this place was the backyard dining area ."], "output": "[['Pizza', 'excellent', 'positive'], ['wine', 'excellent', '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": ["It is one the nicest outdoor restaurants I have ever seen in NY -- I am from Italy and this place rivals the ones in my country ."], "output": "[['outdoor restaurants', '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": ["First of all , this place is *not* romantic , as claimed by Citysearch 's editorial review ."], "output": "[['place', '*not* romantic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The tables are crammed way too close , the menu is typical of any Italian restaurant , and the wine list is simply overpriced ."], "output": "[['tables', 'crammed', 'negative'], ['tables', 'too close', 'negative'], ['menu', 'typical', 'neutral'], ['wine list', '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": ["Slightly above average wines start at $ 70+ with only one selection listed at $ 30+ ."], "output": "[['wines', 'above 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 is not what one would expect from a joint in this price category ."], "output": "[['Service', 'not what one would expect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Somehow working the italian charm with constant mille grazie does not constitute proper service ."], "output": "[['service', 'not constitute proper', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 one of our meals was edible - bland and/or made with weird rosemary or orange flavoring ."], "output": "[['meals', 'edible', 'negative'], ['rosemary or orange flavoring', '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": ["Fish was overdone ."], "output": "[['Fish', 'overdone', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Cute place , nice wait staff but would never go there again ."], "output": "[['wait staff', 'nice', 'positive'], ['place', 'Cute', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Someone else recommended the dessert - we also left that ."], "output": "[['dessert', 'recommended', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Skip this restaurant , it 's a big disappointment ."], "output": "[['restaurant', 'Skip', 'negative'], ['restaurant', '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": ["Myagi is one of my favorite restaurants in the City ; the place the negative reviews describe sound like they were somewhere else ."], "output": "[['Myagi', '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 've never had bad service and the fish is fresh and delicious ."], "output": "[['service', 'never had bad', 'positive'], ['fish', 'fresh', 'positive'], ['fish', '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": ["Their tuna tartar appetizer is to die for ."], "output": "[['tuna tartar appetizer', '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": ["I come from a family of pizzeria owners , and I 'm almost ashamed to say that the pizza in Fornino 's blows my families receipies away ."], "output": "[['pizza', 'ashamed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 so cool and the service is prompt and curtious ."], "output": "[['service', 'prompt', 'positive'], ['service', 'curtious', 'positive'], ['place', '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 highly recommend to anyone to give this place a try ."], "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": ["A restaurant that does n't try to do anything except serve great food with great service in a pleasant atmosphere ."], "output": "[['food', 'great', 'positive'], ['service', 'great', 'positive'], ['atmosphere', '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": ["The dining room is quietly elegant with no music to shout over -- how refreshing !"], "output": "[['dining room', 'elegant', 'positive'], ['dining room', '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": ["The service was impeccable and unobtrusive -- the staff knows what they are there to do -- to know their menu , present your meal , and attend to your needs ."], "output": "[['service', 'impeccable', 'positive'], ['service', 'unobtrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Looking around , I saw a room full of New Yorkers enjoying a real meal in a real restaurant , not a clubhouse of the fabulous trying to be seen ."], "output": "[['meal', 'real', 'positive'], ['restaurant', 'real', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The view is breathtaking the service is top notch ... the ambiance is wonderful ."], "output": "[['view', 'breathtaking', 'positive'], ['service', 'top notch', 'positive'], ['ambiance', '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 staff offers impeccable service ."], "output": "[['staff', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque ."], "output": "[['New England Chowder', 'good', 'positive'], ['Lobster Bisque', 'award', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 boyfriend had Prime Rib it was good ."], "output": "[['Prime Rib', '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 like spicy food get the chicken vindaloo ."], "output": "[['chicken vindaloo', 'get', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to Volare for 1st class service and terrific food ."], "output": "[['service', '1st class', 'positive'], ['food', '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 portions are large and the servers always surprise us with a different starter ."], "output": "[['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 excellent ."], "output": "[['wine list', '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 food is amazing ... especially if you get the Chef 's tasting menu and your favourite bottle ( or two ! ) of wine from an extensive selection of wines ."], "output": "[['food', 'amazing', 'positive'], ['selection of wines', '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": ["The place is small and intimate and you may feel a little crowded , but the service is excellent and it 's great for friends out , a romantic date , or a special occassion ."], "output": "[['service', 'excellent', 'positive'], ['place', 'small', 'positive'], ['place', 'intimate', 'positive'], ['place', 'crowded', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you do n't like ."], "output": "[['food', 'pricey', 'negative'], ['prixe fixe tasting menu', '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": ["With the exception of our lemon salad that had so much pepper on it that our eyes started watering , the food here was decent , not great ."], "output": "[['food', 'decent', 'neutral'], ['food', 'not great', 'neutral'], ['lemon salad', 'exception', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 very limited - i think we counted 4 or 5 entrees ."], "output": "[['menu', '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 ordered the special , grilled branzino , that was so infused with bone , it was difficult to eat ."], "output": "[['grilled branzino', 'difficult to 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": ["The decor in this place is very diner-ish and the kind of place you expect in the East Village - not romantic , just simple , small and sparse ."], "output": "[['decor', 'diner-ish', '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 place is so much fun ."], "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": ["Our family never expected such incredible entertainment in a restaurant ."], "output": "[['entertainment', '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 staff was the friendliest that have seen in New York ."], "output": "[['staff', 'friendliest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 something really different than try Jekyll and Hyde ."], "output": "[['Jekyll and Hyde', '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": ["The food was pretty tradional but it was hot and good with large portions ."], "output": "[['food', 'tradional', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 lot of fun ."], "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": ["The characters really make for an enjoyable experience ."], "output": "[['characters', '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": ["However , I think Jeckll and Hydes t is one of those places that is fun to do once ."], "output": "[['Jeckll and Hydes', '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": ["Service was slow had to wait to order and get food although not crowded ."], "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": ["Drinks way over priced ."], "output": "[['Drinks', '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": ["Food was good not great not worth the wait or another visit"], "output": "[['Food', 'good not great not worth the wait or another visit', '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": ["Great pizza for lunch place ."], "output": "[['pizza', '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": ["Service was 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": ["The pizza was great ."], "output": "[['pizza', '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": ["Whenever you need a Sushi fix , Mizu will be there with quality fish and great service ."], "output": "[['fish', 'quality', '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": ["Delivery is fast too ."], "output": "[['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": ["Great friendly service , Fast seating , Fast Delivery , Excellent sushi ."], "output": "[['service', 'Great friendly', 'positive'], ['seating', 'Fast', 'positive'], ['Delivery', 'Fast', 'positive'], ['sushi', '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": ["Ess-A-Bagel ( either by Sty-town or midtown ) is by far the best bagel in NY ."], "output": "[['bagel', '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 bagels always warm , soft on the inside , crispy on the outside and enormous in size ."], "output": "[['bagels', 'warm', 'positive'], ['bagels', 'soft', 'positive'], ['bagels', 'crispy', 'positive'], ['bagels', 'enormous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 huge selection of different cream cheeses and all of their salads are great ."], "output": "[['salads', 'great', 'positive'], ['cream cheeses', 'huge', 'positive'], ['cream cheeses', '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": ["The lox is always fresh too ."], "output": "[['lox', '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": ["Not impressed with the food ."], "output": "[['food', 'Not impressed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Zero ambiance to boot ."], "output": "[['ambiance', 'Zero', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 this place was totally overrated ."], "output": "[['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": ["The ambience was nice , but service was n't so great ."], "output": "[['ambience', 'nice', 'positive'], ['service', \"was n't so great\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 BEST Shabu-Shabu Restaurant in the Try-State Area ."], "output": "[['Shabu-Shabu 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": ["The atmosphere is nothing special , but it feels like a Sushi establishment in Tokyo ."], "output": "[['atmosphere', 'nothing special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and staff are all Japanese as well and that adds to the entire ambiance ."], "output": "[['ambiance', 'adds', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Taxan delicious !"], "output": "[['Taxan', '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 green curry with vegetables ."], "output": "[['green curry with vegetables', '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 quantity is also very good , you will come out satisfied ."], "output": "[['quantity', 'good', 'positive'], ['quantity', '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": ["The service is ok , some of the people did n't get what they asked for ."], "output": "[['service', '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 had the best ravioli ever ."], "output": "[['ravioli', '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 wine the service was very good too ."], "output": "[['wine', 'good', '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 quaint and romantic trattoria is at the top of my Manhattan restaurant list ."], "output": "[['trattoria', 'quaint', 'positive'], ['trattoria', '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 is delicious - from the specials to the regular menu-fare , the dishes are never a disappointment ."], "output": "[['food', 'delicious', 'positive'], ['dishes', 'never a disappointment', 'positive'], ['specials', 'delicious', 'positive'], ['specials', 'never a disappointment', 'positive'], ['regular menu-fare', 'delicious', 'positive'], ['regular menu-fare', 'never a disappointment', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the tables may be closely situated , the candle-light , food quality and service overcompensate ."], "output": "[['candle-light', 'overcompensate', 'positive'], ['food', 'overcompensate', 'positive'], ['service', 'overcompensate', 'positive'], ['tables', 'closely situated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 go , try the marinara/arrabiatta sauce , the mozzarella en Carozza is mmmmmmmm ... .. everything is just delicious ."], "output": "[['marinara/arrabiatta sauce', 'try', 'positive'], ['marinara/arrabiatta sauce', 'delicious', 'positive'], ['mozzarella en Carozza', '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": ["Check out the secret back room ."], "output": "[['back room', 'secret', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 authentic ."], "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": ["Who has room for Cheesesticks with the best pizza in NYC !"], "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": ["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": ["The food is good , I ca n't lie ."], "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 hostess and the waitress were incredibly rude and did everything they could to rush us out ."], "output": "[['hostess', 'rude', 'negative'], ['waitress', '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": ["Amma is nothing special ."], "output": "[['Amma', 'nothing special', '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 ate here a week ago and found most dishes average at best and too expensive ."], "output": "[['dishes', 'average', 'negative'], ['dishes', 'too 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": ["This place is always packed ."], "output": "[['place', 'packed', '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": ["Most importantly , food is 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": ["and yes Dal Bukhara is so dam good and so are all the kababs ."], "output": "[['kababs', 'good', 'positive'], ['Dal Bukhara', '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": ["Haru on Park S is simply disgusting ."], "output": "[['Haru on Park S', '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 fish was not fresh and the rice tasted old and stale ."], "output": "[['fish', 'not fresh', 'negative'], ['rice', 'old', 'negative'], ['rice', 'stale', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Quite frankly , this is some of the worst sushi I have ever tried ."], "output": "[['sushi', '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": ["honestly the worst sushi my husband and i had in our entire lives ."], "output": "[['sushi', '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": ["not sure why this restaurant would be rated that highly ."], "output": "[['restaurant', 'highly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the all-u-can-eat sushi is definitely in very poor quality ."], "output": "[['all-u-can-eat sushi', 'poor quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 things u could really taste are the very salty soy sauce ( even its low sodium ) , the vinegar-soaked rice , and the scallion on top of the fish ."], "output": "[['soy sauce', 'salty', 'negative'], ['rice', 'vinegar-soaked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the waitstaffs are nice though ."], "output": "[['waitstaffs', '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 have been to Roth 's twice and both times were very disappointing ."], "output": "[[\"Roth 's\", '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": ["Both times I was extremely dissappointed by the service , which was boarderline rude ."], "output": "[['service', 'dissappointed', 'negative'], ['service', '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 dinner was ok , nothing I would have again ."], "output": "[['dinner', '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 had their eggs benedict for brunch , which were the worst in my entire life , I tried removing the hollondaise sauce completely that was how failed it was ."], "output": "[['eggs benedict', '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 service was attentive ."], "output": "[['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": ["Planet Thai is great !"], "output": "[['Planet Thai', '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 love the food , drinks , and atmosphere !"], "output": "[['food', 'love', 'positive'], ['drinks', 'love', 'positive'], ['atmosphere', '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 svc can be a bit rude at times , esp if you have big group , but overall the restaurant is a must !"], "output": "[['svc', 'rude', 'negative'], ['restaurant', '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": ["Try the Pad Thai , it 's fabulous and their prices are so cheap !"], "output": "[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'fabulous', 'positive'], ['Pad Thai', '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": ["Just because it 's cheap does NOT mean the portions are small or the food is nasty , IT IS GREAT !"], "output": "[['portions', 'small', 'positive'], ['food', 'nasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Eating in , the atmosphere saves it , but at your desk , it 's a very disappointing experience ."], "output": "[['atmosphere', 'saves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Chennai Garden is my favorite Indian restaurant in the city ."], "output": "[['Chennai Garden', '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": ["They have authentic Indian at amazin prices ."], "output": "[['Indian', '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": ["It 's a rather cramped and busy restaurant and it closes early ."], "output": "[['restaurant', 'cramped', 'negative'], ['restaurant', '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": ["Patroon features a nice cigar bar and has great staff ."], "output": "[['cigar bar', 'nice', '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": ["The food is tasty and portion sizes are appropriate ."], "output": "[['food', 'tasty', 'positive'], ['portion sizes', 'appropriate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 nice restaurant if you are looking for a good place to host an intimate dinner meeting with business associates ."], "output": "[['restaurant', '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": ["Not a great place for family or general dining ."], "output": "[['place', 'Not a great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ."], "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": ["Food is 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": ["Fish is so very fresh ."], "output": "[['Fish', '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": ["Love YUKA ."], "output": "[['YUKA', '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": ["Mermaid Inn is an overall good restaurant with really good seafood ."], "output": "[['seafood', 'good', 'positive'], ['Mermaid Inn', '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 menu is limited but almost all of the dishes are excellent ."], "output": "[['menu', 'limited', 'negative'], ['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": ["The lobster sandwich is good and the spaghetti with Scallops and Shrimp is great ."], "output": "[['lobster sandwich', 'good', 'positive'], ['spaghetti with Scallops and Shrimp', '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 good and ambience is good for a date or group outing ."], "output": "[['service', 'good', 'positive'], ['ambience', '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 only fallback on this restaurant is the prices ."], "output": "[['restaurant', 'fallback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 its good seafood , the prices are too high ."], "output": "[['seafood', '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": ["Truly the mark of an attentive waiter ."], "output": "[['waiter', '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": ["I highly recommend the restaurant based on our experience last night ."], "output": "[['restaurant', '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": ["We ate at this Thai place following the reviews but very unhappy with the foods ."], "output": "[['foods', 'unhappy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 jelly fish , drunken chicken and the soupy dumplings , certainly the stir fry blue crab ."], "output": "[['jelly fish', 'recommend', 'positive'], ['drunken chicken', 'recommend', 'positive'], ['soupy dumplings', 'recommend', 'positive'], ['stir fry blue crab', '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 so cheap and the waiters are nice ."], "output": "[['food', 'cheap', '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": ["Have frequented 'ino for several years and the food remains 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": ["Cheese plate is a varied delight and great bargain at $ 10 ."], "output": "[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["( The asparagus , truffle oil , parmesan bruschetta is a winner ! )"], "output": "[['asparagus , truffle oil , parmesan bruschetta', '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": ["Wine list is extensive without being over-priced ."], "output": "[['Wine list', 'extensive without being over-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": ["Be sure to try the seasonal , and always delicious , specials ."], "output": "[['specials', 'try', 'positive'], ['specials', 'seasonal', 'positive'], ['specials', '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 loved this place ! !"], "output": "[['place', '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 food was very good , a great deal , and the place its self was great ."], "output": "[['food', 'good', '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": ["The wait staff is very freindly , they make it feel like you 're eating in a freindly little european town ."], "output": "[['wait staff', 'freindly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Cafe Noir dont get me wrong , it is jsut that the people who work there are evil and incompetent ! !"], "output": "[['people', 'evil', 'negative'], ['people', 'incompetent', 'negative'], ['Cafe Noir', '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 service was terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ."], "output": "[['service', '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": ["The whole set up is truly unprofessional and I wish Cafe Noir would get some good staff , because despite the current one this is a great place ."], "output": "[['staff', 'good', 'negative'], ['Cafe Noir', '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": ["Pizza here is consistently good ."], "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": ["Salads are a delicious way to begin the meal ."], "output": "[['Salads', '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": ["You should pass on the calamari ."], "output": "[['calamari', 'pass', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 is charming ."], "output": "[['Decor', '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": ["What a great place ."], "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": ["I would definitely recommend SEA if you like thai cuisine !"], "output": "[['thai cuisine', '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 was here a few weeks back and we had the worst customer service experience at a restaurant ever ."], "output": "[['customer 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": ["I absolutely Loved this place ."], "output": "[['place', '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": ["Excellent atmosphere , delicious dishes good and friendly service ."], "output": "[['atmosphere', 'Excellent', 'positive'], ['dishes', 'delicious', 'positive'], ['service', 'good', '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 wine list is also really nice ."], "output": "[['wine list', '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": ["Everything was wonderful ; food , drinks , staff , mileau ."], "output": "[['food', 'wonderful', 'positive'], ['drinks', 'wonderful', 'positive'], ['staff', 'wonderful', 'positive'], ['mileau', '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 have been to Casimir over 5 times and I have always had a great time there ."], "output": "[['Casimir', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 reasonably priced ."], "output": "[['food', 'great', '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 staff has been nice , but they seemed really stressed and the unisex bathroom needs to be cleaned more often ."], "output": "[['staff', 'nice', 'positive'], ['staff', 'stressed', 'positive'], ['unisex bathroom', 'stressed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 spectacular caviar to the hospitable waitstaff , I felt like royalty and enjoyed every second of it ."], "output": "[['caviar', 'spectacular', 'positive'], ['caviar', 'enjoyed', 'positive'], ['waitstaff', 'hospitable', 'positive'], ['waitstaff', '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": ["Considering we were the last patrons there and it was after the closing time , the waitstaff did not rush us at all and made us feel comfortable and relaxed ."], "output": "[['waitstaff', 'comfortable', 'positive'], ['waitstaff', '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": ["I highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service ."], "output": "[['caviar', 'delicious top grade', '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": ["Friendly staff that actually lets you enjoy your meal and the company you 're with ."], "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": ["I found the food to be outstanding , particulary the salmon dish I had ."], "output": "[['food', 'outstanding', 'positive'], ['salmon dish', '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": ["I also ordered the Change Mojito , which was out of this world ."], "output": "[['Change Mojito', '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": ["We ate out in the back patio , which is worth it as it 's cool and the music is hear well there ."], "output": "[['back patio', 'worth', 'positive'], ['back patio', 'cool', 'positive'], ['music', '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": ["Overall , excellent restaurant !"], "output": "[['restaurant', '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 food was 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 place was nice and calm ."], "output": "[['place', 'nice', 'positive'], ['place', 'calm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 was a bit slow ."], "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 buffet had a nice selection ."], "output": "[['buffet', '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 average or above including some surprising tasty dishes ."], "output": "[['food', 'average or above', 'positive'], ['dishes', '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": ["Service was also 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": ["I got an excellent piece of cheesecake and we had several other nice pastries ."], "output": "[['cheesecake', 'excellent', 'positive'], ['pastries', '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": ["My son and his girlfriend both wanted cheeseburgers and they were huge !"], "output": "[['cheeseburgers', 'huge', '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": ["Consequently , their burgers fell apart in their hands and made such a mess that they did'nt feel like finishing them ."], "output": "[['burgers', 'fell apart', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really trendi but they have forgotten about the most important part of a restaurant , the food ."], "output": "[['food', 'forgotten', 'negative'], ['place', 'trendi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The last two times I ordered from here my food was soo spicy that I could barely eat it , and the spice took away from the flavor of the dish ."], "output": "[['food', '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": ["And the Tom Kha soup was pathetic ."], "output": "[['Tom Kha soup', 'pathetic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 authentic Thai this place is not the place to go ."], "output": "[['Thai', 'good authentic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The pesto pizza was excellent , thin-crust pizza with a nice amount of spicy Italian cheese that I 'd never heard of before ."], "output": "[['pesto pizza', 'excellent', 'positive'], ['spicy Italian cheese', '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 back garden sitting area is very pleasant , where you can see their personal herb garden ."], "output": "[['back garden sitting area', '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": ["We had the lobster sandwich and it was FANTASTIC ."], "output": "[['lobster sandwich', '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": ["My husband said he could 've eaten several more , the portion was fine for me he even exclaimed that the french fries were the best he has had ."], "output": "[['portion', 'fine', 'positive'], ['french fries', '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": ["We waited at the bar and had martinis that were just right ."], "output": "[['martinis', '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": ["love the food ."], "output": "[['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": ["it 's the only place you can get yummy authentic japanese comfort food ."], "output": "[['japanese comfort food', 'yummy 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": ["Great food , good size menu , great service and an unpretensious setting ."], "output": "[['food', 'Great', 'positive'], ['menu', 'good size', 'positive'], ['service', 'great', 'positive'], ['setting', 'unpretensious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The freshest , best variety , and the fastest delivery ."], "output": "[['delivery', '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": ["We are very particular about sushi and were both please with every choice which included : ceviche mix ( special ) , crab dumplings , assorted sashimi , sushi and rolls , two types of sake , and the banana tempura ."], "output": "[['sushi', 'particular', 'positive'], ['ceviche mix ( special )', 'please', 'positive'], ['crab dumplings', 'please', 'positive'], ['assorted sashimi', 'please', 'positive'], ['rolls', 'please', 'positive'], ['two types of sake', 'please', 'positive'], ['banana tempura', '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": ["Definitely a great spot for a nice occasion or date ."], "output": "[['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": ["Average to good Thai food , but terrible delivery ."], "output": "[['Thai food', 'Average to good', 'positive'], ['delivery', '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": ["This is a wonderful place on all stand points especially value ofr money ."], "output": "[['place', '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": ["An excellent service"], "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": ["We were greeted promptly by the waiter who was very nice and cordial ."], "output": "[['waiter', 'nice', 'positive'], ['waiter', 'cordial', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["She was very helpful in suggesting us drinks and helped us in ordering a lot of good dishes since we knew nothing about Indian food ."], "output": "[['dishes', '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 ended our great experience by having Gulab Jamun ( dessert ) recommended by the waiter ."], "output": "[['Gulab Jamun ( dessert )', '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 thanked my friend who recommended me this restaurant and will certainly recommend it to others ."], "output": "[['restaurant', '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": ["Service here was great , food was fantastic ."], "output": "[['Service', 'great', 'positive'], ['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": ["Guacamole+shrimp appetizer was really great , we both had the filet , very good , did n't much like the frites that came with , but the filet was so good , neither of us cared ."], "output": "[['Guacamole+shrimp appetizer', 'great', 'positive'], ['filet', '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 can not go wrong with this place ."], "output": "[['place', 'wrong', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 outstanding and the service is quick , friendly and very professional ."], "output": "[['food', 'outstanding', 'positive'], ['service', 'quick', 'positive'], ['service', 'friendly', 'positive'], ['service', '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": ["Always a nice crowd , but never loud ."], "output": "[['crowd', 'nice', 'positive'], ['crowd', 'never 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": ["I am reluctant to write because I would not want my jem of a pizza place to become overcrowded ."], "output": "[['pizza place', 'overcrowded', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 is thin , the ingredients are fresh and the staff is friendly ."], "output": "[['crust', 'thin', 'positive'], ['staff', 'friendly', '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": ["The fish was really , really fresh ."], "output": "[['fish', '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": ["We all agreed that mare is one of the best seafood restaurants in New York ."], "output": "[['mare', '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 stumbled upon this great pizzeria as I explored my new neighborhood ."], "output": "[['pizzeria', '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": ["All of the pizzas are terrific and the price is even better !"], "output": "[['pizzas', '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": ["I highly recommend the Sophia pizza ."], "output": "[['Sophia pizza', '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": ["For the people who want great food plus great service , Roxy is a place to AVOID !"], "output": "[['food', 'great', 'negative'], ['service', 'great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The first time the sushi was outstanding , the second time it was a little bland ."], "output": "[['sushi', 'outstanding', 'negative'], ['sushi', '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 blond wood decor is very soothing , the premium sake is excellent and the service is great ."], "output": "[['blond wood decor', 'soothing', 'positive'], ['premium sake', 'soothing', '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": ["Warning : You may find it difficult to dine at other Japanese restaurants after a visit to Mizu !"], "output": "[['Mizu', 'difficult', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Thalia is a beautiful restaurant with beautiful people serving you , but the food does n't quite match up ."], "output": "[['people', 'beautiful', 'positive'], ['food', \"does n't quite match up\", 'negative'], ['Thalia', '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": ["I ordered the smoked salmon and roe appetizer and it was off flavor ."], "output": "[['smoked salmon and roe appetizer', 'off flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 expected quite a bit more from such an expensive menu ."], "output": "[['menu', '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 view is spectacular , and the food is great ."], "output": "[['view', 'spectacular', '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": ["delicious simple food in nice outdoor atmosphere ."], "output": "[['food', 'delicious simple', 'positive'], ['outdoor 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": ["Kind , attentive wait staff ."], "output": "[['wait staff', 'Kind', 'positive'], ['wait staff', '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": ["I really like both the scallops and the mahi mahi ( on saffron risotto yum ! ) ."], "output": "[['scallops', 'like', 'positive'], ['mahi mahi ( on saffron risotto', '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": ["Delicious crab cakes too ."], "output": "[['crab cakes', '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": ["Even if the food was n't this good , the garden is a great place to sit outside and relax ."], "output": "[['garden', 'great', 'positive'], ['food', \"was n't this 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": ["Their calzones are horrific , bad , vomit-inducing , YUCK ."], "output": "[['calzones', 'horrific', 'negative'], ['calzones', 'bad', 'negative'], ['calzones', 'vomit-inducing', 'negative'], ['calzones', 'YUCK', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The counter service is bad ."], "output": "[['counter 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": ["The sandwiches are dry , tasteless and way overpriced ."], "output": "[['sandwiches', 'dry', 'negative'], ['sandwiches', 'tasteless', 'negative'], ['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": ["Calling the place Hampton Chutney Co. does warn you that these folks offer more style than substance , but in this unattractive room with unhelpful clerks there was a dearth of the former too ."], "output": "[['place', 'unattractive', 'negative'], ['room', 'unattractive', 'negative'], ['clerks', 'unhelpful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Seriously , this place kicks ass ."], "output": "[['place', 'kicks ass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 unheralded , the service impecible , and the food magnificant ."], "output": "[['atmosphere', 'unheralded', 'positive'], ['service', 'impecible', 'positive'], ['food', 'magnificant', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 such a lovely , peaceful place to eat outside ."], "output": "[['place', 'lovely', 'positive'], ['place', 'peaceful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 take out-of-towners , and perfect for watching the sunset ."], "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": ["Great sushi experience ."], "output": "[['sushi', '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": ["Unique apppetizers ."], "output": "[['apppetizers', '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": ["Try sushimi cucumber roll ."], "output": "[['sushimi cucumber 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": ["The service is awful ."], "output": "[['service', '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": ["This place is not worth the prices ."], "output": "[['place', 'not worth the prices', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Pizza 33 ..."], "output": "[['Pizza 33', '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 will be out with friends and all of a sudden I am hungry and I only crave one thing ... their Pizza ."], "output": "[['Pizza', 'crave', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tiny Williamsburg spot is always pleasantly surprising ."], "output": "[['Williamsburg spot', 'surprising', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 proprietor is one of the nicest in NYC ."], "output": "[['pizza', 'delicious', 'positive'], ['proprietor', '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": ["Bagels are ok , but be sure not to make any special requests !"], "output": "[['Bagels', '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 turkey burgers are scary !"], "output": "[['turkey burgers', 'scary', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 awful !"], "output": "[['sushi', '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 rice was poor quality and was cooked so badly it was hard ."], "output": "[['rice', 'poor quality', 'negative'], ['rice', 'cooked so badly', 'negative'], ['rice', 'hard', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , the rice had no seasoning , so the sushi was bland and disgusting ."], "output": "[['sushi', 'bland', 'negative'], ['sushi', '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": ["Good , fast service ."], "output": "[['service', 'Good', 'positive'], ['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": ["Food is great and inexpensive ."], "output": "[['Food', 'great', 'positive'], ['Food', '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 location is perfect ."], "output": "[['location', '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": ["If you like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you 'll love it here ."], "output": "[['bottle', 'love', 'negative'], ['music', '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": ["Great atmoshere and worth every bit ."], "output": "[['atmoshere', '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": ["Winnie and her staff are the best crew you can find serving you ."], "output": "[['staff', 'best', 'positive'], ['Winnie', '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 reliable and the price is moderate ."], "output": "[['food', '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": ["For authentic Thai food , look no further than Toons ."], "output": "[['Thai 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": ["Try the Pad Thai , or sample anything on the appetizer menu ... they 're all delicious ."], "output": "[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'delicious', 'positive'], ['appetizer 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 service was attentive , yet discreet ."], "output": "[['service', 'attentive', 'positive'], ['service', 'discreet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The brioche and lollies as party favors is a cute and sweet touch to a most memorable meal ."], "output": "[['brioche and lollies', 'cute', 'positive'], ['brioche and lollies', '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 place was quiet and delightful ."], "output": "[['place', 'quiet', 'positive'], ['place', '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": ["Service was good and food is wonderful ."], "output": "[['Service', 'good', '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 did not try the caviar but I tried their salmon and crab salad ( they are all good )"], "output": "[['salmon', 'good', 'positive'], ['crab salad', '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 is definitely a good spot for snacks and chat ."], "output": "[['spot', '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": ["As a retired hipster , I can say with some degree of certainty that for the last year Lucky Strike has been the best laid-back late night in the city ."], "output": "[['Lucky Strike', '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 wait staff is pleasant , fun , and for the most part gorgeous ( in the wonderful aesthetic beautification way , not in that she's-way-cuter-than-me-that-b @ # $ * way ) ."], "output": "[['wait staff', 'pleasant', 'positive'], ['wait staff', 'fun', 'positive'], ['wait staff', '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 food is yummy , especially their cooked-to-perfection mussels in spicy tomato sauce and their shoestring crispy fries ."], "output": "[['food', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'cooked-to-perfection', 'positive'], ['fries', 'yummy', 'positive'], ['fries', '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": ["But the best part about LS is the late night atmosphere , delightfully free of the BTs ."], "output": "[['late night atmosphere', '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": ["You can get a completely delish martini in a glass ( that 's about 2 1/2 drinks ) for $ 8.50 ( I recommend the Vanilla Shanty , mmmm ! ) in a great homey setting with great music ."], "output": "[['martini', 'delish', 'positive'], ['Vanilla Shanty', 'recommend', 'positive'], ['setting', 'homey', 'positive'], ['music', '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 in-house lady DJ on Saturday nights has outrageously good taste in music , and moreover , takes requests ."], "output": "[['in-house lady DJ', 'good taste', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Suan is a great place that I often take my friends ( classmates ) too ."], "output": "[['Suan', '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": ["Its location is good and the fact that Hutner College is near and their prices are very reasonable , makes students go back to Suan again and again ."], "output": "[['location', 'good', 'positive'], ['Suan', '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": ["I LOVE their Thai"], "output": "[['Thai', '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": ["noodles with shrimp and chicken and coconut juice is the MUST !"], "output": "[['noodles with shrimp and chicken and coconut juice', '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": ["In summer-eat outside on a terrace ( another great feature of Suan ) ! ! !"], "output": "[['terrace', '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 not imagine a friendlier staff working in a restaurant ."], "output": "[['staff', 'friendlier', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not imagine better Indian food in all of the city ."], "output": "[['Indian food', '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": ["During the course of the past 3 months , the chef and staff changed and it was not for the better ."], "output": "[['chef', 'changed', 'negative'], ['staff', 'changed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 now is inconsistent ."], "output": "[['food', 'inconsistent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 kind of place you 'd like to take all your friends to and still keep a secret ."], "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 setting is casual and romantic ."], "output": "[['setting', 'casual', 'positive'], ['setting', '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": ["if you 're daring , try the balsamic vinegar over icecream , it 's wonderful !"], "output": "[['balsamic vinegar over icecream', 'try', 'positive'], ['balsamic vinegar over icecream', '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 rest of the dim sum , though pricey by Chinatown standards , is worth it ."], "output": "[['dim sum', 'pricey', 'positive'], ['dim sum', '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 wait here is long for dim sum , but if you do n't like sharing tables or if the typical raucous dim sum atmosphere is not your gig , this is a sleek ( for Chinatown ) alternative ."], "output": "[['wait', 'long', 'negative'], ['atmosphere', 'sleek', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 few tips : skip the turnip cake , roast pork buns and egg custards ."], "output": "[['turnip cake', 'skip', 'negative'], ['roast pork buns', 'skip', 'negative'], ['egg custards', 'skip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 exceptional ."], "output": "[['food', '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": ["I choose to go with one of the special , the braised lamb shank in red wine , which was excellent ."], "output": "[['braised lamb shank in red wine', '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 service was friendly and the atmosphere was casual ."], "output": "[['service', 'friendly', 'positive'], ['atmosphere', 'casual', '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 pad se ew chicken was delicious , however the pad thai was far too oily ."], "output": "[['pad se ew chicken', 'delicious', 'positive'], ['pad thai', '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": ["Have eaten at Ginger House several times , and it 's always good ."], "output": "[['Ginger House', '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 fried dumplings are GREAT !"], "output": "[['fried dumplings', '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": ["Finally a reliable Chinese restaurant !"], "output": "[['Chinese restaurant', '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": ["Terrible , terrible management - deserves to be shut-down ."], "output": "[['management', 'Terrible', 'negative'], ['management', '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": ["Spreads and toppings are great - though a bit pricey ."], "output": "[['Spreads', 'great', 'negative'], ['Spreads', 'pricey', 'negative'], ['toppings', 'great', 'negative'], ['toppings', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 decent at best , and the ambience , well , it 's a matter of opinion , some may consider it to be a sweet thing , I thought it was just annoying ."], "output": "[['food', 'decent', 'negative'], ['ambience', '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": ["You must try the shrimp appetizers ."], "output": "[['shrimp appetizers', '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 the the correct ambience and an excellent staff to make you feel like a guest and a friend at the same time ."], "output": "[['ambience', 'correct', 'positive'], ['staff', '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": ["Great food , great prices , great service ."], "output": "[['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": ["If you are looking for a good quality , cheap eats - this is the place ."], "output": "[['eats', 'good quality', 'positive'], ['eats', '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 's a perfect place to have a amazing indian food ."], "output": "[['indian 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": ["also it 's great to have dinner in a very romantic and comfortable place , the service it 's just perfect ... they 're so frendly that we never want to live the place !"], "output": "[['place', 'romantic', 'positive'], ['place', 'comfortable', 'positive'], ['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": ["Their bagels are fine , but they are a little overcooked , and not really a 'special ' bagel experience ."], "output": "[['bagels', 'fine', 'negative'], ['bagels', 'overcooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bagels made the old-fashioned way ."], "output": "[['bagels', '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 absolutely amazing ! !"], "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": ["The baked clams octopus we shared as appetizers were the best we 've ever had ! !"], "output": "[['baked clams octopus', '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 lamb was tender so full of flavor , the dessert was divine ! !"], "output": "[['lamb', 'tender', 'positive'], ['dessert', '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": ["The waiter was attentive ."], "output": "[['waiter', '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 place itself is beautiful the bar scene seems to be happening ."], "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": ["Downtown Dinner 2002 - Prixe fix : Appetizers were ok , waiter gave me poor suggestion ... try the potato stuff kanish best one ."], "output": "[['Appetizers', 'ok', 'neutral'], ['waiter', 'poor', 'negative'], ['potato stuff kanish', 'try', 'positive'], ['potato stuff kanish', '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": ["Small servings for main entree , i had salmon ( wasnt impressed ) girlfriend had chicken , it was good ."], "output": "[['salmon', 'wasnt impressed', 'negative'], ['chicken', 'good', 'positive'], ['servings for main entree', '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": ["Dessert is a joke ... dont bother"], "output": "[['Dessert', 'joke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 has a Family feel , not least with regard to the portions which are enormous ; the veal alone could have single-handedly solved third world famine ."], "output": "[['restaurant', 'Family feel', 'positive'], ['portions', 'enormous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The anti-pasta was excellent , especially the calamari , as were the filling pasta mains ."], "output": "[['anti-pasta', 'excellent', 'positive'], ['calamari', 'excellent', 'positive'], ['pasta mains', '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 wine list is extensive and can easily hike up an otherwise reasonably priced meal ."], "output": "[['wine list', 'extensive', 'positive'], ['meal', '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": ["Still , any quibbles about the bill were off-set by the pour-your-own measures of liquers which were courtesey of the house ..."], "output": "[['measures of liquers', 'pour-your-own', 'positive'], ['measures of liquers', 'courtesey', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fantastic place ."], "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": ["Great food , great decor , great service ."], "output": "[['food', 'Great', 'positive'], ['decor', '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": ["This is the perfect spot for meeting friends , having lunch , dinner , pre-theatre or after-theatre drinks !"], "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": ["Excellent spot for holiday get togethers with co-workers or friends that you have n't seen in a while ."], "output": "[['spot', '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 been doing all of the above at the Heartland Brewery for over 5 years now and I HAVE NEVER BEEN DISAPPOINTED !"], "output": "[['Heartland Brewery', 'NEVER BEEN 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": ["Not the typical NYC gimmick theme restaurant ."], "output": "[['restaurant', 'Not the 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": ["A cool bar with great food , and tons of excellent beer ."], "output": "[['bar', 'cool', 'positive'], ['food', 'great', 'positive'], ['beer', '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 shrimp scampi was excellent and the antipasti were plentiful ."], "output": "[['shrimp scampi', 'excellent', 'positive'], ['antipasti', 'plentiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 more wonderful than the food ( which is exceptional ) is the service ."], "output": "[['food', 'exceptional', 'positive'], ['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": ["Cozy romantic atomosphere with only around 15 tables at most ."], "output": "[['atomosphere', 'Cozy 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": ["Service was very prompt but slightly rushed ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'rushed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good , but not what I would consider out of this world ."], "output": "[['Food', '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": ["Too bad the food was n't of the same heritage ."], "output": "[['food', '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 porcini mushroom pasta special was tasteless , so was the seafood tagliatelle ."], "output": "[['porcini mushroom pasta special', 'tasteless', 'negative'], ['seafood tagliatelle', '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": ["But that was n't the icing on the cake : a tiramisu that resembled nothing I have ever had ."], "output": "[['tiramisu', 'nothing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 liked this place ."], "output": "[['place', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 rice dishes or the different varieties of congee ( rice porridge ) ."], "output": "[['rice dishes', 'recommend', 'positive'], ['congee ( rice porridge )', '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": ["It 's definately not a place to go if you want to impress someone ."], "output": "[['place', 'impress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , if you want great food at a great price and do n't mind the decor , you ca n't beat this place ."], "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": ["When you 're sitting in their main dining room ( which has a spectacular , hand-painted high ceiling ) you 'd never know there was a world outside ."], "output": "[['main dining room', 'spectacular', 'positive'], ['ceiling', 'spectacular', 'positive'], ['ceiling', 'hand-painted 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": ["The food is wonderful , tasty and filling , and the service is professional and friendly ."], "output": "[['food', 'wonderful', 'positive'], ['food', 'tasty', 'positive'], ['food', 'filling', 'positive'], ['service', 'professional', '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 ca n't wait for summer , when they serve outside on their gigantic patio ."], "output": "[['patio', '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": ["I recently tried Suan and I thought that it was great ."], "output": "[['Suan', '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 fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals ."], "output": "[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['food', 'tasty', 'positive'], ['hot sauce', '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 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": ["Good drink ."], "output": "[['drink', '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 spot , whether looking for a couple of drinks or quiet dinner ."], "output": "[['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": ["Warm and friendly in the winter and terrific outdoor seating in the warmer months ."], "output": "[['outdoor seating', '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 food is great and they have a good selection of wines at reasonable prices ."], "output": "[['food', 'great', 'positive'], ['wines', 'good selection', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ambiance and atmosphere were great , the food and service could have been a lot better ."], "output": "[['ambiance', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['food', 'could have been a lot better', 'negative'], ['service', 'could have been a lot 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": ["i 've been to sapphire twice and both times the food was fine , if not good ."], "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": ["stick with the chicken , beef , and lamb dishes ."], "output": "[['chicken', 'stick', 'positive'], ['beef', 'stick', 'positive'], ['lamb dishes', 'stick', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 friendly , and never had a problem walking in and getting a table ."], "output": "[['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": ["skip dessert ."], "output": "[['dessert', 'skip', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Reuben sandwich ever !"], "output": "[['Reuben sandwich', '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": ["Do n't miss Bloom 's on your next trip to Manhatten ."], "output": "[[\"Bloom 's\", '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": ["Thanks Bloom 's for a lovely trip ."], "output": "[[\"Bloom 's\", 'Thanks', 'positive'], [\"Bloom 's\", '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 was not fresh , the sauces were bland and very oily ."], "output": "[['food', 'not fresh', 'negative'], ['sauces', 'bland', 'negative'], ['sauces', '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": ["Pizza was a little soggy ."], "output": "[['Pizza', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ravioli was good ... but I have to say that I found everything a bit overpriced ."], "output": "[['Ravioli', 'good', 'positive'], ['Ravioli', 'overpriced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 enough wines by the glass either ."], "output": "[['wines by the glass', 'Not enough', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 just average ... if they lowered the prices just a bit , it would be a bigger draw ."], "output": "[['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": ["This place is a great bargain ."], "output": "[['place', 'great bargain', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Authentic Pakistani food ."], "output": "[['Pakistani 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": ["Just straight up cheap , good food ."], "output": "[['food', 'cheap', '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": ["Faan is sooo good ."], "output": "[['Faan', '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 best pad thai i 've ever had ."], "output": "[['pad thai', '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 design and atmosphere is just as good ."], "output": "[['design', '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": ["The mussles were the fishiest things I 've ever tasted , the seabass was bland , the goat cheese salad was missing the goat cheese , the penne w/ chicken had bones in it ... It was disgusting ."], "output": "[['mussles', 'fishiest', 'negative'], ['seabass', 'bland', 'negative'], ['goat cheese salad', 'missing', 'negative'], ['penne w/ chicken', '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": ["Nice atmosphere , the service was very pleasant and the desert was good ."], "output": "[['atmosphere', 'Nice', 'positive'], ['service', 'pleasant', 'positive'], ['desert', '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 is amazing , rich pastas and fresh doughy pizza ."], "output": "[['food', 'amazing', 'positive'], ['pastas', 'rich', 'positive'], ['pizza', 'fresh doughy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 of all is the warm vibe , the owner is super friendly and service is fast ."], "output": "[['vibe', 'warm', 'positive'], ['owner', 'friendly', 'positive'], ['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": ["Ask for Usha , the nicest bartender in manhattan ."], "output": "[['Usha', '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": ["My fav was the sassy lassi ..."], "output": "[['sassy lassi', 'fav', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Toons has recently been redone , so it 's now a very attractive space ."], "output": "[['Toons', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 's as good as ever ."], "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": ["In an area sadly lacking in decent Thai food , this is one of the best spots ."], "output": "[['Thai 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": ["Went here last night - nice decor , good service , but the food was surprisingly excellent ."], "output": "[['decor', 'nice', 'positive'], ['service', 'good', '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": ["The portions are HUGE , so it might be good to order three things to split ( rather than one appetizer and entree per person ) for two people ."], "output": "[['portions', 'HUGE', '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 good and the resturant is clean ."], "output": "[['service', 'good', 'positive'], ['resturant', '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": ["Rao 's has the best service and atmosphere in NYC ."], "output": "[['service', 'best', 'positive'], ['atmosphere', '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": ["My roommate and 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": ["We recently decided to try this location , and to our delight , they have outdoor seating , perfect since I had my yorkie with me ."], "output": "[['outdoor seating', '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": ["Indoor was very cozy and cute ."], "output": "[['Indoor', 'cozy', 'positive'], ['Indoor', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The portion sizes here are huge , and the sushi is good ."], "output": "[['portion sizes', 'huge', 'positive'], ['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": ["Excellent dumplings served amid clean , chic decor ."], "output": "[['dumplings', 'Excellent', 'positive'], ['decor', 'clean', 'positive'], ['decor', 'chic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 but do not come here on a empty stomach ."], "output": "[['food', '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 portions are small but being that the food was so good makes up for that ."], "output": "[['portions', 'small', 'negative'], ['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 staff there is very attentive and down to earth ."], "output": "[['staff', 'attentive', 'positive'], ['staff', 'down to earth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 and the service is incredible ."], "output": "[['Indian food', 'Great', 'positive'], ['service', '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": ["Great food and the prices are very reasonable ."], "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 here does a great service to the name ( Cantonese that is ... ) ."], "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 fell in love with the egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork ."], "output": "[['egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork', '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": ["This dish is my favorite and I always get it when I go there and never get tired of it ."], "output": "[['dish', '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": ["Try the congee and the donut like deep fried dough they call Ow Ley Soh , a delicious and sweet tasting bread ."], "output": "[['Ow Ley Soh', 'delicious', 'positive'], ['Ow Ley Soh', '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": ["Simply some good tasting Chinese food at incredible prices ..."], "output": "[['Chinese food', 'good tasting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Wong is a great place to eat and fill your stomach ."], "output": "[['Big Wong', '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 music , great food , speedy service affordable prices ."], "output": "[['music', 'good', 'positive'], ['food', 'great', 'positive'], ['service', 'speedy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Consistently good Japanese Tapas ."], "output": "[['Japanese Tapas', '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": ["Always good drinks and service is pretty good ;"], "output": "[['drinks', 'good', '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": ["Atmosphere is nice and relaxed too ..."], "output": "[['Atmosphere', 'nice', 'positive'], ['Atmosphere', '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": ["A great place to meet up for some food and drinks ..."], "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": ["Yakitori ( bbq meats ) is tasty too ."], "output": "[['Yakitori ( bbq meats )', '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": ["If you do n't mind pre-sliced low quality fish , unfriendly staff and a sushi chef that looks like he is miserable then this is your place ."], "output": "[['fish', 'low quality', 'negative'], ['staff', 'unfriendly', 'negative'], ['sushi chef', '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": ["Fabulous decor - makes you feel like you 're in a trendy Manhattan restaurant , very very good food , cheaply-priced , generally friendly staff , and if you 're a Manhattanite , or spend most of your time in Manhattan , Rice Avenue will make you feel at home ... ..very Soho/Village/Upper West Side minus the expensive prices and pretentious clientele ... ..all on Roosevelt Avenue !"], "output": "[['decor', 'Fabulous', 'positive'], ['food', 'good', 'positive'], ['food', 'cheaply-priced', '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": ["One would think we 'd get an apology or complimentary drinks - instead , we got a snobby waiter would n't even take our order for 15 minutes and gave us lip when we asked him to do so ."], "output": "[['waiter', 'snobby', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 so many good restaurants on the UWS , I do n't need overpriced food , absurdly arrogant wait-staff who do n't recognize they work at a glorified diner , clumsy service , and management that does n't care ."], "output": "[['food', 'overpriced', 'negative'], ['wait-staff', 'arrogant', 'negative'], ['service', 'clumsy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 relatively new to the area and tried Pick a bgel on 2nd and was disappointed with the service and I thought the food was overated and on the pricey side ."], "output": "[['service', 'disappointed', 'negative'], ['food', 'overated', 'negative'], ['food', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 problem is that the manager is a complete incompetent ."], "output": "[['manager', 'incompetent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["He offers subpar service and has no personality ."], "output": "[['service', 'subpar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 excuse for such lousy service !"], "output": "[['service', '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": ["I have never before eaten 40 pieces of relatively good nigiri ."], "output": "[['nigiri', '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": ["I went to Areo on a Sunday afternoon with four of my girlfriends , and spent three enjoyable hours there ."], "output": "[['Areo', '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": ["Most of the servers are very attentive , friendly and quite attractive ."], "output": "[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive'], ['servers', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went ."], "output": "[['Food', 'good', 'positive'], ['view of the new york city skiline', '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": ["I would highly recommand requesting a table by the window ."], "output": "[['table by the window', 'recommand', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 they do the typical what kind of water would you like questions the service was good and overall very relaxing to place to eat ."], "output": "[['service', 'good', '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 food is 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": ["Personal pans are the perfect size for those hungry nights ."], "output": "[['Personal pans', '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": ["There is a downside if you 're ordering in -- the delivery guys have MAJOR attitude ."], "output": "[['delivery guys', 'downside', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 scene first off- the place has a character and nice light to it..very fortunate , location wise ."], "output": "[['scene', 'Love', 'positive'], ['place', 'nice', 'positive'], ['location', 'fortunate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 was pretty good and huge ."], "output": "[['pizza', 'good', 'positive'], ['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": ["We were 4 and got the family size penne a la vodka which was tremendously gigantic portion ... a bucket of food literally ."], "output": "[['penne a la vodka', '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 pasta penne was pretty extra buttery , creamy which means a big task to diggest.. tasty at first but i would say that i was full with a slice of pizza and 7 to count , penne ... got a little moody afterwards cause was stuffed ... lol"], "output": "[['pasta penne', 'buttery', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["La Rosa waltzes in , and I think they are doing it the best ."], "output": "[['La Rosa', '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": ["Interesting selection , good wines , service fine , fun decor ."], "output": "[['wines', 'good', 'positive'], ['service', 'fine', 'positive'], ['decor', 'fun', 'positive'], ['selection', 'Interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it on a cold night , the perfect spot to warm up ."], "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": ["I recieved prompt service with a smile ."], "output": "[['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": ["This place blew me away ... by far my new favorite restaurant on the uppereast side ."], "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": ["The wine list is extensive and impressive ."], "output": "[['wine list', 'extensive', 'positive'], ['wine list', '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": ["LOVE the atmosphere - felt like I was in Paris ."], "output": "[['atmosphere', '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 mussels were fantastic and so was the dessert ... definitely going to be back very soon ."], "output": "[['mussels', 'fantastic', 'positive'], ['dessert', '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 have been coming here for years and have nothing but good things to say about the service and the great staff at La Lanterna ."], "output": "[['service', 'good', '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": ["Over the years the host , Vittorio , and his crew , have always treated me as family -- although with all the business this not-so-little gem does , it amazing he 's even able to remember a consistent but not-so-frequent visitor ."], "output": "[['host', '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 've also been amazed at all the new additions in the past few years : A new Jazz Bar , the most fantastic Dining Garden , the Best Thin Crust Pizzas , and now a Lasagna Menu which is to die for ( these are not your average lasagnas ) !"], "output": "[['Dining Garden', 'fantastic', 'positive'], ['Jazz Bar', 'new', 'positive'], ['Thin Crust Pizzas', 'Best', 'positive'], ['Lasagna Menu', '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": ["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": ["I have to say I have never had a disapointing meal here ."], "output": "[['meal', 'never had a disapointing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 could have made a meal of the yummy dumplings from the dumpling menu ."], "output": "[['dumplings', '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": ["Luckily we saved room for the BBQ Salmon , Sea Bass and Crispy Duck ."], "output": "[['BBQ Salmon', 'Luckily', 'positive'], ['Sea Bass', 'Luckily', 'positive'], ['Crispy Duck', 'Luckily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Judging from previous posts this used to be a good place , but not any longer ."], "output": "[['place', '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": ["We , there were four of us , arrived at noon - the place was empty - and the staff acted like we were imposing on them and they were very rude ."], "output": "[['staff', '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 food was lousy - too sweet or too salty and the portions tiny ."], "output": "[['food', 'lousy', 'negative'], ['food', 'too sweet', 'negative'], ['food', 'too salty', 'negative'], ['portions', '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": ["Avoid this 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": ["I have eaten at Saul , many times , the food is always consistently , outrageously 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": ["Saul is the best restaurant on Smith Street and in Brooklyn ."], "output": "[['Saul', '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 duck confit is always amazing and the foie gras terrine with figs was out of this world ."], "output": "[['foie gras terrine with figs', 'out of this world', 'positive'], ['duck confit', '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 interesting and has many good values ."], "output": "[['wine list', 'interesting', 'positive'], ['wine list', 'good values', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very disappointed with this restaurant ."], "output": "[['restaurant', '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": ["Food was okay , nothing great ."], "output": "[['Food', 'okay', 'neutral'], ['Food', 'nothing 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": ["Chow fun was dry ; pork shu mai was more than usually greasy and had to share a table with loud and rude family ."], "output": "[['Chow fun', 'dry', 'negative'], ['pork shu mai', '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": ["I/we will never go back to this place again ."], "output": "[['place', 'never go back', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 devine , oysters where a sensual as they come , and the price ca n't be beat ! ! !"], "output": "[['Service', 'devine', 'positive'], ['oysters', 'sensual', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always cooked to perfection , the service is excellent , the decor cool and understated ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 duck breast special on my last visit and it was incredible ."], "output": "[['duck breast special', '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 only thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree ."], "output": "[['Grilled Chicken special with Edamame Puree', '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 never had Edamame pureed before but I thought it was innovative and tasty ( could 've used a bit more salt ) ."], "output": "[['Edamame pureed', 'innovative', 'positive'], ['Edamame pureed', '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 decor is night tho ... but they REALLY need to clean that vent in the ceiling ... its quite un-appetizing , and kills your effort to make this place look sleek and modern ."], "output": "[['place', 'sleek', 'negative'], ['place', 'modern', 'negative'], ['decor', 'night', 'positive'], ['vent', 'un-appetizing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 sake list was extensive , but we were looking for Purple Haze , which was n't listed but made for us upon request !"], "output": "[['sake 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": ["The spicy tuna roll was unusually good and the rock shrimp tempura was awesome , great appetizer to share !"], "output": "[['spicy tuna roll', 'good', 'positive'], ['rock shrimp tempura', '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 perfect spot ."], "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": ["Food awesome ."], "output": "[['Food', '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": ["Service friendly and attentive ."], "output": "[['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": ["Ambiance relaxed and stylish ."], "output": "[['Ambiance', 'relaxed', 'positive'], ['Ambiance', 'stylish', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got to be the best japanese restaurant in the new york area ."], "output": "[['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": ["Food is 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": ["Service is top notch ."], "output": "[['Service', '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": ["The rice to fish ration was also good -- they did n't try to overpack the rice ."], "output": "[['rice to fish ration', '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 took advanatage of the half price sushi deal on saturday so it was well worth it ."], "output": "[['half price sushi deal', '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": ["$ 6 and there is much tasty food , all of it fresh and continually refilled ."], "output": "[['food', 'tasty', 'positive'], ['food', 'fresh', 'positive'], ['food', 'refilled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 not a vegetarian but , almost all the dishes were great ."], "output": "[['dishes', '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 is rather good , but only if you like to wait for it ."], "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": ["I like the somosas , chai , and the chole , but the dhosas and dhal were kinda disappointing ."], "output": "[['somosas', 'like', 'positive'], ['chai', 'like', 'positive'], ['chole', 'like', 'positive'], ['dhosas', 'disappointing', 'negative'], ['dhal', '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": ["The service varys from day to day- sometimes they 're very nice , and sometimes not ."], "output": "[['service', 'varys', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , specify if you like your food spicy- its rather bland if you do n't ."], "output": "[['food', '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 ambience is pretty and nice for conversation , so a casual lunch here would probably be best ."], "output": "[['ambience', 'pretty', '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": ["The lava cake dessert was incredible and I recommend it ."], "output": "[['lava cake dessert', 'incredible', 'positive'], ['lava cake dessert', '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": ["Once you step into Cosette , you 're miraculously in a small , off-the-beaten path Parisian bistro ."], "output": "[['Cosette', 'off-the-beaten', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tiny restaurant is as cozy as it gets , with that certain Parisian flair ."], "output": "[['restaurant', 'tiny', 'positive'], ['restaurant', '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 food was average to above-average ; the French Onion soup filling yet not overly impressive , and the desserts not brilliant in any way ."], "output": "[['food', 'average to above-average', 'positive'], ['French Onion soup', 'not overly impressive', 'positive'], ['desserts', 'not brilliant', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 overpriced and soggy ."], "output": "[['pizza', 'overpriced', 'negative'], ['pizza', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 I 've had some the best meals of my life at minnow ."], "output": "[['meals', '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 seafood is amazing , there 's a good wine list , and the ever-changing menu always offers some great surprises ."], "output": "[['seafood', 'amazing', 'positive'], ['wine list', 'good', 'positive'], ['menu', 'ever-changing', 'positive'], ['menu', 'great 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": ["The combination of super-fresh ingredients in the dishes are unusual but really delicious ."], "output": "[['ingredients', 'super-fresh', 'positive'], ['ingredients', '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": ["As a Japanese native , I 've lived in the Tristate area for over 8 years , but I was just so amazed at this place ."], "output": "[['place', '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": ["The signs , the specials menus , food , and even all the waitstaff are ALL TOTALLY Japanese ."], "output": "[['signs', 'Japanese', 'positive'], ['specials menus', 'Japanese', 'positive'], ['food', 'Japanese', 'positive'], ['waitstaff', 'Japanese', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 worth an one-hour drive ."], "output": "[['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": ["My wife and I always enjoy the young , not always well trained but nevertheless friendly , staff , all of whom have a story ."], "output": "[['staff', 'enjoy', 'positive'], ['staff', 'young', 'positive'], ['staff', 'not always well trained', '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": ["Decent wine at reasonable prices ."], "output": "[['wine', '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": ["This is by far my favorite place in the neighborhood ."], "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": ["The service is excellent , the decor is great , and the food is delicious and comes in large portions ."], "output": "[['service', 'excellent', 'positive'], ['decor', 'great', 'positive'], ['food', 'delicious', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 partial to the Gnocchi ."], "output": "[['Gnocchi', 'partial', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 incredibly 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": ["The hostess is rude to the point of being offensive ."], "output": "[['hostess', 'rude', 'negative'], ['hostess', '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": ["We have been to this place many times , and always have great food , wine , and service ."], "output": "[['food', 'great', 'positive'], ['wine', '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": ["We were worried we would have trouble getting in , but somehow managed to have a short wait ."], "output": "[['wait', 'short', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 always we had a great glass of wine while we waited ."], "output": "[['glass 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": ["When we sat , we got great and fast service ."], "output": "[['service', 'great', 'positive'], ['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": ["The people that work there are always so friendly you forget you are in New York sometimes ."], "output": "[['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": ["Make sure you try this place as often as you can ."], "output": "[['place', '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 is a fun restaurant to go to ."], "output": "[['restaurant', '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": ["The pizza is yummy and I like the atmoshpere ."], "output": "[['pizza', 'yummy', 'positive'], ['atmoshpere', '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": ["But the pizza is way to expensive ."], "output": "[['pizza', '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": ["Sauce was watery and the food did n't have much flavor ."], "output": "[['Sauce', 'watery', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 very patient with us and the food is phenomenal !"], "output": "[['waitress', 'patient', 'positive'], ['food', '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": ["Service was prompt , friendly and great ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'friendly', '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": ["There was a small wait , but shorter than I expected ."], "output": "[['wait', 'small', 'positive'], ['wait', 'shorter', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 best sushi in new york city - hands down ."], "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": ["Planet Thailand has always been a hit with me , I go there usually for the sushi , which is great , the thai food is excellent too ."], "output": "[['sushi', 'great', 'positive'], ['thai food', 'excellent', 'positive'], ['Planet Thailand', '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": ["With the great variety on the menu , I eat here often and never get bored ."], "output": "[['menu', 'great 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": ["The atmosphere is n't the greatest , but I suppose that 's how they keep the prices down ."], "output": "[['atmosphere', \"is n't 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": ["those rolls were big , but not good and sashimi was n't fresh ."], "output": "[['rolls', 'big', 'negative'], ['rolls', 'not good', 'negative'], ['sashimi', \"was n't 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": ["Try the crunchy tuna , it is to die for ."], "output": "[['crunchy tuna', 'Try', 'positive'], ['crunchy tuna', '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": ["First went here to enjoy their garden terrace ."], "output": "[['garden terrace', '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 food was amazing , and the service was prompt and helpful , but not over-bearing or rushed ."], "output": "[['food', 'amazing', 'positive'], ['service', 'prompt', 'positive'], ['service', 'helpful', 'positive'], ['service', 'not over-bearing or rushed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 Tartare is a great bet , they fix it for you at the table ."], "output": "[['Steak Tartare', '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": ["Admittedly some nights inside the restaurant were rather warm , but the open kitchen is part of the charm ."], "output": "[['open kitchen', 'charm', 'positive'], ['restaurant', '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": ["Great wine selection , Gigondas is worth the price , and the house champagne is a great value ."], "output": "[['wine selection', 'Great', 'positive'], ['Gigondas', 'worth the price', 'positive'], ['house champagne', 'great value', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 may be a bit packed on weekends , but the vibe is good and it is the best French food you will find in the area ."], "output": "[['vibe', 'good', 'positive'], ['French 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": ["Have recommended the place to friends , always gets good response ."], "output": "[['place', '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": ["Pizza - the only pizza in NYC that should not have additional toppings - the crust tastes like the best , freshly baked bread !"], "output": "[['crust', '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": ["Not sure where the previous reviewer , lonk , dined , but Saul is in a great neighborhood and has great food !"], "output": "[['neighborhood', '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": ["I 'd highly recommend it for a special occasion -- it provides and intimate setting and nice service ."], "output": "[['setting', 'intimate', 'positive'], ['service', '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 'm not sure where the other reviewers ate but it seems as if we visited two different restaurants because my friends and I all enjoy Mizu very much ... and we 're repeat customers ."], "output": "[['Mizu', '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": ["Took my mom for Mother 's Day , and the maitre d ' was pretty rude ."], "output": "[[\"maitre d '\", '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": ["Tiny dessert was $ 8.00 ... just plain overpriced for what it is ."], "output": "[['dessert', 'Tiny', 'negative'], ['dessert', '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": ["The drinks are always well made and wine selection is fairly priced ."], "output": "[['drinks', 'well made', 'positive'], ['wine selection', '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": ["Try their chef 's specials -- they are to die for ."], "output": "[[\"chef 's specials\", 'Try', 'positive'], [\"chef 's specials\", '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": ["Raga 's is a romantic , cozy restaurant ."], "output": "[[\"Raga 's\", 'romantic', 'positive'], [\"Raga 's\", '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 exotic food is beautifully presented and is a delight in delicious combinations ."], "output": "[['exotic food', 'beautifully presented', 'positive'], ['exotic food', '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": ["The bar is very well stocked with interesting beers and well priced wines ."], "output": "[['bar', 'well stocked', 'positive'], ['beers', 'interesting', 'positive'], ['wines', 'well 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": ["I loved everythig about it-especially the shows and actors ."], "output": "[['shows', 'loved', 'positive'], ['actors', '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": ["Our server was very helpful and friendly ."], "output": "[['server', 'helpful', '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 outdoor atmosphere of sitting on the sidewalk watching the world go by 50 feet away on 6th avenue on a cool evening was wonderful ."], "output": "[['outdoor atmosphere', '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": ["Service was prompt and courteous ."], "output": "[['Service', 'prompt', 'positive'], ['Service', 'courteous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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', 'complaints', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Wait staff is blantently unappreciative of your business but its the best pie on the UWS !"], "output": "[['Wait staff', 'unappreciative', 'negative'], ['pie', '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": ["By far the best salad I have had in a fast food restaurant ."], "output": "[['salad', '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": ["fine dining restaurant quality ."], "output": "[['dining', '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": ["On a recent Sunday afternoon , a friend and I accidently found this great restaurant on our way to see the pulitzer prize winning play DOUBT ."], "output": "[['restaurant', '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 chicken pot pie is exceptional , the cheeseburger huge and delictable , and the service professional wan warm ."], "output": "[['chicken pot pie', 'exceptional', 'positive'], ['cheeseburger', 'huge', 'positive'], ['cheeseburger', 'delictable', 'positive'], ['service', 'professional', 'positive'], ['service', 'warm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 no nonsense ."], "output": "[['staff', 'no nonsense', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 lived upstate for a while I would buy freeze the bagels and they would still be better than any else ."], "output": "[['bagels', '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": ["Worth visiting the 1st Ave spot because it is the original store ."], "output": "[['1st Ave spot', 'Worth visiting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sake menu should not be overlooked !"], "output": "[['sake menu', 'overlooked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good - prompt , attentive and non-intrusive ."], "output": "[['Service', 'good', 'positive'], ['Service', 'prompt', 'positive'], ['Service', 'attentive', 'positive'], ['Service', 'non-intrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 very good as well , considering that we tried the budget selection ( though I wish the pork belly that I ordered was roasted a bit longer , so that fat was more of a melt-in-your-mouth experience ) ."], "output": "[['Food', '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": ["Wine list selection is good and wine-by-the-glass was generously filled to the top ."], "output": "[['Wine list selection', 'good', 'positive'], ['wine-by-the-glass', 'generously filled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Traditional French decour was pleasant though the hall was rather noisy - the restaurant was full and we had to raise our voices to be able to maintain a conversation ."], "output": "[['Traditional French decour', 'pleasant', 'positive'], ['hall', 'noisy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 been to at Cafe Spice probably 5-8 times , it is probably still the best Indian restaurant around Union Square ."], "output": "[['Cafe Spice', '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": ["To sum it up : Service varies from good to mediorce , depending on which waiter you get ; generally it is just average Ok ."], "output": "[['Service', 'varies', '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": ["Seating is always prompt , though the restaurant does fill up in the evening ."], "output": "[['Seating', '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": ["Food is usually very good , though ocasionally I wondered about freshmess of raw vegatables in side orders ."], "output": "[['Food', 'good', 'positive'], ['raw vegatables in side orders', 'wondered about freshmess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 vibrant and eye-pleasing with several semi-private boths on the right side of the dining hall , which are great for a date ."], "output": "[['decor', 'vibrant', 'positive'], ['decor', 'eye-pleasing', 'positive'], ['semi-private boths', 'eye-pleasing', 'positive'], ['semi-private boths', '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 NEVER been disappointed in the Red Eye ."], "output": "[['Red Eye', 'NEVER been 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 first time I went , and was completely taken by the live jazz band and atmosphere , I ordered the Lobster Cobb Salad ."], "output": "[['live jazz band', 'taken', 'positive'], ['atmosphere', 'taken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 simply the best meal in NYC ."], "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": ["If we were to move from the upper east side , we would genuinely miss this restaurant ."], "output": "[['restaurant', '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": ["The restaurant is cute but not upscale ."], "output": "[['restaurant', 'cute', 'neutral'], ['restaurant', 'not 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": ["The food is a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes ."], "output": "[['food', 'diamond', 'positive'], ['balance of herbs and tomatoes', '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 had a great time at the Jekyll and hyde Pub last night ."], "output": "[['Jekyll and hyde Pub', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 really enjoying ourselves at the bar we sat down at a table and had dinner ."], "output": "[['bar', 'enjoying', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The server was really cool and served us our food and drinks with a smile ."], "output": "[['server', '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 place 's decor and hidden bathrooms made for a good laugh ."], "output": "[['decor', 'good laugh', 'positive'], ['hidden bathrooms', 'good laugh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 visiting this restaurant and having dinner and drinks !"], "output": "[['restaurant', '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": ["If you are the type of person who likes being scared and entertained , this is a great place to go and eat ."], "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 have over 100 different beers to offer thier guest so that made my husband very happy and the food was delicious , if I must recommend a dish it must be the pumkin tortelini ."], "output": "[['beers', 'happy', 'positive'], ['food', 'delicious', 'positive'], ['pumkin tortelini', '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 bagel was huge ."], "output": "[['bagel', '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": ["The workers there also absolutely load the bagel with cream cheese ( gets a little messy ) ."], "output": "[['bagel', 'messy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 guests enjoyed pizza , santa fe chopped salad and fish and chips ."], "output": "[['pizza', 'enjoyed', 'positive'], ['santa fe chopped salad', 'enjoyed', 'positive'], ['fish and chips', '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 highly recommend Cafe St. Bart 's for their food , the ambience and wonderful service ."], "output": "[['food', 'recommend', 'positive'], ['ambience', 'recommend', 'positive'], ['service', 'recommend', 'positive'], ['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": ["My chow fun and chow see was really bland and oily ."], "output": "[['chow fun and chow see', 'bland', 'negative'], ['chow fun and chow see', '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": ["The scallion pancakes and fried dumplings were nothing out of the ordinary ."], "output": "[['scallion pancakes', 'ordinary', 'neutral'], ['fried dumplings', 'ordinary', '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 the only thing good about this restaurant ."], "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": ["fresh restaurant was amazing ... ... .. food was delicious and of course fresh ."], "output": "[['fresh restaurant', 'fresh', 'positive'], ['fresh restaurant', 'amazing', 'positive'], ['food', 'delicious', 'positive'], ['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": ["Hats off to the chef ."], "output": "[['chef', 'Hats off', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the salads are delicious , both refreshing and very spicy ."], "output": "[['salads', 'delicious', 'positive'], ['salads', 'refreshing', 'positive'], ['salads', 'spicy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Pam 's special fried fish and it was amazing ."], "output": "[[\"Pam 's special fried fish\", '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": ["Great vibe , lots of people ."], "output": "[['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": ["I did n't complain , I liked the atmosphere so much ."], "output": "[['atmosphere', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ambience is so cute and quaint , good for business although we were there on vacation ."], "output": "[['Ambience', 'cute', 'positive'], ['Ambience', 'quaint', 'positive'], ['Ambience', '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": ["Salads were fantastic ."], "output": "[['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": ["Although we were looking for regular lettuce and some walnuts the salads we got were great ."], "output": "[['salads', '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": ["Ingredients are organic which is a real plus for me ."], "output": "[['Ingredients', 'organic', 'positive'], ['Ingredients', 'plus', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 some really good , inexpensive sushi ."], "output": "[['sushi', 'good', 'positive'], ['sushi', '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 Yellowtail was particularly good as well ."], "output": "[['Yellowtail', '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 reservations about the all you can eat deal , however -- the choices are fairly limited and you can probably order more food than you can eat for less than $ 18 by just going off the menu ."], "output": "[['all you can eat deal', '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": ["Big Wong gets big Ups for a fine establishment ."], "output": "[['Big Wong', 'big Ups', 'positive'], ['Big Wong', '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": ["They have it all -- great price , food , and service ."], "output": "[['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": ["The atmosphere is noisy and the waiters are literally walking around doing things as fast as they can ."], "output": "[['atmosphere', 'noisy', 'negative'], ['waiters', '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 takeout is great too since they give high quality tupperware as well ."], "output": "[['takeout', '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 is always very crowded and popular ."], "output": "[['place', 'crowded', 'positive'], ['place', 'popular', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a very nice Caesar Salad while my wife had arugula and goat cheese ... .both very tasty ."], "output": "[['Caesar Salad', 'Enjoyed', 'positive'], ['Caesar Salad', 'nice', 'positive'], ['arugula and goat cheese', '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": ["We both opted for a pasta dish and they were served timely and fresh ."], "output": "[['pasta dish', 'served timely', 'positive'], ['pasta dish', '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": ["I recently went to this restaurant with some co-workers for lunch and had an amazing time ."], "output": "[['restaurant', 'amazing time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["sometimes i get good food and ok service ."], "output": "[['food', 'good', 'positive'], ['service', '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": ["sometimes i get bad food and bad service , sometimes i get good good and bad service ."], "output": "[['food', 'bad', 'negative'], ['service', 'bad', 'negative'], ['good', '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 is a BISTRO which means : simple dishes and wine served efficiently in a bustling atmosphere ."], "output": "[['dishes', 'simple', 'positive'], ['wine', 'served efficiently', 'positive'], ['atmosphere', 'bustling', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 evaluated on those terms Pastis is simply wonderful ."], "output": "[['Pastis', '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": ["Right off the L in Brooklyn this is a nice cozy place with good pizza ."], "output": "[['pizza', 'good', 'positive'], ['place', 'nice 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": ["Mine was a little burnt but still delicious with goat cheese and panchetta ( raddichio was kind of bitter though ) ."], "output": "[['raddichio', 'bitter', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 got the mushroom pizza which tasted better ."], "output": "[['mushroom pizza', '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 sangria was pretty tasty and good on a hot muggy day ."], "output": "[['sangria', 'tasty', '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": ["Kind of a small place but I guess if they are not too busy might be able to fit a group or kids ."], "output": "[['place', 'small', '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 started out with a Bombay beer which was big enough for two ."], "output": "[['Bombay beer', 'big', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 slow , but the people were friendly ."], "output": "[['Service', 'slow', 'negative'], ['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": ["It 's a nice place to relax and have conversation ."], "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": ["Pizza is terrific , as is homemade pasta ."], "output": "[['Pizza', 'terrific', 'positive'], ['homemade pasta', '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": ["Ambience is delightful , service impeccable ."], "output": "[['Ambience', 'delightful', 'positive'], ['service', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hanger steak was like rubber and the tuna was flavorless not to mention it tasted like it had just been thawed ."], "output": "[['hanger steak', 'rubber', 'negative'], ['tuna', 'flavorless', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 also horrible and the ambience is not that great ."], "output": "[['Service', 'horrible', 'negative'], ['ambience', 'not that great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 my first time writing a review for a restaurant because the food and service was excellent ."], "output": "[['food', 'excellent', '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": ["The filet mignon dish was superb !"], "output": "[['filet mignon dish', '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": ["It 's a small cute restaurant ."], "output": "[['restaurant', 'small cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 absolutely 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": ["I like the ambience , it 's very dark and original ."], "output": "[['ambience', 'like', 'positive'], ['ambience', 'dark', 'positive'], ['ambience', 'original', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 amazing ! ! !"], "output": "[['sushi', '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": ["My Girlfriend and I stumbled onto this hopping place the other night and had a great time !"], "output": "[['place', 'hopping', 'positive'], ['place', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and wine were excellent -- the service too -- but what really MADE this place was the backyard dining area ."], "output": "[['Pizza', 'excellent', 'positive'], ['wine', 'excellent', '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": ["First of all , this place is *not* romantic , as claimed by Citysearch 's editorial review ."], "output": "[['place', '*not* romantic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The tables are crammed way too close , the menu is typical of any Italian restaurant , and the wine list is simply overpriced ."], "output": "[['tables', 'crammed', 'negative'], ['tables', 'too close', 'negative'], ['menu', 'typical', 'neutral'], ['wine list', '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": ["Slightly above average wines start at $ 70+ with only one selection listed at $ 30+ ."], "output": "[['wines', 'above 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 is not what one would expect from a joint in this price category ."], "output": "[['Service', 'not what one would expect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Somehow working the italian charm with constant mille grazie does not constitute proper service ."], "output": "[['service', 'not constitute proper', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 completely fair , the only redeeming factor was the food , which was above average , but could n't make up for all the other deficiencies of Teodora ."], "output": "[['food', 'above average', 'positive'], ['Teodora', 'deficiencies', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 one of our meals was edible - bland and/or made with weird rosemary or orange flavoring ."], "output": "[['meals', 'edible', 'negative'], ['rosemary or orange flavoring', '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": ["Fish was overdone ."], "output": "[['Fish', 'overdone', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 us actually liked the expresso - that 's it ."], "output": "[['expresso', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Skip this restaurant , it 's a big disappointment ."], "output": "[['restaurant', 'Skip', 'negative'], ['restaurant', '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": ["Myagi is one of my favorite restaurants in the City ; the place the negative reviews describe sound like they were somewhere else ."], "output": "[['Myagi', '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": ["Their tuna tartar appetizer is to die for ."], "output": "[['tuna tartar appetizer', '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": ["I come from a family of pizzeria owners , and I 'm almost ashamed to say that the pizza in Fornino 's blows my families receipies away ."], "output": "[['pizza', 'ashamed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to anyone to give this place a try ."], "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": ["A restaurant that does n't try to do anything except serve great food with great service in a pleasant atmosphere ."], "output": "[['food', 'great', 'positive'], ['service', 'great', 'positive'], ['atmosphere', '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": ["The dining room is quietly elegant with no music to shout over -- how refreshing !"], "output": "[['dining room', 'elegant', 'positive'], ['dining room', '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": ["The service was impeccable and unobtrusive -- the staff knows what they are there to do -- to know their menu , present your meal , and attend to your needs ."], "output": "[['service', 'impeccable', 'positive'], ['service', 'unobtrusive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Looking around , I saw a room full of New Yorkers enjoying a real meal in a real restaurant , not a clubhouse of the fabulous trying to be seen ."], "output": "[['meal', 'real', 'positive'], ['restaurant', 'real', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The view is breathtaking the service is top notch ... the ambiance is wonderful ."], "output": "[['view', 'breathtaking', 'positive'], ['service', 'top notch', 'positive'], ['ambiance', '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 staff offers impeccable service ."], "output": "[['staff', 'impeccable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 boyfriend had Prime Rib it was good ."], "output": "[['Prime Rib', '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 did n't want a bottle of bubbly on a weekday so we each got little bottles of Korbett it was just enough ."], "output": "[['bottles of Korbett', '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": ["If you like spicy food get the chicken vindaloo ."], "output": "[['chicken vindaloo', 'get', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 to Volare for 1st class service and terrific food ."], "output": "[['service', '1st class', 'positive'], ['food', '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 portions are large and the servers always surprise us with a different starter ."], "output": "[['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 excellent ."], "output": "[['wine list', '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 food is amazing ... especially if you get the Chef 's tasting menu and your favourite bottle ( or two ! ) of wine from an extensive selection of wines ."], "output": "[['food', 'amazing', 'positive'], ['selection of wines', '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": ["The place is small and intimate and you may feel a little crowded , but the service is excellent and it 's great for friends out , a romantic date , or a special occassion ."], "output": "[['service', 'excellent', 'positive'], ['place', 'small', 'positive'], ['place', 'intimate', 'positive'], ['place', 'crowded', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you do n't like ."], "output": "[['food', 'pricey', 'negative'], ['prixe fixe tasting menu', '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": ["With the exception of our lemon salad that had so much pepper on it that our eyes started watering , the food here was decent , not great ."], "output": "[['food', 'decent', 'neutral'], ['food', 'not great', 'neutral'], ['lemon salad', 'exception', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 very limited - i think we counted 4 or 5 entrees ."], "output": "[['menu', '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 ordered the special , grilled branzino , that was so infused with bone , it was difficult to eat ."], "output": "[['grilled branzino', 'difficult to 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": ["The decor in this place is very diner-ish and the kind of place you expect in the East Village - not romantic , just simple , small and sparse ."], "output": "[['decor', 'diner-ish', '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": ["Problem is nothing at Prune is particularly memorable ."], "output": "[['Prune', 'memorable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 so much fun ."], "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": ["Our food was great too !"], "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": ["And really large portions ."], "output": "[['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 the friendliest that have seen in New York ."], "output": "[['staff', 'friendliest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 something really different than try Jekyll and Hyde ."], "output": "[['Jekyll and Hyde', '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": ["The food was pretty tradional but it was hot and good with large portions ."], "output": "[['food', 'tradional', 'positive'], ['portions', 'large', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 lot of fun ."], "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": ["The food however , is what one might expect ."], "output": "[['food', 'expect', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 think Jeckll and Hydes t is one of those places that is fun to do once ."], "output": "[['Jeckll and Hydes', '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": ["Service was slow had to wait to order and get food although not crowded ."], "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": ["Drinks way over priced ."], "output": "[['Drinks', '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": ["Great pizza for lunch place ."], "output": "[['pizza', '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": ["Service was 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": ["The pizza was great ."], "output": "[['pizza', '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": ["Whenever you need a Sushi fix , Mizu will be there with quality fish and great service ."], "output": "[['fish', 'quality', '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": ["Delivery is fast too ."], "output": "[['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": ["Great friendly service , Fast seating , Fast Delivery , Excellent sushi ."], "output": "[['service', 'Great friendly', 'positive'], ['seating', 'Fast', 'positive'], ['Delivery', 'Fast', 'positive'], ['sushi', '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": ["Ess-A-Bagel ( either by Sty-town or midtown ) is by far the best bagel in NY ."], "output": "[['bagel', '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 bagels always warm , soft on the inside , crispy on the outside and enormous in size ."], "output": "[['bagels', 'warm', 'positive'], ['bagels', 'soft', 'positive'], ['bagels', 'crispy', 'positive'], ['bagels', 'enormous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 huge selection of different cream cheeses and all of their salads are great ."], "output": "[['salads', 'great', 'positive'], ['cream cheeses', 'huge', 'positive'], ['cream cheeses', '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": ["Not impressed with the food ."], "output": "[['food', 'Not impressed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 too high for this cramped and unappealing resturant ."], "output": "[['resturant', 'cramped', 'negative'], ['resturant', 'unappealing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Zero ambiance to boot ."], "output": "[['ambiance', 'Zero', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 this place was totally overrated ."], "output": "[['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": ["The ambience was nice , but service was n't so great ."], "output": "[['ambience', 'nice', 'positive'], ['service', \"was n't so great\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 BEST Shabu-Shabu Restaurant in the Try-State Area ."], "output": "[['Shabu-Shabu 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": ["Thius is a must for anyone who loves Shabu-Shabu ."], "output": "[['Shabu-Shabu', 'loves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 nothing special , but it feels like a Sushi establishment in Tokyo ."], "output": "[['atmosphere', 'nothing special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and staff are all Japanese as well and that adds to the entire ambiance ."], "output": "[['ambiance', 'adds', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 a slightly limited menu , everything prepared is done to perfection , ultra fresh and a work of food art ."], "output": "[['menu', '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": ["Taxan delicious !"], "output": "[['Taxan', '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 location and ambience is Ok but the food is what makes up for it ."], "output": "[['location', 'Ok', 'neutral'], ['ambience', '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": ["Try green curry with vegetables ."], "output": "[['green curry with vegetables', '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 had the best ravioli ever ."], "output": "[['ravioli', '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 quaint and romantic trattoria is at the top of my Manhattan restaurant list ."], "output": "[['trattoria', 'quaint', 'positive'], ['trattoria', '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 is delicious - from the specials to the regular menu-fare , the dishes are never a disappointment ."], "output": "[['food', 'delicious', 'positive'], ['dishes', 'never a disappointment', 'positive'], ['specials', 'delicious', 'positive'], ['specials', 'never a disappointment', 'positive'], ['regular menu-fare', 'delicious', 'positive'], ['regular menu-fare', 'never a disappointment', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 the tables may be closely situated , the candle-light , food quality and service overcompensate ."], "output": "[['candle-light', 'overcompensate', 'positive'], ['food', 'overcompensate', 'positive'], ['service', 'overcompensate', 'positive'], ['tables', 'closely situated', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 go , try the marinara/arrabiatta sauce , the mozzarella en Carozza is mmmmmmmm ... .. everything is just delicious ."], "output": "[['marinara/arrabiatta sauce', 'try', 'positive'], ['marinara/arrabiatta sauce', 'delicious', 'positive'], ['mozzarella en Carozza', '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": ["Check out the secret back room ."], "output": "[['back room', 'secret', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , service and value exceptional everytime I have been there ."], "output": "[['food', 'exceptional', 'positive'], ['service', '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": ["The food was authentic ."], "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": ["The service was excellent - friendly and attentive ."], "output": "[['service', 'excellent', '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": ["Very good wine choices ."], "output": "[['wine choices', '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": ["Who has room for Cheesesticks with the best pizza in NYC !"], "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": ["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": ["The food is good , I ca n't lie ."], "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": ["But the staff was so horrible to us ."], "output": "[['staff', '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": ["This place is pricey , and yes , the food is worth it ; but the service makes you feel like you should be paying a quater of the price ."], "output": "[['place', 'pricey', 'negative'], ['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": ["Amma is nothing special ."], "output": "[['Amma', 'nothing special', '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 ate here a week ago and found most dishes average at best and too expensive ."], "output": "[['dishes', 'average', 'negative'], ['dishes', 'too 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": ["Do n't dine at Tamarind for the vegetarian dishes , they are simply not up to par with the non-veg selections ."], "output": "[['vegetarian dishes', 'not up to 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": ["Decor is nice though service can be spotty ."], "output": "[['Decor', 'nice', 'positive'], ['service', 'spotty', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , food is 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 am happy i did the food was awsome ."], "output": "[['food', 'awsome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Haru on Park S is simply disgusting ."], "output": "[['Haru on Park S', '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 fish was not fresh and the rice tasted old and stale ."], "output": "[['fish', 'not fresh', 'negative'], ['rice', 'old', 'negative'], ['rice', 'stale', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Quite frankly , this is some of the worst sushi I have ever tried ."], "output": "[['sushi', '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": ["honestly the worst sushi my husband and i had in our entire lives ."], "output": "[['sushi', '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": ["not sure why this restaurant would be rated that highly ."], "output": "[['restaurant', 'highly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the all-u-can-eat sushi is definitely in very poor quality ."], "output": "[['all-u-can-eat sushi', 'poor quality', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["limited menu , no-so-fresh ingredients , thinly-sliced fish , fall-apart rice ."], "output": "[['menu', 'limited', 'negative'], ['ingredients', 'no-so-fresh', 'negative'], ['fish', 'thinly-sliced', 'negative'], ['rice', 'fall-apart', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 things u could really taste are the very salty soy sauce ( even its low sodium ) , the vinegar-soaked rice , and the scallion on top of the fish ."], "output": "[['soy sauce', 'salty', 'negative'], ['rice', 'vinegar-soaked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["the waitstaffs are nice though ."], "output": "[['waitstaffs', '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": ["Both times I was extremely dissappointed by the service , which was boarderline rude ."], "output": "[['service', 'dissappointed', 'negative'], ['service', '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 dinner was ok , nothing I would have again ."], "output": "[['dinner', '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 had their eggs benedict for brunch , which were the worst in my entire life , I tried removing the hollondaise sauce completely that was how failed it was ."], "output": "[['eggs benedict', '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": ["With the theater 2 blocks away we had a delicious meal in a beautiful room ."], "output": "[['meal', 'delicious', 'positive'], ['room', '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 service was attentive ."], "output": "[['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": ["Planet Thai is great !"], "output": "[['Planet Thai', '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 love the food , drinks , and atmosphere !"], "output": "[['food', 'love', 'positive'], ['drinks', 'love', 'positive'], ['atmosphere', '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 svc can be a bit rude at times , esp if you have big group , but overall the restaurant is a must !"], "output": "[['svc', 'rude', 'negative'], ['restaurant', '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": ["Try the Pad Thai , it 's fabulous and their prices are so cheap !"], "output": "[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'fabulous', 'positive'], ['Pad Thai', '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": ["Just because it 's cheap does NOT mean the portions are small or the food is nasty , IT IS GREAT !"], "output": "[['portions', 'small', 'positive'], ['food', 'nasty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Eating in , the atmosphere saves it , but at your desk , it 's a very disappointing experience ."], "output": "[['atmosphere', 'saves', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The seats are uncomfortable if you are sitting against the wall on wooden benches ."], "output": "[['seats', '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": ["Patroon features a nice cigar bar and has great staff ."], "output": "[['cigar bar', 'nice', '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": ["The food is tasty and portion sizes are appropriate ."], "output": "[['food', 'tasty', 'positive'], ['portion sizes', 'appropriate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 nice restaurant if you are looking for a good place to host an intimate dinner meeting with business associates ."], "output": "[['restaurant', '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": ["Not a great place for family or general dining ."], "output": "[['place', 'Not a great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ."], "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": ["Waitstaff are very friendly ."], "output": "[['Waitstaff', '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": ["Mermaid Inn is an overall good restaurant with really good seafood ."], "output": "[['seafood', 'good', 'positive'], ['Mermaid Inn', '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 menu is limited but almost all of the dishes are excellent ."], "output": "[['menu', 'limited', 'negative'], ['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": ["The lobster sandwich is good and the spaghetti with Scallops and Shrimp is great ."], "output": "[['lobster sandwich', 'good', 'positive'], ['spaghetti with Scallops and Shrimp', '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 good and ambience is good for a date or group outing ."], "output": "[['service', 'good', 'positive'], ['ambience', '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 only fallback on this restaurant is the prices ."], "output": "[['restaurant', 'fallback', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 its good seafood , the prices are too high ."], "output": "[['seafood', '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": ["The lobster sandwich is $ 24 and although it was good it was not nearly enough to warrant that price ."], "output": "[['lobster sandwich', 'good', 'negative'], ['lobster sandwich', 'not nearly enough to warrant that 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": ["The food was delicious ( I had a halibut special , my husband had steak ) , and the service was top-notch ."], "output": "[['food', 'delicious', 'positive'], ['service', '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": ["Truly the mark of an attentive waiter ."], "output": "[['waiter', '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": ["I highly recommend the restaurant based on our experience last night ."], "output": "[['restaurant', '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": ["We ate at this Thai place following the reviews but very unhappy with the foods ."], "output": "[['foods', 'unhappy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 jelly fish , drunken chicken and the soupy dumplings , certainly the stir fry blue crab ."], "output": "[['jelly fish', 'recommend', 'positive'], ['drunken chicken', 'recommend', 'positive'], ['soupy dumplings', 'recommend', 'positive'], ['stir fry blue crab', '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": ["Have frequented 'ino for several years and the food remains 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": ["Cheese plate is a varied delight and great bargain at $ 10 ."], "output": "[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["( The asparagus , truffle oil , parmesan bruschetta is a winner ! )"], "output": "[['asparagus , truffle oil , parmesan bruschetta', '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": ["Wine list is extensive without being over-priced ."], "output": "[['Wine list', 'extensive without being over-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": ["I loved this place ! !"], "output": "[['place', '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": ["I almost hesititate to write a review because the atmosphere was so great and I would hate for it too become to crowded ."], "output": "[['atmosphere', '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 very good , a great deal , and the place its self was great ."], "output": "[['food', 'good', '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": ["The wait staff is very freindly , they make it feel like you 're eating in a freindly little european town ."], "output": "[['wait staff', 'freindly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Cafe Noir dont get me wrong , it is jsut that the people who work there are evil and incompetent ! !"], "output": "[['people', 'evil', 'negative'], ['people', 'incompetent', 'negative'], ['Cafe Noir', '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 service was terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ."], "output": "[['service', '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": ["The whole set up is truly unprofessional and I wish Cafe Noir would get some good staff , because despite the current one this is a great place ."], "output": "[['staff', 'good', 'negative'], ['Cafe Noir', '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": ["Pizza here is consistently good ."], "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": ["You should pass on the calamari ."], "output": "[['calamari', 'pass', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 is charming ."], "output": "[['Decor', '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": ["Service is average ."], "output": "[['Service', '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": ["What a great place ."], "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 ambience was so fun , and the prices were great , on top of the fact that the food was really tasty ."], "output": "[['ambience', 'fun', 'positive'], ['food', '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 was here a few weeks back and we had the worst customer service experience at a restaurant ever ."], "output": "[['customer 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": ["Excellent atmosphere , delicious dishes good and friendly service ."], "output": "[['atmosphere', 'Excellent', 'positive'], ['dishes', 'delicious', 'positive'], ['service', 'good', '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 wine list is also really nice ."], "output": "[['wine list', '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 would highly 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": ["I have been to Casimir over 5 times and I have always had a great time there ."], "output": "[['Casimir', 'great time', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 reasonably priced ."], "output": "[['food', 'great', '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 staff has been nice , but they seemed really stressed and the unisex bathroom needs to be cleaned more often ."], "output": "[['staff', 'nice', 'negative'], ['staff', 'stressed', 'negative'], ['unisex bathroom', 'stressed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 spectacular caviar to the hospitable waitstaff , I felt like royalty and enjoyed every second of it ."], "output": "[['caviar', 'spectacular', 'positive'], ['caviar', 'enjoyed', 'positive'], ['waitstaff', 'hospitable', 'positive'], ['waitstaff', '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": ["Considering we were the last patrons there and it was after the closing time , the waitstaff did not rush us at all and made us feel comfortable and relaxed ."], "output": "[['waitstaff', 'comfortable', 'positive'], ['waitstaff', '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": ["I highly recommend Caviar Russe to anyone who wants delicious top grade caviar and fantastic service ."], "output": "[['caviar', 'delicious top grade', '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": ["Fresh ingredients and everything is made to order ."], "output": "[['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": ["Friendly staff that actually lets you enjoy your meal and the company you 're with ."], "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": ["I found the food to be outstanding , particulary the salmon dish I had ."], "output": "[['food', 'outstanding', 'positive'], ['salmon dish', '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": ["My friends settled for rice dishes , but we came back the following day to try the dim sum , which was good ... not outstanding , but good ."], "output": "[['dim sum', 'good', 'neutral'], ['dim sum', '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": ["We ate out in the back patio , which is worth it as it 's cool and the music is hear well there ."], "output": "[['back patio', 'worth', 'positive'], ['back patio', 'cool', 'positive'], ['music', '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": ["Overall , excellent restaurant !"], "output": "[['restaurant', '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 food was 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": ["but the service was a bit slow ."], "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 buffet had a nice selection ."], "output": "[['buffet', '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 average or above including some surprising tasty dishes ."], "output": "[['food', 'average or above', 'positive'], ['dishes', '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": ["Service was also 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": ["I got an excellent piece of cheesecake and we had several other nice pastries ."], "output": "[['cheesecake', 'excellent', 'positive'], ['pastries', '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 would recommend Roxy 's for that , but not for their food ."], "output": "[['food', '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": ["My son and his girlfriend both wanted cheeseburgers and they were huge !"], "output": "[['cheeseburgers', 'huge', '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 place is really trendi but they have forgotten about the most important part of a restaurant , the food ."], "output": "[['food', 'forgotten', 'negative'], ['place', 'trendi', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The last two times I ordered from here my food was soo spicy that I could barely eat it , and the spice took away from the flavor of the dish ."], "output": "[['food', '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": ["And the Tom Kha soup was pathetic ."], "output": "[['Tom Kha soup', 'pathetic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 authentic Thai this place is not the place to go ."], "output": "[['Thai', 'good authentic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 went here for lunch a couple of weeks ago on a Saturday , and I was thoroughly impressed with the food ."], "output": "[['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 pesto pizza was excellent , thin-crust pizza with a nice amount of spicy Italian cheese that I 'd never heard of before ."], "output": "[['pesto pizza', 'excellent', 'positive'], ['spicy Italian cheese', '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": ["We had the lobster sandwich and it was FANTASTIC ."], "output": "[['lobster sandwich', '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": ["My husband said he could 've eaten several more , the portion was fine for me he even exclaimed that the french fries were the best he has had ."], "output": "[['portion', 'fine', 'positive'], ['french fries', '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": ["We had the scallops as an appetizer and they were delicious and the sauce was wonderful ."], "output": "[['scallops', 'delicious', 'positive'], ['sauce', '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 waited at the bar and had martinis that were just right ."], "output": "[['martinis', '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": ["love the food ."], "output": "[['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": ["it 's the only place you can get yummy authentic japanese comfort food ."], "output": "[['japanese comfort food', 'yummy 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": ["Great food , good size menu , great service and an unpretensious setting ."], "output": "[['food', 'Great', 'positive'], ['menu', 'good size', 'positive'], ['service', 'great', 'positive'], ['setting', 'unpretensious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 offered were unique , very tasty and fresh from the lamb sausages , sardines with biscuits , large whole shrimp to the amazing pistachio ice cream ( the best and freshest I 've ever had ) ."], "output": "[['dishes', 'unique', 'positive'], ['dishes', 'tasty', 'positive'], ['dishes', 'fresh', 'positive'], ['pistachio ice cream', '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 was introduced to this place and this is a rare gem in NY ."], "output": "[['place', 'glad', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The freshest , best variety , and the fastest delivery ."], "output": "[['delivery', '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": ["The service was excellent and the food was delicious ."], "output": "[['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": ["We are very particular about sushi and were both please with every choice which included : ceviche mix ( special ) , crab dumplings , assorted sashimi , sushi and rolls , two types of sake , and the banana tempura ."], "output": "[['sushi', 'particular', 'positive'], ['ceviche mix ( special )', 'please', 'positive'], ['crab dumplings', 'please', 'positive'], ['assorted sashimi', 'please', 'positive'], ['rolls', 'please', 'positive'], ['banana tempura', '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": ["Definitely a great spot for a nice occasion or date ."], "output": "[['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": ["Average to good Thai food , but terrible delivery ."], "output": "[['Thai food', 'Average to good', 'positive'], ['delivery', '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": ["The food arrived 20 minutes after I called , cold and soggy ."], "output": "[['food', 'cold', 'negative'], ['food', 'soggy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 wonderful place on all stand points especially value ofr money ."], "output": "[['place', '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": ["An excellent service"], "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": ["We were greeted promptly by the waiter who was very nice and cordial ."], "output": "[['waiter', 'nice', 'positive'], ['waiter', 'cordial', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["She was very helpful in suggesting us drinks and helped us in ordering a lot of good dishes since we knew nothing about Indian food ."], "output": "[['dishes', '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 looked very appetizing and delicious since it came on a variety of fancy plates ."], "output": "[['food', 'appetizing', '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": ["Service here was great , food was fantastic ."], "output": "[['Service', 'great', 'positive'], ['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": ["Guacamole+shrimp appetizer was really great , we both had the filet , very good , did n't much like the frites that came with , but the filet was so good , neither of us cared ."], "output": "[['Guacamole+shrimp appetizer', 'great', 'positive'], ['filet', '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 can not go wrong with this place ."], "output": "[['place', 'wrong', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 outstanding and the service is quick , friendly and very professional ."], "output": "[['food', 'outstanding', 'positive'], ['service', 'quick', 'positive'], ['service', 'friendly', 'positive'], ['service', '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": ["Always a nice crowd , but never loud ."], "output": "[['crowd', 'nice', 'positive'], ['crowd', 'never 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": ["By far , the best pizza in Manhattan ."], "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 crust is thin , the ingredients are fresh and the staff is friendly ."], "output": "[['crust', 'thin', 'positive'], ['staff', 'friendly', '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": ["The fish was really , really fresh ."], "output": "[['fish', '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": ["We all agreed that mare is one of the best seafood restaurants in New York ."], "output": "[['mare', '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 stumbled upon this great pizzeria as I explored my new neighborhood ."], "output": "[['pizzeria', '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": ["All of the pizzas are terrific and the price is even better !"], "output": "[['pizzas', '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": ["I highly recommend the Sophia pizza ."], "output": "[['Sophia pizza', '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 was mediocre at best but it was the horrible service that made me vow never to go back ."], "output": "[['food', 'mediocre', 'negative'], ['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": ["For the people who want great food plus great service , Roxy is a place to AVOID !"], "output": "[['food', 'great', 'negative'], ['service', 'great', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The first time the sushi was outstanding , the second time it was a little bland ."], "output": "[['sushi', 'outstanding', 'negative'], ['sushi', '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 blond wood decor is very soothing , the premium sake is excellent and the service is great ."], "output": "[['blond wood decor', 'soothing', 'positive'], ['premium sake', 'soothing', '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": ["Mizu is home to creative and unique rolls not to found anywhere else ."], "output": "[['rolls', '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": ["Not only is the cuisine the best around , the service has always been attentive and charming ."], "output": "[['cuisine', 'best', 'positive'], ['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": ["Warning : You may find it difficult to dine at other Japanese restaurants after a visit to Mizu !"], "output": "[['Mizu', 'difficult', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 smoked salmon and roe appetizer and it was off flavor ."], "output": "[['smoked salmon and roe appetizer', 'off flavor', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 bland and small , dessert was not inspired ."], "output": "[['entree', 'bland', 'negative'], ['entree', 'small', 'negative'], ['dessert', 'not inspired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 strawberry daiquiries as well !"], "output": "[['strawberry daiquiries', '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": ["delicious simple food in nice outdoor atmosphere ."], "output": "[['food', 'delicious simple', 'positive'], ['outdoor 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": ["Delicious crab cakes too ."], "output": "[['crab cakes', '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": ["Even if the food was n't this good , the garden is a great place to sit outside and relax ."], "output": "[['garden', 'great', 'positive'], ['food', \"was n't this 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 neighborhood joint ."], "output": "[['joint', '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 a nice pizza place with good selection of thin crust pizza including the Basil slice ."], "output": "[['selection of thin crust pizza', 'good', 'positive'], ['pizza place', 'nice', 'positive'], ['Basil slice', '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": ["Their calzones are horrific , bad , vomit-inducing , YUCK ."], "output": "[['calzones', 'horrific', 'negative'], ['calzones', 'bad', 'negative'], ['calzones', 'vomit-inducing', 'negative'], ['calzones', 'YUCK', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The counter service is bad ."], "output": "[['counter 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": ["The dosas are skimpy , unattractive and drip with grease , and personally I 'd drink popcorn topping before I 'd eat another one of these ."], "output": "[['dosas', 'skimpy', 'negative'], ['dosas', 'unattractive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sandwiches are dry , tasteless and way overpriced ."], "output": "[['sandwiches', 'dry', 'negative'], ['sandwiches', 'tasteless', 'negative'], ['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": ["Calling the place Hampton Chutney Co. does warn you that these folks offer more style than substance , but in this unattractive room with unhelpful clerks there was a dearth of the former too ."], "output": "[['place', 'unattractive', 'negative'], ['room', 'unattractive', 'negative'], ['clerks', 'unhelpful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Seriously , this place kicks ass ."], "output": "[['place', 'kicks ass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Italian food I ever had ( and being Italian , that means alot ) ."], "output": "[['Italian 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 restaurant looks out over beautiful green lawns to the Hudson River and the Statue of Liberty ."], "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": ["The food is good , especially their more basic dishes , and the drinks are delicious ."], "output": "[['food', 'good', 'positive'], ['basic dishes', 'good', 'positive'], ['drinks', '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": ["This is a great place to take out-of-towners , and perfect for watching the sunset ."], "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": ["Unique apppetizers ."], "output": "[['apppetizers', '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": ["Try sushimi cucumber roll ."], "output": "[['sushimi cucumber 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": ["Good spreads , great beverage selections and bagels really tasty ."], "output": "[['spreads', 'Good', 'positive'], ['beverage selections', 'great', 'positive'], ['bagels', '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 service is awful ."], "output": "[['service', '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": ["I will be out with friends and all of a sudden I am hungry and I only crave one thing ... their Pizza ."], "output": "[['Pizza', 'crave', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 tiny Williamsburg spot is always pleasantly surprising ."], "output": "[['Williamsburg spot', 'surprising', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 proprietor is one of the nicest in NYC ."], "output": "[['pizza', 'delicious', 'positive'], ['proprietor', '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": ["The cream cheeses are out of this world and I love that coffee ! !"], "output": "[['cream cheeses', 'out of this world', 'positive'], ['coffee', '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": ["Bagels are ok , but be sure not to make any special requests !"], "output": "[['Bagels', '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 turkey burgers are scary !"], "output": "[['turkey burgers', 'scary', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 awful !"], "output": "[['sushi', '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": ["Furthermore , the rice had no seasoning , so the sushi was bland and disgusting ."], "output": "[['sushi', 'bland', 'negative'], ['sushi', '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": ["Good , fast service ."], "output": "[['service', 'Good', 'positive'], ['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": ["Food is great and inexpensive ."], "output": "[['Food', 'great', 'positive'], ['Food', '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 location is perfect ."], "output": "[['location', '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": ["Well , this place is so Ghetto its not even funny ."], "output": "[['place', 'Ghetto', 'negative'], ['place', 'not even funny', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 like your music blasted and the system isnt that great and if you want to pay at least 100 dollar bottle minimun then you 'll love it here ."], "output": "[['music', '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": ["Awsome Pizza especially the Margheritta slice ."], "output": "[['Pizza', 'Awsome', 'positive'], ['Margheritta slice', 'Awsome', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 atmoshere and worth every bit ."], "output": "[['atmoshere', '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": ["Winnie and her staff are the best crew you can find serving you ."], "output": "[['staff', 'best', 'positive'], ['Winnie', '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 reliable and the price is moderate ."], "output": "[['food', '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": ["For authentic Thai food , look no further than Toons ."], "output": "[['Thai 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": ["Try the Pad Thai , or sample anything on the appetizer menu ... they 're all delicious ."], "output": "[['Pad Thai', 'Try', 'positive'], ['Pad Thai', 'delicious', 'positive'], ['appetizer 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": ["Everything about this restaurant was special ."], "output": "[['restaurant', 'special', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 attentive , yet discreet ."], "output": "[['service', 'attentive', 'positive'], ['service', 'discreet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The brioche and lollies as party favors is a cute and sweet touch to a most memorable meal ."], "output": "[['brioche and lollies', 'cute', 'positive'], ['brioche and lollies', '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 place was quiet and delightful ."], "output": "[['place', 'quiet', 'positive'], ['place', '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": ["Service was good and food is wonderful ."], "output": "[['Service', 'good', '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 did not try the caviar but I tried their salmon and crab salad ( they are all good )"], "output": "[['salmon', 'good', 'positive'], ['crab salad', '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 is definitely a good spot for snacks and chat ."], "output": "[['spot', '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": ["As a retired hipster , I can say with some degree of certainty that for the last year Lucky Strike has been the best laid-back late night in the city ."], "output": "[['Lucky Strike', '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 yummy , especially their cooked-to-perfection mussels in spicy tomato sauce and their shoestring crispy fries ."], "output": "[['food', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'yummy', 'positive'], ['mussels in spicy tomato sauce', 'cooked-to-perfection', 'positive'], ['fries', 'yummy', 'positive'], ['fries', '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": ["You can get a completely delish martini in a glass ( that 's about 2 1/2 drinks ) for $ 8.50 ( I recommend the Vanilla Shanty , mmmm ! ) in a great homey setting with great music ."], "output": "[['martini', 'delish', 'positive'], ['Vanilla Shanty', 'recommend', 'positive'], ['setting', 'homey', 'positive'], ['music', '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 in-house lady DJ on Saturday nights has outrageously good taste in music , and moreover , takes requests ."], "output": "[['in-house lady DJ', 'good taste', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 ca n't go wrong with this place ."], "output": "[['place', \"ca n't go wrong\", 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 location is good and the fact that Hutner College is near and their prices are very reasonable , makes students go back to Suan again and again ."], "output": "[['location', 'good', 'positive'], ['Suan', '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": ["I LOVE their Thai"], "output": "[['Thai', '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": ["In summer-eat outside on a terrace ( another great feature of Suan ) ! ! !"], "output": "[['terrace', '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": ["During the course of the past 3 months , the chef and staff changed and it was not for the better ."], "output": "[['chef', 'changed', 'negative'], ['staff', 'changed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 now is inconsistent ."], "output": "[['food', 'inconsistent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 kind of place you 'd like to take all your friends to and still keep a secret ."], "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 setting is casual and romantic ."], "output": "[['setting', 'casual', 'positive'], ['setting', '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 is 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": ["The wait here is long for dim sum , but if you do n't like sharing tables or if the typical raucous dim sum atmosphere is not your gig , this is a sleek ( for Chinatown ) alternative ."], "output": "[['wait', 'long', 'negative'], ['atmosphere', 'sleek', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 choose to go with one of the special , the braised lamb shank in red wine , which was excellent ."], "output": "[['braised lamb shank in red wine', '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 service was friendly and the atmosphere was casual ."], "output": "[['service', 'friendly', 'positive'], ['atmosphere', 'casual', '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 restaurant is a bit noisy but that is something that can be overlooked once you sit down and enjoy a great meal"], "output": "[['meal', 'enjoy', 'positive'], ['meal', 'great', 'positive'], ['restaurant', 'noisy', '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 little place has a cute interior decor and affordable city prices ."], "output": "[['interior decor', 'cute', 'positive'], ['place', '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": ["the pad se ew chicken was delicious , however the pad thai was far too oily ."], "output": "[['pad se ew chicken', 'delicious', 'positive'], ['pad thai', '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": ["Have eaten at Ginger House several times , and it 's always good ."], "output": "[['Ginger House', '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 fried dumplings are GREAT !"], "output": "[['fried dumplings', '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": ["Finally a reliable Chinese restaurant !"], "output": "[['Chinese restaurant', '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": ["Terrible , terrible management - deserves to be shut-down ."], "output": "[['management', 'Terrible', 'negative'], ['management', '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": ["delicious bagels , especially when right out of the oven ."], "output": "[['bagels', '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": ["Spreads and toppings are great - though a bit pricey ."], "output": "[['Spreads', 'great', 'negative'], ['Spreads', 'pricey', 'negative'], ['toppings', 'great', 'negative'], ['toppings', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 fast and friendly ."], "output": "[['Service', 'fast', '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 food is decent at best , and the ambience , well , it 's a matter of opinion , some may consider it to be a sweet thing , I thought it was just annoying ."], "output": "[['food', 'decent', 'negative'], ['ambience', '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": ["Rao is a good restaurant , but it 's nothing special ."], "output": "[['Rao', '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": ["You must try the shrimp appetizers ."], "output": "[['shrimp appetizers', '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 the the correct ambience and an excellent staff to make you feel like a guest and a friend at the same time ."], "output": "[['ambience', 'correct', 'positive'], ['staff', '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": ["Great food , great prices , great service ."], "output": "[['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": ["If you are looking for a good quality , cheap eats - this is the place ."], "output": "[['eats', 'good quality', 'positive'], ['eats', '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 really loved the different and inovated touch that 's the cheff gives to the food ."], "output": "[['cheff', 'loved', 'positive'], ['cheff', 'inovated', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it 's great to have dinner in a very romantic and comfortable place , the service it 's just perfect ... they 're so frendly that we never want to live the place !"], "output": "[['place', 'romantic', 'positive'], ['place', 'comfortable', 'positive'], ['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": ["Their bagels are fine , but they are a little overcooked , and not really a 'special ' bagel experience ."], "output": "[['bagels', 'fine', 'negative'], ['bagels', 'overcooked', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 bagels made the old-fashioned way ."], "output": "[['bagels', '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 absolutely amazing ! !"], "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": ["The baked clams octopus we shared as appetizers were the best we 've ever had ! !"], "output": "[['baked clams octopus', '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 lamb was tender so full of flavor , the dessert was divine ! !"], "output": "[['lamb', 'tender', 'positive'], ['dessert', '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": ["The waiter was attentive ."], "output": "[['waiter', '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 place itself is beautiful the bar scene seems to be happening ."], "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": ["Small servings for main entree , i had salmon ( wasnt impressed ) girlfriend had chicken , it was good ."], "output": "[['salmon', 'wasnt impressed', 'negative'], ['chicken', 'good', 'positive'], ['servings for main entree', '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": ["Dessert is a joke ... dont bother"], "output": "[['Dessert', 'joke', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Volare virgins or weekly regulars , everyone gets treated the same and you ca n't ask for more than that when the service is this friendly ."], "output": "[['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 restaurant has a Family feel , not least with regard to the portions which are enormous ; the veal alone could have single-handedly solved third world famine ."], "output": "[['portions', 'enormous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 and can easily hike up an otherwise reasonably priced meal ."], "output": "[['wine list', 'extensive', 'positive'], ['meal', '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": ["Still , any quibbles about the bill were off-set by the pour-your-own measures of liquers which were courtesey of the house ..."], "output": "[['measures of liquers', 'pour-your-own', 'positive'], ['measures of liquers', 'courtesey', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Fantastic place ."], "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": ["Lucky Strike is a great casual place to just grab a bite to eat ."], "output": "[['Lucky Strike', 'great 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": ["This is the perfect spot for meeting friends , having lunch , dinner , pre-theatre or after-theatre drinks !"], "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": ["Excellent spot for holiday get togethers with co-workers or friends that you have n't seen in a while ."], "output": "[['spot', '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 been doing all of the above at the Heartland Brewery for over 5 years now and I HAVE NEVER BEEN DISAPPOINTED !"], "output": "[['Heartland Brewery', 'NEVER BEEN 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": ["What a great place !"], "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": ["A cool bar with great food , and tons of excellent beer ."], "output": "[['bar', 'cool', 'positive'], ['food', 'great', 'positive'], ['beer', '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 shrimp scampi was excellent and the antipasti were plentiful ."], "output": "[['shrimp scampi', 'excellent', 'positive'], ['antipasti', 'plentiful', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 more wonderful than the food ( which is exceptional ) is the service ."], "output": "[['food', 'exceptional', 'positive'], ['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": ["Cozy romantic atomosphere with only around 15 tables at most ."], "output": "[['atomosphere', 'Cozy 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": ["Food was very good , but not what I would consider out of this world ."], "output": "[['Food', '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": ["Too bad the food was n't of the same heritage ."], "output": "[['food', '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 porcini mushroom pasta special was tasteless , so was the seafood tagliatelle ."], "output": "[['porcini mushroom pasta special', 'tasteless', 'negative'], ['seafood tagliatelle', '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": ["But that was n't the icing on the cake : a tiramisu that resembled nothing I have ever had ."], "output": "[['tiramisu', 'nothing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 liked this place ."], "output": "[['place', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Chinese style BBQ ribs in the city ."], "output": "[['BBQ ribs', '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 also recommend the rice dishes or the different varieties of congee ( rice porridge ) ."], "output": "[['rice dishes', 'recommend', 'positive'], ['congee ( rice porridge )', '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": ["It 's definately not a place to go if you want to impress someone ."], "output": "[['place', 'impress', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , if you want great food at a great price and do n't mind the decor , you ca n't beat this place ."], "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": ["Quick and friendly service ."], "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": ["When you 're sitting in their main dining room ( which has a spectacular , hand-painted high ceiling ) you 'd never know there was a world outside ."], "output": "[['main dining room', 'spectacular', 'positive'], ['ceiling', 'spectacular', 'positive'], ['ceiling', 'hand-painted 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": ["The food is wonderful , tasty and filling , and the service is professional and friendly ."], "output": "[['food', 'wonderful', 'positive'], ['food', 'tasty', 'positive'], ['food', 'filling', 'positive'], ['service', 'professional', '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 recently tried Suan and I thought that it was great ."], "output": "[['Suan', '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 little place definitely exceeded my expectations and you sure get a lot of food for your money ."], "output": "[['food', 'lot', 'positive'], ['place', '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": ["The service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals ."], "output": "[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['food', 'tasty', 'positive'], ['hot sauce', '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 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": ["Great spot , whether looking for a couple of drinks or quiet dinner ."], "output": "[['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": ["Warm and friendly in the winter and terrific outdoor seating in the warmer months ."], "output": "[['outdoor seating', '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 food is great and they have a good selection of wines at reasonable prices ."], "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": ["While the ambiance and atmosphere were great , the food and service could have been a lot better ."], "output": "[['ambiance', 'great', 'positive'], ['atmosphere', 'great', 'positive'], ['food', 'could have been a lot better', 'negative'], ['service', 'could have been a lot 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": ["Best Reuben sandwich ever !"], "output": "[['Reuben sandwich', '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": ["Do n't miss Bloom 's on your next trip to Manhatten ."], "output": "[[\"Bloom 's\", '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": ["Thanks Bloom 's for a lovely trip ."], "output": "[[\"Bloom 's\", 'Thanks', 'positive'], [\"Bloom 's\", '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 was not fresh , the sauces were bland and very oily ."], "output": "[['food', 'not fresh', 'negative'], ['sauces', 'bland', 'negative'], ['sauces', '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": ["Ravioli was good ... but I have to say that I found everything a bit overpriced ."], "output": "[['Ravioli', 'good', 'positive'], ['Ravioli', 'overpriced', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 enough wines by the glass either ."], "output": "[['wines by the glass', 'Not enough', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 , however , was excellent ... and I liked the setting/atmosphere a lot ."], "output": "[['Service', 'excellent', 'positive'], ['setting/atmosphere', 'liked', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 just average ... if they lowered the prices just a bit , it would be a bigger draw ."], "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": ["Authentic Pakistani food ."], "output": "[['Pakistani 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": ["People are always friendly ."], "output": "[['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": ["Just straight up cheap , good food ."], "output": "[['food', 'cheap', '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": ["Faan is sooo good ."], "output": "[['Faan', '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 best pad thai i 've ever had ."], "output": "[['pad thai', '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": ["bottles of wine are cheap and good ."], "output": "[['bottles of wine', 'cheap', 'positive'], ['bottles of 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 food was actually aweful ."], "output": "[['food', 'aweful', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The mussles were the fishiest things I 've ever tasted , the seabass was bland , the goat cheese salad was missing the goat cheese , the penne w/ chicken had bones in it ... It was disgusting ."], "output": "[['mussles', 'fishiest', 'negative'], ['seabass', 'bland', 'negative'], ['goat cheese salad', 'missing', 'negative'], ['penne w/ chicken', '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": ["Nice atmosphere , the service was very pleasant and the desert was good ."], "output": "[['atmosphere', 'Nice', 'positive'], ['service', 'pleasant', 'positive'], ['desert', '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 is amazing , rich pastas and fresh doughy pizza ."], "output": "[['food', 'amazing', 'positive'], ['pastas', 'rich', 'positive'], ['pizza', 'fresh doughy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 of all is the warm vibe , the owner is super friendly and service is fast ."], "output": "[['vibe', 'warm', 'positive'], ['owner', 'friendly', 'positive'], ['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": ["Ask for Usha , the nicest bartender in manhattan ."], "output": "[['Usha', '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": ["My fav was the sassy lassi ..."], "output": "[['sassy lassi', 'fav', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 recommend the very simple Unda ( Egg ) rolls ."], "output": "[['Unda ( Egg ) rolls', 'recommend', 'positive'], ['Unda ( Egg ) rolls', '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": ["Delicate spices , onions , eggs and a kick-ass roti ."], "output": "[['spices', 'Delicate', 'positive'], ['onions', 'Delicate', 'positive'], ['eggs', 'Delicate', 'positive'], ['roti', 'kick-ass', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Toons has recently been redone , so it 's now a very attractive space ."], "output": "[['Toons', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 an area sadly lacking in decent Thai food , this is one of the best spots ."], "output": "[['Thai 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": ["Went here last night - nice decor , good service , but the food was surprisingly excellent ."], "output": "[['decor', 'nice', 'positive'], ['service', 'good', '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": ["The portions are HUGE , so it might be good to order three things to split ( rather than one appetizer and entree per person ) for two people ."], "output": "[['portions', '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": ["Beef noodle soup is good as well ."], "output": "[['Beef noodle soup', '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 Taiwanese food in NY !"], "output": "[['Taiwanese 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 have been to Rao 's probably 15 times the past 3 years and it keeps getting better ."], "output": "[[\"Rao 's\", '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": ["Rao 's has the best service and atmosphere in NYC ."], "output": "[['service', 'best', 'positive'], ['atmosphere', '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": ["My roommate and 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": ["Indoor was very cozy and cute ."], "output": "[['Indoor', 'cozy', 'positive'], ['Indoor', 'cute', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The portion sizes here are huge , and the sushi is good ."], "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": ["Staff is very accomodating ."], "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": ["Excellent dumplings served amid clean , chic decor ."], "output": "[['dumplings', 'Excellent', 'positive'], ['decor', 'clean', 'positive'], ['decor', 'chic', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 very simple but comfortable ."], "output": "[['decor', 'simple', 'positive'], ['decor', '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": ["The food was delicious but do not come here on a empty stomach ."], "output": "[['food', '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 portions are small but being that the food was so good makes up for that ."], "output": "[['portions', 'small', 'negative'], ['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": ["You must have the crabmeat lasagna which is out of this world and the chocolate bread pudding for dessert ."], "output": "[['crabmeat lasagna', '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 staff there is very attentive and down to earth ."], "output": "[['staff', 'attentive', 'positive'], ['staff', 'down to earth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 and the prices are very reasonable ."], "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 fell in love with the egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork ."], "output": "[['egg noodles in the beef broth with shrimp dumplings and slices of BBQ roast pork', '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": ["This dish is my favorite and I always get it when I go there and never get tired of it ."], "output": "[['dish', '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": ["Try the congee and the donut like deep fried dough they call Ow Ley Soh , a delicious and sweet tasting bread ."], "output": "[['Ow Ley Soh', 'delicious', 'positive'], ['Ow Ley Soh', '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": ["Simply some good tasting Chinese food at incredible prices ..."], "output": "[['Chinese food', 'good tasting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 Wong is a great place to eat and fill your stomach ."], "output": "[['Big Wong', '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": ["whoever the jazz duo was , they were on POINT ."], "output": "[['jazz duo', '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": ["even the wine by the glass was good ."], "output": "[['wine by the glass', '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": ["Consistently good Japanese Tapas ."], "output": "[['Japanese Tapas', '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": ["Always good drinks and service is pretty good ;"], "output": "[['drinks', 'good', '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": ["A great place to meet up for some food and drinks ..."], "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": ["Yakitori ( bbq meats ) is tasty too ."], "output": "[['Yakitori ( bbq meats )', '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": ["Fabulous decor - makes you feel like you 're in a trendy Manhattan restaurant , very very good food , cheaply-priced , generally friendly staff , and if you 're a Manhattanite , or spend most of your time in Manhattan , Rice Avenue will make you feel at home ... ..very Soho/Village/Upper West Side minus the expensive prices and pretentious clientele ... ..all on Roosevelt Avenue !"], "output": "[['decor', 'Fabulous', 'positive'], ['food', 'good', 'positive'], ['food', 'cheaply-priced', '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": ["I am relatively new to the area and tried Pick a bgel on 2nd and was disappointed with the service and I thought the food was overated and on the pricey side ."], "output": "[['service', 'disappointed', 'negative'], ['food', 'overated', 'negative'], ['food', 'pricey', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more 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 okay and the prices here are mediocre ."], "output": "[['food', '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": ["Baluchi 's has solid food and a nice decor at reasonable prices ."], "output": "[['food', 'solid', 'positive'], ['decor', 'nice', 'positive'], [\"Baluchi 's\", '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 only problem is that the manager is a complete incompetent ."], "output": "[['manager', 'incompetent', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["He offers subpar service and has no personality ."], "output": "[['service', 'subpar', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 excuse for such lousy service !"], "output": "[['service', '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": ["I have never before eaten 40 pieces of relatively good nigiri ."], "output": "[['nigiri', '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": ["I went to Areo on a Sunday afternoon with four of my girlfriends , and spent three enjoyable hours there ."], "output": "[['Areo', '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": ["Most of the servers are very attentive , friendly and quite attractive ."], "output": "[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive'], ['servers', 'attractive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["The vibe is very relaxed and cozy , service was great and the food was excellent !"], "output": "[['vibe', 'relaxed', 'positive'], ['vibe', 'cozy', 'positive'], ['service', 'great', '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": ["The food is 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": ["Personal pans are the perfect size for those hungry nights ."], "output": "[['Personal pans', '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": ["There is a downside if you 're ordering in -- the delivery guys have MAJOR attitude ."], "output": "[['delivery guys', 'downside', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 have I had such dramatic delivery guys ( a lot of huffing and panting and muttering under breath b/c I live in a walkup ) who always seem disappointed with their tips ."], "output": "[['delivery guys', 'dramatic', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 scene first off- the place has a character and nice light to it..very fortunate , location wise ."], "output": "[['scene', 'Love', 'positive'], ['place', 'nice', 'positive'], ['location', 'fortunate', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 4 and got the family size penne a la vodka which was tremendously gigantic portion ... a bucket of food literally ."], "output": "[['penne a la vodka', '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 pasta penne was pretty extra buttery , creamy which means a big task to diggest.. tasty at first but i would say that i was full with a slice of pizza and 7 to count , penne ... got a little moody afterwards cause was stuffed ... lol"], "output": "[['pasta penne', 'buttery', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much more speed and the screen is very sharp .\"  Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}
{"task_type": "generation", "dataset": "aste-data-v2", "input": ["Interesting selection , good wines , service fine , fun decor ."], "output": "[['wines', 'good', 'positive'], ['service', 'fine', 'positive'], ['decor', 'fun', 'positive'], ['selection', 'Interesting', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 it on a cold night , the perfect spot to warm up ."], "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": ["I recieved prompt service with a smile ."], "output": "[['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": ["This place blew me away ... by far my new favorite restaurant on the uppereast side ."], "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": ["The wine list is extensive and impressive ."], "output": "[['wine list', 'extensive', 'positive'], ['wine list', '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": ["LOVE the atmosphere - felt like I was in Paris ."], "output": "[['atmosphere', '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 've also been amazed at all the new additions in the past few years : A new Jazz Bar , the most fantastic Dining Garden , the Best Thin Crust Pizzas , and now a Lasagna Menu which is to die for ( these are not your average lasagnas ) !"], "output": "[['Dining Garden', 'fantastic', 'positive'], ['Jazz Bar', 'new', 'positive'], ['Thin Crust Pizzas', 'Best', 'positive'], ['Lasagna Menu', '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": ["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": ["I have to say I have never had a disapointing meal here ."], "output": "[['meal', 'never had a disapointing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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 could have made a meal of the yummy dumplings from the dumpling menu ."], "output": "[['dumplings', '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": ["Luckily we saved room for the BBQ Salmon , Sea Bass and Crispy Duck ."], "output": "[['BBQ Salmon', 'Luckily', 'positive'], ['Sea Bass', 'Luckily', 'positive'], ['Crispy Duck', 'Luckily', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example:  Input: \"It has so much 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": ["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": ["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": ["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": ["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 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": ["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 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 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": ["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 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["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 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": ["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": ["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 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["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": ["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 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 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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']] "}