{"task_type": "generation", "dataset": "aste-data-v2", "input": ["In the shop , these MacBooks are encased in a soft rubber enclosure - so you will never know about the razor edge until you buy it , get it home , break the seal and use it ( very clever con ) ."], "output": "[['rubber enclosure', '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": ["This laptop meets every expectation and Windows 7 is great !"], "output": "[['Windows 7', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Drivers updated ok but the BIOS update froze the system up and the computer shut down ."], "output": "[['Drivers', 'ok', 'positive'], ['BIOS update', 'froze', 'negative'], ['system', '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": ["The fact that you can spend over $ 100 on just a webcam underscores the value of this machine ."], "output": "[['value', 'underscores', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 rarely works and when it does it 's incredibly slow ."], "output": "[['works', 'rarely', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 much easier to navigate through the operating system , to find files , and it runs a lot faster !"], "output": "[['operating system', 'easier', 'positive'], ['runs', 'faster', 'positive'], ['navigate', 'easier', 'positive'], ['find files', '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 am using the external speaker -- sound is good ."], "output": "[['external speaker', 'good', 'positive'], ['sound', '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 battery life seems to be very good , and have had no issues with it ."], "output": "[['battery life', 'good', 'positive'], ['battery life', 'no issues', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Temperatures on the outside were alright but i did not track in Core Processing Unit temperatures ."], "output": "[['Temperatures', 'alright', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["After about a week I finally got it back and was told that the motherboard had failed and so they installed a new motherboard ."], "output": "[['motherboard', 'failed', 'neutral'], ['motherboard', '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": ["It was slow , locked up , and also had hardware replaced after only 2 months !"], "output": "[['hardware', '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": ["Yes , the computer was light weight , less expensive than the average laptop , and was pretty self explantory in use ."], "output": "[['use', 'self explantory', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , very quiet for all the typing that I do ."], "output": "[['Keyboard', 'great', 'positive'], ['Keyboard', 'quiet', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The keyboard feels good and I type just fine on it ."], "output": "[['keyboard', '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 thought the white Mac computers looked dirty too quicly where you use the mousepad and where you place your hands when typing ."], "output": "[['mousepad', 'dirty', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 part of this computer is that it has a vga port so I can connect it to a bigger screen ."], "output": "[['vga port', 'favorite', 'positive'], ['screen', 'bigger', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , it 's still a very new laptop but in comparison to my previous laptops and desktops , my Mac boots up noticeably quicker ."], "output": "[['boots up', 'quicker', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 caught a virus that completely wiped out my hard drive in a matter of hours ."], "output": "[['hard drive', 'wiped 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 AMD Turin processor seems to always perform so much better than Intel ."], "output": "[['AMD Turin processor', '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": ["High price tag , however ."], "output": "[['price tag', '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 custom ordered the machine from HP and could NOT understand the techie due to his accent ."], "output": "[['techie', 'NOT understand', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 not so good , I got the stock screen - which is VERY glossy ."], "output": "[['stock screen', 'glossy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The gray color was a good choice ."], "output": "[['gray color', '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 like to have volume buttons rather than the adjustment that is on the front ."], "output": "[['volume buttons', '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": ["The processor a AMD Semprom at 2.1 ghz is a bummer it does not have the power for HD or heavy computing ."], "output": "[['processor', 'bummer', 'negative'], ['computing', 'heavy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It is easy to use , fast and has great graphics for the money ."], "output": "[['graphics', '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": ["I like how the Mac OS is so simple and easy to use ."], "output": "[['Mac OS', 'like', '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": ["Obviously one of the most important features of any computer is the `` human interface ."], "output": "[['features', 'most important', 'neutral'], ['human interface', 'most important', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["A great feature is the spotlight search : one can search for documents by simply typing a keyword , rather than parsing tens of file folders for a document ."], "output": "[['spotlight search', 'great', 'positive'], ['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 've had to call Apple support to set up my new printer and have had wonderful experiences with helpful , english speaking ( from Vancouver ) techs that walked me through the processes to help me ."], "output": "[['Apple support', 'wonderful', 'positive'], ['techs', '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": ["I need graphic power to run my Adobe Creative apps efficiently ."], "output": "[['graphic power', 'efficiently', 'neutral'], ['Adobe Creative apps', 'efficiently', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 giving them the serial number the first thing I was told , was that it was out of warranty and I could pay to have it repaired ."], "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": ["Laptop was in new condition and operational , but for the audio problem when 1st sent for repair ."], "output": "[['audio', '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 was disappointed when I realized that the keyboard does n't light up on this model ."], "output": "[['keyboard', 'disappointed', 'negative'], ['keyboard', \"does n't light 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": ["It runs perfectly ."], "output": "[['runs', '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": ["Sometimes the screen even goes black on this computer ."], "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": ["Its fast and another thing I like is that it has three USB ports ."], "output": "[['USB ports', '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 salesman talked us into this computer away from another we were looking at and we have had nothing but problems with software problems and just not happy with it ."], "output": "[['software', 'problems', 'negative'], ['software', 'not happy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 system is fixed ."], "output": "[['system', '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": ["I would not recommend this to anyone wanting a notebook expecting the performance of a Desktop it does not meet the expectations ."], "output": "[['performance', '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": ["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": ["It 's super fast and a great value for the price !"], "output": "[['value', 'great', '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": ["It drives me crazy when I want to download a game or something of that nature and I ca n't play it because its not compatable with the software ."], "output": "[['software', 'not compatable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The online tutorial videos make it super easy to learn if you have always used a PC ."], "output": "[['online tutorial videos', 'easy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was very easy to just pick up and use -- It did not take long to get used to the Mac OS ."], "output": "[['Mac OS', 'easy', '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": ["Features like the font are very block-like and old school ."], "output": "[['font', 'block-like', 'negative'], ['font', 'old', 'negative'], ['Features', 'block-like', 'negative'], ['Features', '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": ["It is loaded with programs that is of no good for the average user , that makes it run way to slow ."], "output": "[['programs', 'no good', 'negative'], ['run', '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": ["Now , , , , , my monitor has been acting up for about 2 months ."], "output": "[['monitor', 'acting 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": ["Also , the extended warranty was a problem ."], "output": "[['extended warranty', '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": ["They sent it back with a huge crack in it and it still did n't work ."], "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": ["The size is perfect and I do not recommend anything bigger except for any person who can exceed the limited space it gives you ."], "output": "[['size', 'perfect', 'positive'], ['space', 'limited', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["the mouse buttons are hard to push ."], "output": "[['mouse buttons', '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 price is another driving influence that made me purchase this laptop ."], "output": "[['price', 'driving', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 stamped and not in pieces therefore it is a stronger more resilient frame ."], "output": "[['frame', 'stronger', 'positive'], ['frame', 'resilient', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 like at least a 4 hr . battery life ."], "output": "[['battery life', 'like', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Clear picture on it and everything ."], "output": "[['picture', '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": ["Screen is awesome , battery life is good ."], "output": "[['Screen', 'awesome', 'positive'], ['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": ["Somehow the system clock got messed up after reboot ."], "output": "[['system clock', 'messed 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": ["HP said it was 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": ["I like those programs better than Office and you can save your files to be completely compatible with the Office programs as well ."], "output": "[['programs', 'like', 'positive'], ['programs', 'better', 'positive'], ['Office programs', 'compatible', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 wifi too ."], "output": "[['wifi', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The lcd screen stopped working on mine after 10 months ."], "output": "[['lcd screen', '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": ["We have had numerous problems with Vista , such as Adobe Flash player just quits and has to be uninstalled and then reinsalled , Internet Explore just quits and you lose whatever you were working on , also , the same Windows update has appeared on this computer since we got it and has been updated probably 400 times , the same update ."], "output": "[['Vista', 'problems', 'negative'], ['Adobe Flash player', 'problems', 'negative'], ['Internet Explore', 'problems', 'negative'], ['Windows update', 'problems', 'negative'], ['update', 'problems', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I always have used a tower home PC and jumped to the laptop and have been very satisfied with its performance ."], "output": "[['performance', 'satisfied', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Apple applications ( ex . iPhoto ) are fun , easy , and really cool to use ( unlike the competition ) !"], "output": "[['Apple applications', 'fun', 'positive'], ['Apple applications', 'easy', 'positive'], ['Apple applications', 'cool', 'positive'], ['iPhoto', 'fun', 'positive'], ['iPhoto', 'easy', 'positive'], ['iPhoto', '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": ["First it burned or fused the power adapter plug ."], "output": "[['power adapter plug', 'burned', 'negative'], ['power adapter plug', 'fused', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 still working , but there was nothing on the screen ."], "output": "[['screen', '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": ["Though the picture , video , and music software is nowhere close to professional grade software Im used to ( CS5 ) but does the job for beginner and even intermediate media designers ."], "output": "[['music software', 'nowhere close to professional', 'negative'], ['music software', 'does the job', 'negative'], ['picture', 'nowhere close to professional', 'negative'], ['picture', 'does the job', 'negative'], ['video', 'nowhere close to professional', 'negative'], ['video', 'does the job', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The much lauded combined touch pad and clicker is a nightmare ."], "output": "[['combined touch pad and clicker', '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 Unibody construction is solid , sleek and beautiful ."], "output": "[['Unibody construction', 'solid', 'positive'], ['Unibody construction', 'sleek', 'positive'], ['Unibody construction', '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": ["This MacBook is an outstanding product with great value ."], "output": "[['value', 'outstanding', '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": ["No temporary replacement , they are out of replacements because `` many computers had problems with the Nvidia chipset `` -Inquired status of repair ."], "output": "[['Nvidia chipset', 'problems', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I BOUGHT THIS LAP TOP AND THE CHARGE TIME DOSE N'T LAST AS LONG AS THEY SAY IT WILL MORE LIKE 2 HOURS"], "output": "[['CHARGE TIME', '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 feature are good enough for what I need ."], "output": "[['feature', '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": ["Finally , the biggest problem has been tech support ."], "output": "[['tech support', '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 had been a Windows/Linux user before this ) I love the size because the screen is big enough for what I use it for ( Internet , artwork ) , and yet it is small enough to be reasonably portable ."], "output": "[['size', 'love', 'positive'], ['screen', 'big', 'positive'], ['screen', '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": ["Plain and simple , it ( laptop ) runs great and loads fast ."], "output": "[['runs', 'great', 'positive'], ['loads', '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": ["It was a great laptop , ran great and was really fast ."], "output": "[['ran', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 a lack of screen resolutions !"], "output": "[['screen resolutions', 'problem', 'negative'], ['screen resolutions', '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": ["It is very well built ."], "output": "[['built', '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 design is awesome , quality is unprecedented ."], "output": "[['design', 'awesome', 'positive'], ['quality', 'unprecedented', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 best part is that it even comes with a free printer ( when they have a certain promotion/offer going , of course ) !"], "output": "[['printer', '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": ["it is very easy for anyone to use an apple and specially the mcbook pro notebook ."], "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": ["The touchpad is very intuitive , so much so that I never want to use buttons to click again !"], "output": "[['touchpad', 'intuitive', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["tons of bloatware and junk programs ."], "output": "[['programs', 'junk', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 stand out on this computer is the feel of the keyboard and it 's speed ."], "output": "[['keyboard', 'stand out', 'positive'], ['speed', 'stand out', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delivery was early too ."], "output": "[['Delivery', '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": ["Laptops are usually used on the go , so why not give you a better battery ?"], "output": "[['battery', '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 was n't a big fan of the Netbooks but this one was very well designed ."], "output": "[['designed', 'well', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I still have that stupid bluetooth mouse to !"], "output": "[['bluetooth mouse', 'stupid', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["2nd Best computer in the world only one way this computer might become the best is that it needs to upgreade patches to make less easier for people to hack into"], "output": "[['patches', 'needs to upgreade', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 could be a perfect laptop if it would have faster system memory and its radeon 5850 would have DDR5 instead of DDR3 ."], "output": "[['system memory', 'faster', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I definitely suggest getting an extended warranty , you will probably need it !"], "output": "[['extended warranty', 'suggest', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 wish is the 15 inch MacBook Pro has much better speakers on the side of the keyboard ."], "output": "[['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": ["Keys stick periodically and I havent had the laptop for 45 days yet ."], "output": "[['Keys', 'stick', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 graphics are n't bad at all , for the lower end of the MacBook Pro spectrum , easily capable of running StarCraft II and other games with comparable graphics ."], "output": "[['graphics', \"are n't 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": ["I have Vista , so I am unable to install and uninstall some programs ."], "output": "[['install', '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": ["i am a huge computer person i love anykind of computer that works well , but when i got this one i was so happy with the way it works and how it runs its amazing ."], "output": "[['runs', '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": ["Its white color is stylish for college students and easy to take to carry and take to classes ."], "output": "[['color', '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": ["I took off a star because the machine has a lot of junk software on it ."], "output": "[['software', 'junk', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 great ."], "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": ["I sent it back and found this time that the battery was faulty , so I got a new one and some other fixes they found ."], "output": "[['battery', '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": ["Great pick for portability and affordability ."], "output": "[['portability', 'Great', 'positive'], ['affordability', 'Great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , it 's easy easy easy to set up , easy to hook to my wireless network ."], "output": "[['set up', 'easy easy easy', 'positive'], ['hook to my wireless network', '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 previously purchased a 13 '' macbook ( had pro specs and was aluminum style ) which had a nvidia 9800 ( If I am not mistaken ) and it had major heating issues ."], "output": "[['nvidia 9800', 'issues', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Oh yea , has no numeric pad on the side ."], "output": "[['numeric pad', '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": ["More times that not the screen pops up saying I have a bad internet connection , or the page ca n't be displayed ."], "output": "[['internet connection', '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 ease of use is wonderful ."], "output": "[['use', 'ease', 'positive'], ['use', '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": ["Best thing is I can use existing 32 bit old programs ."], "output": "[['programs', '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 thing I would change about it is the mouse keys ."], "output": "[['mouse keys', 'change', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 that I turned to email in my next vain help to get them to acknowledge that the warranty was still valid ."], "output": "[['warranty', 'valid', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 developed excellent proprietary software for editing video and pictures and I 'm looking forward to utilizing these tools on the regular ."], "output": "[['proprietary software', '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": ["Graphics are clean and sharp , internet interfaces are seamless ."], "output": "[['Graphics', 'clean', 'positive'], ['Graphics', 'sharp', 'positive'], ['internet interfaces', '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": ["But after using it a couple of weeks , the overall operation is poor ."], "output": "[['operation', '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": ["I already have a HP laptop I bought last year that 's standard size ."], "output": "[['size', '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 just plug this into my 22 '' Monitor and the speedy MacOSX performs just as well on this dual-core that my Dell did with Windows 7 with a quad-core ."], "output": "[['MacOSX', 'speedy', 'positive'], ['MacOSX', '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": ["Good monitor and performed well ."], "output": "[['monitor', 'Good', 'positive'], ['performed', '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 mouse pad and buttons are the worst i 've ever seen ."], "output": "[['mouse pad', 'worst', 'negative'], ['buttons', '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": ["It really is perfect for work and play ."], "output": "[['play', 'perfect', 'positive'], ['work', '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": ["Eventually my battery would n't charge , so unless I had it plugged in it would n't even power on ."], "output": "[['battery', \"would n't charge\", 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 first problem was with the pre-loaded Norton Firewall/Security program ."], "output": "[['pre-loaded Norton Firewall/Security program', '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 had a USB connect but , i ca n't use it because it is not compatible ."], "output": "[['USB connect', \"ca n't use\", 'negative'], ['USB connect', 'not compatible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , good quality and good price ."], "output": "[['quality', 'good', 'positive'], ['price', '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": ["After 2 months of complaints , Asus finally sent the right power supply to my techies ."], "output": "[['power supply', 'right', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 included the extra Sony Sonic Stage software , the speakers and the subwoofer I got ( that WAS worth the money ) , the bluetooth mouse for my supposedly bluetooth enabled computer , the extended life battery and the Docking port ."], "output": "[['Sony Sonic Stage software', 'extra', 'neutral'], ['speakers', 'worth', 'positive'], ['subwoofer', '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": ["also the keyboard does not liht up so unless your sitting in a room with some light you cant see anything and thats bad for me because my boyfriend tends to watch tv in the dark at night which leaves me with no way of seeing the keyboard ."], "output": "[['keyboard', '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 agree with the previous comment that ASUS TECH SUPPORT IS HORRIBLE WHICH IS A CON IN MY OPINION ."], "output": "[['ASUS TECH 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": ["I would recommend this computer to anyone searching for the perfect laptop , and the battery life is 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": ["Not easy to carry ."], "output": "[['carry', 'easy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 : I 've had this laptop for 2 months , out of the blue the power adapter stops working ."], "output": "[['power adapter', 'stops 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": ["Of course , for a student , weight is always an issue ."], "output": "[['weight', 'issue', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["2.The wireless card is low quality ."], "output": "[['wireless card', 'low 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": ["They offer the best warranty in the business , and do n't 3rd party it out like Toshiba ."], "output": "[['warranty', '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 problems are the sound isnt very loud I have to wear headphones ."], "output": "[['sound', 'isnt 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": ["There are no viruses or spyware to worry about like on a Windows computer ."], "output": "[['Windows', 'worry about', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 about 8 years ago , I hope that the quality has changed ."], "output": "[['quality', 'hope', 'negative'], ['quality', '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 difference is it 's a whole lot of fun using the laptop now , still learning the Apple navigation , but is fun and comes with a lot of cool apps ."], "output": "[['Apple navigation', 'fun', 'neutral'], ['apps', '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 display is awesome ."], "output": "[['display', '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 speakers on it are useless too ."], "output": "[['speakers', '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": ["In early May I got it back and this time I only had it back for 1 day before it had a NEW issue so it was sent back in for the 6th time they `` expedited '' the repairs so I was only supposed to have to be without it for 3 days and it was supposed to be fixed , by a `` Senior Tech '' ."], "output": "[['Senior Tech', 'supposed to be fixed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Adjust the sensitivity since it 's not that responsive to begin with ."], "output": "[['sensitivity', 'not that responsive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 shift key to go to other lines ."], "output": "[['shift key', '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": ["iLife is easily compatible with Microsoft Office so you can send and receive files from a PC ."], "output": "[['iLife', 'easily 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": ["Fully charged , the MacBook Pro can last about five hours unplugged ."], "output": "[['charged', 'Fully', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 display is exceptional !"], "output": "[['display', '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": ["Your cursor will end up all over the freaking place , , , it 's not uncommon for me to accidentally delete words , sentences , paragraphs because of this mousepad ."], "output": "[['cursor', 'end up', 'negative'], ['cursor', 'freaking', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 I 've fixed the DC jack ( inside the unit ) , rewired the DC jack to the OUTside of the laptop , replaced the power brick ."], "output": "[['DC jack', 'fixed', 'neutral'], ['DC jack', 'rewired', 'neutral'], ['power brick', '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": ["Great product , very easy to use and great graphics ."], "output": "[['graphics', '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 built-in webcam is great for Skype and similar video-chat services ."], "output": "[['built-in webcam', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["THE MOTHERBOARD IS DEAD !"], "output": "[['MOTHERBOARD', 'DEAD', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["This process continued to repeat itself until the mother board had been replaced 4 times and the hard drive replaced 3 times ."], "output": "[['mother board', 'replaced', 'negative'], ['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": ["I could n't believe how long the battery lasted on a single charge ."], "output": "[['battery', 'long', 'positive'], ['charge', 'single', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The backlit keys are wonderful when you are working in the dark ."], "output": "[['backlit keys', '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 most recent being that my Safari internet browser is freaking out on me , but I have just been using firefox instead ."], "output": "[['Safari internet browser', 'freaking 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 DVD drive randomly pops open when it is in my backpack as well , which is annoying ."], "output": "[['DVD drive', 'randomly pops open', 'negative'], ['DVD drive', '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": ["Its also FUN to use !"], "output": "[['use', '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 graphics and screen are stunning and although I was a PC person , I was able to understand how to use a mac fairly quickly ."], "output": "[['graphics', 'stunning', 'positive'], ['screen', 'stunning', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I just took the broken cords into the Apple store and they gave me new ones ."], "output": "[['cords', 'broken', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 gorgeous - yummy good ."], "output": "[['screen', 'gorgeous', '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 Macbook starts fast , does n't crash , has a fantastic display , is small and light ( I have the 13.3 '' model ) , and is n't always complaining about updates , lost connections , errors , blue screens , etc ."], "output": "[['display', 'fantastic', 'positive'], ['starts', '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 guy then said that if I insist on having the hinge tightened , they can do it for me but I have to accept the condition after the `` repair '' ."], "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": ["so in a brief summary i would have to say that i would not recommend dell vostro 1000 to anyone due to it being a down right awful setup so in my opinion you should steer clear of them if you want a decent laptop ."], "output": "[['setup', '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": ["My friend just had to replace his entire motherboard , so did my wife , and it looks like I will have to as well ."], "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": ["First , it does not have a push button to open the lid ."], "output": "[['push button', 'does 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 screen almost looked like a barcode when it froze ."], "output": "[['screen', 'barcode', 'negative'], ['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": ["I love the solid machined aluminum frame , and the keyboard is the best of any laptop I 've used ."], "output": "[['machined aluminum frame', 'love', 'positive'], ['machined aluminum frame', 'solid', 'positive'], ['keyboard', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["You can even run a parallels type program easily and run any leftover PC software that you absolutely can not be without ."], "output": "[['parallels type program', '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 has easy to use features and all the speed and power I could ask for ."], "output": "[['features', 'easy', 'positive'], ['speed', 'easy', 'positive'], ['power', '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 Mac Snow Leopard O/S is extremely easy to use , although very different than Win XP , Visa or Win7 ."], "output": "[['Mac Snow Leopard O/S', 'easy to use', 'positive'], ['Mac Snow Leopard O/S', '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": ["super fast processor and really nice graphics card ..."], "output": "[['processor', 'fast', 'positive'], ['graphics card', '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 dislike the weight and size , cubersome ."], "output": "[['weight', 'dislike', 'negative'], ['weight', 'cubersome', 'negative'], ['size', 'dislike', 'negative'], ['size', 'cubersome', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 but i ca n't give Toshiba any credit for that , unless y'all get serious about ergonomics and making required connections less obtrusive i will be looking to different manufacturer next time ."], "output": "[['windows 7', 'love', 'positive'], ['ergonomics', 'serious', 'negative'], ['connections', 'less obtrusive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 how I recommend it for quality gaming , as I have a desktop rig for that reason ."], "output": "[['gaming', '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": ["Great value , fast delivery -- Computer works as if brand new , no problems , very pleased"], "output": "[['delivery', 'fast', 'positive'], ['delivery', 'pleased', 'positive'], ['value', 'Great', 'positive'], ['value', '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": ["so the fact that the computer does not work on the 24 twenty fourth day is my fault ."], "output": "[['work', 'does 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": ["I would definitely reccomend this if you are in the market for an ease to use , stylish , fun , awesome computer ."], "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": ["The Windows 7 Starter is , in my opinion , a great way to think about using your netbook : basics , basics , basics ."], "output": "[['Windows 7 Starter', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 we exchanged it for the same on and after 2 hours it did n't work ."], "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": ["The OS is still as fast as the day that the laptop was purchased and continues to run flawlessly ."], "output": "[['OS', 'fast', 'positive'], ['run', '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": ["After way too many times sending the thing in for repairs ( delivery service was slow , and without the laptop I had no access to the internet , and thus no way of tracking it to find out when I might hope to see my computer again ) , it finally kicked the bucket after just over 2 years ."], "output": "[['delivery 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 only thing I wish this had was the option to turn off the touchpad with a button like my big 16 '' laptop does ."], "output": "[['touchpad', 'turn 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": ["I especially like the backlit keyboard ."], "output": "[['backlit keyboard', '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 buttons you have to press a little harder than most ."], "output": "[['buttons', 'harder', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , I do n't use my computer for anything like graphics editing and complex data analysis and gaming ."], "output": "[['gaming', \"do n't use\", 'neutral'], ['graphics editing', \"do n't use\", 'neutral'], ['complex data analysis', \"do n't use\", 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 thing I wish it had was a detailed hardcopy manuel ."], "output": "[['hardcopy manuel', 'wish', 'negative'], ['hardcopy manuel', 'detailed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["the mcbook pro notebook will make it easy for you to write and read your emails at blazing speeds ."], "output": "[['speeds', 'easy', 'positive'], ['speeds', '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": ["However , I love this particular Mac because its very fast , great size , and has fantastic features like the lighted keyboard and easy mouse pad ."], "output": "[['size', 'great', 'positive'], ['features', 'fantastic', 'positive'], ['lighted keyboard', 'fantastic', 'positive'], ['mouse pad', 'fantastic', 'positive'], ['mouse pad', '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": ["We paid for the three year warranty and the extended warranty after that one ended as well ."], "output": "[['three year warranty', 'paid for', 'neutral'], ['extended warranty', 'paid for', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["My husband got me this for Chrismas after getting me a very expensive laptop that did not work after 2 days ."], "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 resolution is even higher then any other laptop on the market ."], "output": "[['resolution', 'higher', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["But with A WAY Bigger Screen , and IS able to connect to an HDMI ."], "output": "[['Screen', 'Bigger', 'positive'], ['HDMI', 'able to connect', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 awful and the wireless switch it at the top rather than the side which I am used to it being on the side ."], "output": "[['graphics', '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 speakers are terrible and are probably the cheapest ones I have ever seen in a laptop so if your planning to listen to music I suggest you get something better ."], "output": "[['speakers', 'terrible', 'negative'], ['speakers', 'cheapest', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 no problems with it unlike some hardware defects on past models ."], "output": "[['hardware', 'defects', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 fact that your mac comes fully loaded with all necessary basic programs ."], "output": "[['programs', '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": ["If this is an improvement in Customer Service then I would hate too see what it was before !"], "output": "[['Customer Service', 'improvement', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 I was lucky and a local store was selling them for $ 2000 off and Best Buy matched their price so I was able to buy one for under $ 1000"], "output": "[['price', 'lucky', 'positive'], ['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": ["The layout of the MacBook is horrible and confusing ;"], "output": "[['layout', 'horrible', 'negative'], ['layout', '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": ["Was not happy with one of the programs on it ."], "output": "[['one of the programs', 'not happy', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 one sent : Touchpad did n't work The second sent : USB did n't work The third sent : Touchpad did n't work The fourth sent : Has n't arrived yet ."], "output": "[['Touchpad', \"did n't work\", 'negative'], ['USB', \"did n't work\", 'negative'], ['Touchpad', \"did 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": ["In November my computer messed up entirely and would n't power on after intalling a Windows update , I had to have my HD flashed and lost EVERYTHING on it , including my school assignments and irriplaceable pictures that were only in digital format and several other things , when this update was installed for some reason I was unable to roll back the drivers and everything to an earlier working condition because when the update was installed it deleted my history ."], "output": "[['Windows update', 'messed 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": ["Overall : Poor , Features : Average , Performance : Poor , Battery Life : Excellent , Price -- Value : Poor"], "output": "[['Features', 'Average', 'neutral'], ['Performance', 'Poor', 'negative'], ['Battery Life', 'Excellent', 'positive'], ['Price', 'Poor', 'negative'], ['Value', '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 graphics are stunning ."], "output": "[['graphics', 'stunning', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["( I found a 2GB stick for a bit under $ 50 ) Nice and portable and definitely a decent enough system to keep you entertained while sitting in the airplane for a couple of hours , or at the hotel taking care of some last minute details and documents ."], "output": "[['system', 'Nice', 'positive'], ['system', 'portable', 'positive'], ['system', '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": ["after much effort and 10 days ASUS replaced itThe WiFi is very weak ."], "output": "[['WiFi', 'weak', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 respond immediately ( not like the tired MS applications ) ."], "output": "[['Applications', 'respond immediately', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The only drawback for me is how dirty the screen gets , and rather quickly too ."], "output": "[['screen', 'dirty', 'negative'], ['screen', '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": ["Seems to slow down occassionally but can run many applications ( ie Internet tabs , programs , etc ) simultaneously ."], "output": "[['applications', '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": ["Not to mention sometimes the whole charger unit will decide not to work entirely ."], "output": "[['charger unit', 'not to work entirely', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 other computers that get strong signals that do n't drop in places that this `` net '' book loses its signal ."], "output": "[['signals', 'strong', 'positive'], ['signal', 'loses', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 , in early July of this year , the DVD burner stopped working , and the computer stared having issues with power supply ."], "output": "[['DVD burner', 'stopped working', '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": ["The screen gets smeary and dusty very quickly and it 's very noticeable ."], "output": "[['screen', 'smeary', 'negative'], ['screen', 'dusty', 'negative'], ['screen', 'quickly', 'negative'], ['screen', 'noticeable', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 , before the battery completely died of course , left much to be desired ."], "output": "[['battery life', 'left much to be desired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It had most of the features and all of the power that I wanted to replace my desktop machine ."], "output": "[['features', 'wanted', 'positive'], ['power', 'wanted', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It seemed to be a very nice laptop except I was not able to load my Garmin GPS software or Microsoft Office 2003 ."], "output": "[['Garmin GPS software', 'not able to load', 'negative'], ['Microsoft Office 2003', 'not able to load', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 very much worth the price i paid ."], "output": "[['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": ["This is a great little computer for the 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": ["All apple associates are always willing to help you out with anything , no matter when you purchased the computer and how many years passed ."], "output": "[['apple associates', 'willing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 like to use a different operating system altogether ."], "output": "[['operating system', 'like', 'neutral'], ['operating system', '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": ["Not only was the food outstanding , but the little ' perks ' were great ."], "output": "[['food', 'outstanding', 'positive'], ['perks', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 the best if you like thin crusted pizza ."], "output": "[['pizza', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["Fabulous service , fantastic food , and a chilled out atmosphere and environment ."], "output": "[['service', 'Fabulous', 'positive'], ['food', 'fantastic', 'positive'], ['atmosphere', 'chilled out', 'positive'], ['environment', 'chilled 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": ["Go here for a romantic dinner but not for an all out wow dining experience ."], "output": "[['dinner', 'romantic', 'positive'], ['dining', 'wow', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["Not too crazy about their sake martini ."], "output": "[['sake martini', '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": ["All my co-workers were amazed at how small the dish was ."], "output": "[['dish', 'small', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wait staff is friendly , and the food has gotten better and better !"], "output": "[['wait staff', 'friendly', 'positive'], ['food', 'better', '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": ["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": ["I also ordered for delivery and the restaurant forgot half the order ."], "output": "[['delivery', 'forgot', 'negative'], ['order', '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": ["Overall A oh ya even though there is waiting it is deff worth it"], "output": "[['waiting', '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": ["Service is highly refined : our seating was delayed 35 minutes past our reservation and the maitre d ' apologized and regularly kept us apprised of progress ."], "output": "[['Service', 'refined', 'positive'], ['maitre', 'delayed', 'positive'], ['reservation', 'delayed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 and garlic knots are great as well , I order from them quite often and the delivery is always super quick !"], "output": "[['Pizza', 'great', 'positive'], ['delivery', 'super quick', 'positive'], ['garlic knots', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 great chinese food nearby , you have Wu Liang Ye and Grand Sichuan just a block away ."], "output": "[['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": ["Service could be improved but overall this is a place that understands the importance of little things ( the heavy , black , antique-seeming teapot , for one ) in the restaurant experience ."], "output": "[['Service', 'improved', 'negative'], ['teapot', 'antique-seeming', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 Kruno , the beverage manager is the best bartender I have yet to come across ."], "output": "[['bartender', 'best', 'positive'], ['beverage manager', '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 understand the area and folks you need not come here for the romantic , alluring ambiance or the five star service featuring a sommlier and a complicated maze of captain and back waiters - you come for the authentic foods , the tastes , the experiance ."], "output": "[['ambiance', 'romantic', 'positive'], ['ambiance', 'alluring', 'positive'], ['service', 'five star', 'positive'], ['foods', 'authentic', 'positive'], ['captain', 'complicated maze', 'positive'], ['back waiters', 'complicated maze', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["Succulent steaks cooked precisely to your desired 'doneness ' accompanied by salads and sides that do n't look like leafy road kill ."], "output": "[['steaks', 'desired', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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'], ['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": ["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": ["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": ["The food was just awful , ATROCIOUS actually ."], "output": "[['food', 'awful', 'negative'], ['food', 'ATROCIOUS', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 plain pizza with fresh garlic or eggplant ."], "output": "[['plain pizza', 'Try', 'positive'], ['garlic', '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 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 recently went to this restaurant with some co-workers for lunch and had an amazing time ."], "output": "[['lunch', '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": ["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 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": ["The service , wine selection , ambiance are all outstanding and deserve recognition ."], "output": "[['service', 'outstanding', 'positive'], ['wine selection', 'outstanding', 'positive'], ['ambiance', '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": ["It 's really also the service , is good and the waiters are friendly ."], "output": "[['service', 'good', 'positive'], ['waiters', 'friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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'], ['hollondaise sauce', 'failed', 'negative'], ['brunch', 'worst', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 really good , I had the onion soup and it was one of the best ever ."], "output": "[['food', 'good', 'positive'], ['onion soup', '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 thing I moderately enjoyed was their Grilled Chicken special with Edamame Puree ."], "output": "[['Grilled Chicken special with Edamame Puree', 'enjoyed', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 tasty , but I suggest only eating one with meat because they tend not to mesh that well with the average American digestive system ."], "output": "[['meat', 'tasty', 'neutral'], ['meat', 'suggest', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["The atmosphere is great if your looking for a laid back scene and an inexpensive way to spend a weekend afternoon ."], "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 had the salmon dish and while it was fine , for the price paid , I expected it to have some type of flavor ."], "output": "[['flavor', 'fine', 'negative'], ['price', 'fine', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Especially liked chicken tikka and the naan , and the dals ."], "output": "[['chicken tikka', 'liked', 'positive'], ['naan', 'liked', 'positive'], ['dals', '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 restaurant looks out over beautiful green lawns to the Hudson River and the Statue of Liberty ."], "output": "[['lawns', '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 overall price tag was very very expensive , something I did expect ."], "output": "[['price tag', '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": ["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": ["Its a great place for a casual date or to entertain clients for lunch ."], "output": "[['lunch', '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": ["Plain and simple it 's bad thai food ."], "output": "[['thai 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": ["While certain staples are excellent ( the burger , some of the pastas ) , the food is not really the point ."], "output": "[['burger', 'excellent', 'positive'], ['pastas', 'excellent', 'positive'], ['food', 'not really the point', 'neutral'], ['staples', '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": ["good music , great food , speedy service affordable prices ."], "output": "[['music', 'good', 'positive'], ['food', 'great', 'positive'], ['service', 'speedy', '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": ["The sides were ok and incredibly salty ."], "output": "[['sides', 'ok', 'negative'], ['sides', '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": ["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": ["I must say the view of NYC is so beautiful !"], "output": "[['view', '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": ["Otherwise , this place has great service and prices and a nice friendly atmosphere ."], "output": "[['service', 'great', 'positive'], ['prices', 'great', 'positive'], ['atmosphere', 'nice 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 desserts are more appealing then stuffy overpriced French restaurants ."], "output": "[['desserts', 'appealing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["The atmosphere is noisy and the waiters are literally walking around doing things as fast as they can ."], "output": "[['atmosphere', '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": ["Pastrami or corned beef are juicy and piled high ( ask for extra rye bread ) ."], "output": "[['Pastrami or corned beef', 'juicy', 'positive'], ['Pastrami or corned beef', '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": ["( $ 200 for 2 glasses of champagne , not too expensive bottle of wine and 2 after dinner drinks ) ."], "output": "[['glasses of champagne', 'not too expensive', 'negative'], ['bottle of wine', 'not 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": ["otherwise , good stuff for late nite eats ."], "output": "[['stuff', 'good', 'positive'], ['eats', 'late', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["All the food was hot tasty ."], "output": "[['food', 'hot 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": ["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 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": ["The menu was impressive with selections ranging from a burger , to steak , to escargot ."], "output": "[['menu', 'impressive', 'positive'], ['burger', 'impressive', 'neutral'], ['steak', 'impressive', 'neutral'], ['escargot', 'impressive', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 higher to dine in and their chicken tikka marsala is quite good ."], "output": "[['Prices', 'higher', 'negative'], ['chicken tikka marsala', '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 photos of the restaurant in its web site are way better than the real look ."], "output": "[['look', '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 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": ["But the coconut rice was good ."], "output": "[['coconut 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": ["All of my co-workers stated that the food was amazing and wondered why they had n't heard about this place ."], "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": ["Friendly staff that actually lets you enjoy your meal and the company you 're with ."], "output": "[['staff', 'Friendly', 'positive'], ['meal', '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 appetizing is excellent - just as good as Zabars Barney Greengrass at a reasonable price ( if bought by the pound ) ."], "output": "[['appetizing', 'excellent', '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": ["First , the waiter who served us neglected to fill us in on the specials , which I would have chosen had I known about them ."], "output": "[['waiter', 'neglected', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 food and they have REAL service , not just the rush you get sometimes when they try to push you out the door ."], "output": "[['food', 'Authentic', 'positive'], ['service', '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": ["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": ["Prices are in line ."], "output": "[['Prices', 'in line', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 prepared quickly and efficiently ."], "output": "[['food', 'quickly', 'positive'], ['food', '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": ["While this is n't classical restaurant fare , the chef has given new life to an old cuisine with some really innovative and tasty dishes that are genuinely Indian without being heavy or same old restaurant burn-outs ."], "output": "[['dishes', 'innovative', 'positive'], ['dishes', 'tasty', 'positive'], ['cuisine', 'old', 'neutral'], ['Indian', 'genuinely', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 romantic place for a date ( try to get the corner booth table for a little privacy and to sit close ! ) ."], "output": "[['corner booth table', 'privacy', 'positive'], ['place', 'Great 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": ["We were fans of the half-price Saturday night option until some inedible squid during a recent visit ."], "output": "[['squid', 'inedible', 'negative'], ['half-price Saturday night option', 'fans', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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'], ['lamb sausages', 'tasty', 'positive'], ['lamb sausages', 'fresh', 'positive'], ['sardines with biscuits', 'tasty', 'positive'], ['sardines with biscuits', 'fresh', 'positive'], ['large whole shrimp', 'large', '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 had to share my table with a loud group of kids and the service was rude an unattentive ."], "output": "[['service', 'rude', 'negative'], ['service', 'unattentive', 'negative'], ['table', '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 '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": ["It is kinda nosiy and the tables are close together but it 's still a beautiful place to enjoy a nice dinner ."], "output": "[['tables', 'close', 'negative'], ['dinner', 'nice', '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": ["The Pastrami sandwich was like buttah and with pickles and an icy cold beer to wash it down , it was a pleasurable experience ."], "output": "[['Pastrami sandwich', 'pleasurable', 'positive'], ['beer', 'icy cold', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["I was pretty much full after our fondue appetizer ."], "output": "[['fondue appetizer', 'full', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["Drawbacks : service is slow and they do n't toast !"], "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 spicy tuna and salmon are the best we 've ever had ."], "output": "[['spicy tuna', 'best', 'positive'], ['salmon', '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": ["Even though its good seafood , the prices are too high ."], "output": "[['seafood', 'good', 'positive'], ['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": ["Meat dishes now adorn the selections , although there 's still a large number of vegetarian-friendly choices ."], "output": "[['vegetarian-friendly choices', '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": ["Reasonable prices ."], "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 dim sum servings here are a bit larger than I 'm used to ."], "output": "[['dim sum servings', '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": ["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'], ['clubhouse', 'fabulous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 tiem watching the shows and characters and ar food was just what we were looking for ."], "output": "[['shows', 'great', 'positive'], ['food', 'looking for', 'positive'], ['characters', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["The noodle and rices dishes taste great ."], "output": "[['noodle and rices 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 '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": ["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'], ['quality', 'poor', 'negative'], ['cooked', 'badly', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 they keep the capex to a minimum , they do put some cash into the bagels , because they among the best in the city ."], "output": "[['bagels', '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": ["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": ["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 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": ["THE FOOD PORTIONS ARE REALLY LARGE ."], "output": "[['FOOD 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": ["It looked like shredded cheese partly done - still in strips ."], "output": "[['shredded cheese', 'partly done', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 better enjoyed humble root vegetables or a mushroom consomme - and this chef accomplishes without fats ."], "output": "[['root vegetables', 'better enjoyed', 'positive'], ['mushroom consomme', 'better 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": ["If you go to Roth 's try to be served by Mike , he is GREAT ! !"], "output": "[['served', 'GREAT !', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 ! ! ! !"], "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": ["Interesting selection , good wines , service fine , fun decor ."], "output": "[['wines', 'good', 'positive'], ['service', 'fine', 'positive'], ['decor', '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 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": ["The food is great and they have a good selecion of wines at reasonable prices ."], "output": "[['food', 'great', 'positive'], ['selecion of wines', '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": ["I could n't reccommend their Godmother pizza any higher ."], "output": "[['Godmother pizza', 'reccommend', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["Decor is minimalist and clean - nothing to distract or commend ."], "output": "[['Decor', 'minimalist', 'neutral'], ['Decor', 'clean', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 in the restaurant were pretty obnoxious and loud ."], "output": "[['people', 'obnoxious', 'negative'], ['people', '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": ["Price no more than a Jersey deli but way better ."], "output": "[['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": ["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": ["The drinks are always well made and wine selection is fairly priced ."], "output": "[['drinks', 'well made', 'positive'], ['wine selection', 'fairly priced', 'neutral'], ['priced', 'fairly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 but tasty ."], "output": "[['Food', 'average', '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": ["Admittedly some nights inside the restaurant were rather warm , but the open kitchen is part of the charm ."], "output": "[['open kitchen', 'charm', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["Worse of all , $ 60 was erroneously added to our $ 80 bill ."], "output": "[['bill', 'erroneously', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["It was nice and fresh , but I ca n't give it high scores on being authentic thai ."], "output": "[['thai', '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 , and the complimentary pudding dessert was just enough - yummy !"], "output": "[['pudding dessert', 'enough', 'positive'], ['pudding dessert', '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": ["It saves walking in and waiting for a table in the often noisy , crowded bar at dinnertime ."], "output": "[['bar', 'noisy', 'negative'], ['bar', 'crowded', 'negative'], ['waiting', 'saves', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": "[['goat cheese', 'delicious', 'positive'], ['panchetta', 'delicious', 'positive'], ['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": ["Disappointing food , lousy service ."], "output": "[['food', 'Disappointing', 'negative'], ['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": ["Over price , and small portions ."], "output": "[['price', 'Over', '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": ["My husband said the portions were very small , but if my main course was good to eat the portion would 've been fine for me ."], "output": "[['portions', 'small', 'negative'], ['main course', '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": ["Because we did n't have a reservation , we could only sit in the back garden , but it was great , secluded and perfect in nice weather ."], "output": "[['back garden', 'great', 'positive'], ['back garden', 'secluded', 'positive'], ['back garden', '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": ["Stuffing yourself with Japanese food is a rare thing ."], "output": "[['Japanese food', 'rare', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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 all you can eat deal is truly amazing here ."], "output": "[['all you can eat deal', '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 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": ["They have it all -- great price , food , and service ."], "output": "[['price', 'great', 'positive'], ['food', 'great', 'positive'], ['service', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food was amazing , the service was so attentive and personable , and how about that ambience !"], "output": "[['food', 'amazing', 'positive'], ['service', 'attentive', '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": ["This place has the best interior I have seen anywhere in the northside of W'burg , and will impress whoever you bring there ."], "output": "[['interior', 'best', 'positive'], ['place', 'impress', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 variety of the sashimi plate to be satisfying - fresh and yummy ."], "output": "[['sashimi plate', 'satisfying', 'positive'], ['sashimi plate', 'fresh', 'positive'], ['sashimi plate', '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": ["Dahkin also offers prix fixe lunch and buffet ."], "output": "[['prix fixe lunch', 'prix', 'positive'], ['buffet', 'prix', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service , however , was a bright flower in a garden ."], "output": "[['service', 'bright', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Tried the pad see ew on the recommendation of the last reviewer since it 's one of my favorite dishes ."], "output": "[['pad see ew', 'Tried', 'neutral'], ['pad see ew', 'favorite', 'neutral'], ['dishes', '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 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": ["The lunch special is an absolute steal ."], "output": "[['lunch special', 'steal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": "[['The 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": ["She gets 10 for her excellent service and advice ."], "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": ["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']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["Apparently , the good cook works then ."], "output": "[['cook', '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 steak au poivre was one of the worst I 've had ."], "output": "[['steak au poivre', '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": ["Although the tables may be closely situated , the candle-light , food-quality and service overcompensate ."], "output": "[['candle-light', 'closely situated', 'positive'], ['food-quality', '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": ["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": ["Service was excellent , and the AC worked very well too ( thank God , it was hot ! ) ."], "output": "[['Service', 'excellent', 'positive'], ['AC', '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": ["My friend ordered some of their special sushi rolls which had excellent presentation and tasted great !"], "output": "[['sushi rolls', 'special', 'positive'], ['sushi rolls', 'excellent', 'positive'], ['sushi rolls', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 be warned their dinner menu to sit and take out prices are different ."], "output": "[['prices', 'different', 'neutral'], ['dinner menu to sit', 'warned', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 celebrate a birthday , three of us went to Mare anticipating great food ."], "output": "[['food', '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 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'], ['appetizer', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 staff ."], "output": "[['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": ["To finish off such a delightful dinner experience you must have dessert , especially the White Chocolate Bread Pudding with Gelato and hot chocolate ."], "output": "[['dinner', '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": ["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": ["Great food and the prices are very reasonable ."], "output": "[['food', 'Great', 'positive'], ['prices', 'reasonable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food ( spinach and corn dumplings and massamman curry ) , very friendly and no nonsense service and a clean and funky bathroom ."], "output": "[['food', 'Great', 'positive'], ['spinach and corn dumplings', 'Great', 'positive'], ['service', 'friendly', 'positive'], ['service', 'nonsense', 'positive'], ['bathroom', 'clean', 'positive'], ['bathroom', 'funky', 'positive'], ['massamman curry', '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": ["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": ["If you love seafood , you would love this place !"], "output": "[['seafood', 'love', 'positive'], ['place', 'love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["They charge different prices all the time ."], "output": "[['prices', 'different', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 terms of the food itself -- nothing special , we limited ourselves to several appetizers ."], "output": "[['food', 'nothing special', 'neutral'], ['appetizers', 'limited', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 dress codes , no attitudes , plenty of comfort companionship , a great place to relax in an always busy Midtown ."], "output": "[['dress codes', 'No', 'positive'], ['attitudes', 'no', '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": ["They have a huge selection of different cream cheeses and all of their salads are great ."], "output": "[['cream cheeses', 'huge', 'positive'], ['cream cheeses', 'different', 'positive'], ['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": ["I ordered a Chicken Teriyaki dish and found that the chicken was extremely dry ."], "output": "[['Chicken Teriyaki dish', 'dry', 'negative'], ['chicken', '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": ["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": ["So , a little inconsistency there but either way , both pizzas were really good ."], "output": "[['pizzas', '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 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": ["These innovators of french indian fusion do a great job of making dishes as interesting as possible while still being accessible ."], "output": "[['french indian fusion', 'great', 'positive'], ['dishes', 'interesting', 'positive'], ['dishes', 'accessible', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["night without a reservation , we had to wait at the bar for a little while , but the manager was so nice and made our wait a great experience ."], "output": "[['manager', '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": ["You rarely have to wait for a seat and the currys ( masaman , green , red ) are full of flavor and come super spicy if you ask for it ."], "output": "[['seat', 'rarely', 'positive'], ['currys ( masaman , green , red )', '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 bar is very well stocked with interesting beers and well priced wines ."], "output": "[['bar', 'well stocked', 'positive'], ['beers', 'interesting', 'positive'], ['wines', '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": ["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": ["I have enjoyed everything I have ever gotten and the fish is so fresh and always prepared in a great way ."], "output": "[['fish', 'fresh', '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": ["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": ["I could have drank 4 glasses of water and still been parched - so watch out ."], "output": "[['glasses of water', 'parched', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["They forgot a sandwich , did n't include plastic forks , and did n't include pita with the hummus platter ."], "output": "[['sandwich', 'forgot', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 Prix Fixe , so be prepared to spend at least $ 60 per person , but it is Well worth it superb food ."], "output": "[['menu', 'Well worth', 'negative'], ['food', 'superb', 'positive'], ['Prix Fixe', 'Well 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": ["We had the most wonderful waitress ."], "output": "[['waitress', '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": ["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": ["The blond wood decor is very soothing , the premium sake is excellent and the service is great ."], "output": "[['blond wood decor', 'soothing', 'positive'], ['sake', 'excellent', '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": ["Your money could easily be better spent elsewhere ( Anywhere ) ."], "output": "[['money', '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": ["Try the Pad Se-Ew or Chicken with Cashew Nuts for a memorable and repeatable experience ."], "output": "[['Pad Se-Ew', 'Try', 'positive'], ['Pad Se-Ew', 'memorable', 'positive'], ['Pad Se-Ew', 'repeatable', 'positive'], ['Chicken with Cashew Nuts', 'Try', 'positive'], ['Chicken with Cashew Nuts', 'memorable', 'positive'], ['Chicken with Cashew Nuts', 'repeatable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 O.K . pizza ."], "output": "[['pizza', 'O.K .', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 did n't like was how the food came right after it was ordered ."], "output": "[['food', \"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": ["The best part of the experience was knowing that the manager ( a bubbly , friendly young woman with a great smile ) truly cared about how we were doing ."], "output": "[['manager', 'bubbly', 'positive'], ['manager', 'friendly 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": ["one of the best Chicken Tikka Masala ."], "output": "[['Chicken Tikka Masala', '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 corned beef and pastrami are excellent , much less fatty than those big tourist places around Times Square ."], "output": "[['corned beef', 'excellent', 'positive'], ['corned beef', 'less fatty', 'positive'], ['pastrami', 'excellent', 'positive'], ['pastrami', 'less fatty', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["If you 've ever been along the river in Weehawken you have an idea of the top of view the chart house has to offer ."], "output": "[['view', '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": ["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": ["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": ["The food was just OK , I would never go back ."], "output": "[['food', 'OK', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Ummm ... the beer was cold ."], "output": "[['beer', 'cold', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 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": ["We ordered the chicken casserole , but what we got were a few small pieces of chicken , all dark meat and on the bone ."], "output": "[['chicken', 'few', 'negative'], ['meat', '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": ["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": ["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": ["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'], ['Italian cheese', 'nice', 'positive'], ['Italian cheese', '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": ["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": ["Incredible food at a very agreeable price brings me back just about every other day to this authentic Thai restaurant ."], "output": "[['food', 'Incredible', 'positive'], ['price', 'agreeable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 the worst dining experience I 've ever had ."], "output": "[['dining experience', 'worst', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["The bread is the soft paratha bread ( unlike the plain bread they use in Calcutta ) , and the stuffing is tandoori styled and very flavorful ."], "output": "[['paratha bread', 'soft', 'positive'], ['bread', 'plain', 'negative'], ['stuffing', 'styled', 'positive'], ['stuffing', 'flavorful', 'positive'], ['tandoori', 'styled', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 average , and I would say even the chain restaurant Baluchi 's tastes better ."], "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": ["The place is small and cramped but the food is fantastic ."], "output": "[['place', 'small', 'negative'], ['place', 'cramped', 'negative'], ['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 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": ["The bartender on my most recent visit was so incredibly rude that I will never go back ."], "output": "[['bartender', '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": ["you can actually get 2 salads worth if u take it home and add it to some lettuce !"], "output": "[['salads', '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 ambience is very romantic and definitely a good place to bring a date ."], "output": "[['ambience', 'romantic', 'positive'], ['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": ["It is far more popular as a bar than as a restaurant , with only a few tables and the waiter being the bartender , but we greatly enjoyed the unobtrusive atmosphere ."], "output": "[['bar', 'popular', 'positive'], ['tables', 'few', 'negative'], ['atmosphere', 'enjoyed', 'positive'], ['atmosphere', '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": ["There are much better places in NY with better prices ."], "output": "[['prices', '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 ambience is very calm and quiet ."], "output": "[['ambience', '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": ["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": ["Considering their price of $ 6.25 for lunch special , the dish was ridiculously small ."], "output": "[['dish', 'ridiculously 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 was pretty traditional but it was hot and good with large portions ."], "output": "[['food', 'traditional', 'positive'], ['food', 'hot', 'positive'], ['food', 'good', '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": ["They were very abrupt with me when I called and actually claimed the food was late because they were out of rice ."], "output": "[['food', 'late', 'negative'], ['rice', '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": ["Service is extraordinary , yet not overbearing , and the decor brings a taste of trendy SoHo into Queens ."], "output": "[['Service', 'extraordinary', 'positive'], ['Service', 'not overbearing', 'positive'], ['decor', 'trendy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["Their sake martini is wonderful ."], "output": "[['sake martini', '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 service is friendly , if not the most prompt in the world , the food is great , and the prices , while not cheap , wo n't put your wallet out of commission ."], "output": "[['service', 'friendly', '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": ["Best drumsticks over rice and sour spicy soup in town !"], "output": "[['drumsticks over rice', 'Best', 'positive'], ['sour spicy soup', '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 it all comes at a very reasonable price ( congee , noodles , and rice dishes are no more than $ 3-6 each ) ."], "output": "[['price', 'reasonable', 'positive'], ['congee', 'reasonable', 'neutral'], ['noodles', 'reasonable', 'neutral'], ['rice dishes', '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": ["Overall I was impressed and will return , it 's a great QPR ( Quality to Price Ratio ) ."], "output": "[['Price', 'great', 'positive'], ['Quality', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["Unlike HH up the block , this place actually gives you hearty and hot bagels this town is known for ."], "output": "[['bagels', 'hearty', 'positive'], ['bagels', '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": ["What generous portions !"], "output": "[['portions', 'generous', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["So , the menu is written in chalk above your head and it all sounds delicious ."], "output": "[['menu', '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": ["I have been there many times , and food is good and consistent ."], "output": "[['food', 'good', 'positive'], ['food', '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": ["The meat dishes were only so-so ."], "output": "[['meat dishes', '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 menu consisted of standard brassiere food , better then places like Balthazar etc ."], "output": "[['brassiere food', 'standard', 'positive'], ['brassiere 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": ["The service is always bad though , do n't expect much of anything from your server , and I would not recommend bringing a date here either ."], "output": "[['service', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sushi is also great !"], "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": ["From the complimentary chef app of a delicate butternut squash ravioli in a delicious truffle sauce to an amazing buttery and tender langostine entree to a dessert that I ca n't remember because of the fabulous Cakebread Cabernet we were drinking -- the whole evening was amazing ."], "output": "[['chef app', 'complimentary', 'positive'], ['delicate butternut squash ravioli in a delicious truffle sauce', 'delicate', 'positive'], ['buttery and tender langostine entree', 'amazing', 'positive'], ['Cakebread Cabernet', '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": ["The makhani was OK -- the korma was bland ."], "output": "[['makhani', 'OK', 'neutral'], ['korma', '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": ["Service was very 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": ["We actually left hungry and went across the street to Wo Hop at 15 Mott street for some good chinese food ."], "output": "[['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": ["I have known about this secret for the last 13 years , Emilio ( the Godfather ) has continued to serve food and wine for the gods at mortal prices ."], "output": "[['prices', 'mortal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 bill was outrageous ."], "output": "[['bill', 'outrageous', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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": ["It was like the servers forgot that they actually worked there and instead wanted to hang out and be cool ."], "output": "[['servers', '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": ["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": ["This restaurant is a wonderful place to go many times and it is reasonably priced ."], "output": "[['priced', 'reasonably', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Went on a 3 day oyster binge , with Fish bringing up the closing , and I am so glad this was the place it O trip ended , because it was so great !"], "output": "[['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": ["If you are looking for a good quality , cheap eats - this is the place ."], "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": ["Never in my life did I think that I could be satisfied both in taste and in quantity for $ 3.00 in NYC ."], "output": "[['taste', 'satisfied', '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 main course had an average portion , and was decent overall ."], "output": "[['main course', 'decent', 'positive'], ['portion', '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": ["20 minutes for our reservation but it gave us time to have a few cocktails and enjoy our surroundings and each other ."], "output": "[['surroundings', '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": ["Waitstaff is great , very attentive ."], "output": "[['Waitstaff', 'great', 'positive'], ['Waitstaff', '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": ["Coming from Boston this place is like Emma 's Pizza in Kendall Square in Cambridge ( although they have more funky toppings ! )"], "output": "[['toppings', 'funky', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 nice but when we order our drink we were in for a surprise ."], "output": "[['space', 'nice', 'positive'], ['drink', 'surprise', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 very reasonable ."], "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": ["The waiters are sweet , the food is tasty and the bill is never too large ."], "output": "[['waiters', 'sweet', 'positive'], ['food', 'tasty', 'positive'], ['bill', 'never too 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 flavors robust and subtle ."], "output": "[['flavors', 'robust', 'positive'], ['flavors', '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": ["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": ["Oh , but wait , we were out of drinks ( which were also delightfully overpriced ) ."], "output": "[['drinks', '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 service is fantastic ."], "output": "[['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": ["The garlic mashed potatoes are hands down the best in the city !"], "output": "[['garlic mashed potatoes', '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 meat was under-cooked and EXTRMELY CHEWY ."], "output": "[['lamb meat', '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": ["Over time , the food quality has decreased substantially , it is a lot less crowded than it used to , and the service must definitely be part of the reason ."], "output": "[['food quality', 'decreased', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Killer Sushi !"], "output": "[['Sushi', 'Killer', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Plus they made a perfect martini ."], "output": "[['martini', '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": ["Furthermore , the rice had no seasoning , so the sushi was bland and disgusting ."], "output": "[['rice', 'no seasoning', 'negative'], ['sushi', 'bland', 'negative'], ['sushi', 'disgusting', 'negative'], ['seasoning', '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": ["Winnie and her staff are the best crew you can find serving you ."], "output": "[['crew', 'best', 'positive'], ['staff', '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 it is n't for the food ( A+++ ) , it must be the service or the ambience ."], "output": "[['food', '( A+++ )', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["$ 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": ["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": ["Seating is ok even though sometimes there 's alot of people ."], "output": "[['Seating', '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": ["As a long-time patron of Mamoun 's , I always figured that I had found the best late night food spot in the city ."], "output": "[['food spot', '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 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": ["Yeah , sometimes the service can be 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 service was attentive without being overbearing and each dish we tried was wonderful from the spring rolls to the cod with pineapple tempura ."], "output": "[['service', 'attentive without being overbearing', 'positive'], ['dish', 'wonderful', 'positive'], ['spring rolls', 'wonderful', 'positive'], ['cod with pineapple tempura', '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 would not have been so disappointed with the portions if the qualities were good enough to make up for it , but they were not !"], "output": "[['portions', 'disappointed', 'negative'], ['qualities', '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": ["All the desserts the group tried got favorable reviews ."], "output": "[['desserts', 'favorable', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["When I saw that their website had a link to da Ciro in Napoli , I knew there was going to be 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": ["And their prices are very high - they actually think that they can get away with charging such prices for such terrible food and service !"], "output": "[['prices', 'high', 'negative'], ['food', 'terrible', 'negative'], ['service', 'terrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great spot , whether looking for a couple of drinks or quiet dinner ."], "output": "[['dinner', 'quiet', 'positive'], ['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": ["Just stick with the small dishes !"], "output": "[['dishes', '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": ["both are very reasonably priced ( around $ 8 for dinner and $ 5 for lunch ) , and are delicious and filling ."], "output": "[['priced', 'reasonably', 'positive'], ['dinner', 'delicious', 'positive'], ['dinner', 'filling', 'positive'], ['lunch', 'delicious', 'positive'], ['lunch', '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": ["My boyfriend ate tuna and it was cooked perfectly !"], "output": "[['tuna', '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": ["great eats , good times ."], "output": "[['eats', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 , the atmosphere was relaxed , and we have now adopted Plate 347 as our Secret on Second !"], "output": "[['food', 'delicious', '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": ["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": ["great food , lt 's of it , more then one person can eat !"], "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": ["Really tasty spring rolls and noodles for a good price though ."], "output": "[['spring rolls', 'tasty', 'positive'], ['noodles', 'tasty', '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": ["Little Tonino 's is just awesome , our favorite delivery place in Kennsington , honestly the best Gnochi I have ever had !"], "output": "[['Gnochi', '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": ["INCREDIBLY POOR SERVICE AN FOOD QUALITY AT EXORBITANT PRICES ."], "output": "[['SERVICE', 'POOR', 'negative'], ['FOOD QUALITY', 'POOR', 'negative'], ['PRICES', 'EXORBITANT', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I have been about 4 times and have always had a great meal ."], "output": "[['meal', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wine and cheese plate are plentiful and ca n't wait to try the fondue or table grilling ."], "output": "[['wine', 'plentiful', 'positive'], ['cheese', '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 BIG COMPLAINT : NO TOASTING AVAILABLE ."], "output": "[['TOASTING', '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": ["No you 're going to go back because 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 fish is fresh and each piece is sliced to perfection and seasoned by the sushi chef ( usually with a little fresh wasabi and soy sauce but also sometimes with some sea salt ) ."], "output": "[['fish', 'fresh', 'positive'], ['sushi chef', 'seasoned', 'positive'], ['wasabi', '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": ["Veal Parmigana - Better than Patsy 's !"], "output": "[['Veal Parmigana', '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": ["Went to Ottimo and was expecting outstanding pizza ( as I love La Pizza Fresca ) ."], "output": "[['pizza', '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": ["Our tiny table for two ( dinner plates hung over edge ) was right in the middle of one of the lanes of waiter traffic ."], "output": "[['table', '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": ["Sake collection was excellent ( Try Nanbu Bijin ) , but pricey ."], "output": "[['Nanbu Bijin', '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": ["A wonderful place !"], "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": ["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', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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 ordered two hot dogs thinking they would be pretty good since there is a whole section on the menu devoted to them ."], "output": "[['hot dogs', '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": ["If you like the food and the value you get from some of Chinatown restaurants , this is not the place for you ."], "output": "[['food', 'like', 'neutral'], ['value', 'like', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The restaraurant is very small so reservations are a must ."], "output": "[['reservations', '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": ["The service was typical short-order , dinner type ."], "output": "[['service', '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 is very average ... the Thai fusion stuff is a bit too sweet , every thing they serve is too sweet here ."], "output": "[['food', 'average', 'negative'], ['Thai fusion stuff', 'too sweet', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The 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": ["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": ["we love th pink pony ."], "output": "[['pink pony', '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 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": ["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": ["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": ["i happen to have a policy that goes along with a little bit of self-respect , which includes not letting a waiter intimidate me , i.e . make me feel bad asking for trivialities like water , or the check ."], "output": "[['waiter', '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 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 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": ["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": ["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": ["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']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["This place is the most Japanese it can ever get ."], "output": "[['place', '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": ["Leon is an East Village gem : casual but hip , with well prepared basic French bistro fare , good specials , a warm and lively atmosphere ."], "output": "[['Leon', 'casual', 'positive'], ['Leon', 'hip', 'positive'], ['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 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": ["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', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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 cramped but the food is fantastic ."], "output": "[['place', 'small', 'negative'], ['place', 'cramped', 'negative'], ['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": ["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": ["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": ["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": ["Service is not exactly five star , but thats not really a big deal ."], "output": "[['Service', 'not exactly 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": ["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": ["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": ["The pizza is delicious - they use fresh mozzarella instead of the cheap , frozen , shredded cheese common to most pizzaria 's ."], "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": ["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": ["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": ["My husband and I thougt it would be great to go to the Jekyll and Hyde Pub for our anniversary , and to our surprise it was fantastic ."], "output": "[['Jekyll and Hyde Pub', 'great', 'positive'], ['Jekyll and Hyde Pub', '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 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": ["I have to highly recommend the lobster roll - not to much mayo ; you can tell it was a fresh lobster ."], "output": "[['lobster roll', 'recommend', 'positive'], ['lobster', '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 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": ["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 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 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["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": ["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": ["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 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": ["Great staff ."], "output": "[['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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["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": ["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": ["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 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": ["Nice Family owned traditional restaurant ."], "output": "[['restaurant', '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": ["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": ["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": ["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": ["I had a huge pastrami sandwich on a roll ."], "output": "[['pastrami sandwich on a roll', '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": ["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": ["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": ["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 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": ["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": ["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": ["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 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": ["While their kitchen food is delicious , their Sushi is out of this world ."], "output": "[['kitchen food', 'delicious', 'positive'], ['Sushi', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["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": ["Authentic Taiwanese food that 's cheap ... what more could you ask for ?"], "output": "[['Taiwanese food', 'Authentic', 'positive'], ['Taiwanese food', 'cheap', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["My friend devoured her chicken and mashed potatos ."], "output": "[['chicken and mashed potatos', 'devoured', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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": ["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": ["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 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": ["The fish was adequate , but inexpertly sliced ."], "output": "[['fish', 'adequate', 'negative'], ['fish', 'inexpertly sliced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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": ["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": ["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": ["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 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', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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": ["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": ["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": ["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": ["Drawbacks : service is slow and they do n't toast !"], "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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["Best drumsticks over rice and sour spicy soup in town !"], "output": "[['drumsticks over rice', 'Best', 'positive'], ['sour spicy soup', '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": ["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": ["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": ["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": ["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": ["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": ["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": ["$ 20 for all you can eat sushi can not be beaten ."], "output": "[['all you can eat sushi', '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": ["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": ["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": ["The food is very average ... the Thai fusion stuff is a bit too sweet , every thing they serve is too sweet here ."], "output": "[['food', 'average', 'negative'], ['Thai fusion stuff', '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": ["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": ["we love th pink pony ."], "output": "[['pink pony', '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 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": ["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": ["i happen to have a policy that goes along with a little bit of self-respect , which includes not letting a waiter intimidate me , i.e . make me feel bad asking for trivialities like water , or the check ."], "output": "[['waiter', '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 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 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": ["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": ["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": ["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']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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": ["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": ["This place is the most Japanese it can ever get ."], "output": "[['place', '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": ["Leon is an East Village gem : casual but hip , with well prepared basic French bistro fare , good specials , a warm and lively atmosphere ."], "output": "[['Leon', 'casual', 'positive'], ['Leon', 'hip', 'positive'], ['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 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": ["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', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much 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": ["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": ["The place is small and cramped but the food is fantastic ."], "output": "[['place', 'small', 'negative'], ['place', 'cramped', 'negative'], ['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": ["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": ["Service is not exactly five star , but thats not really a big deal ."], "output": "[['Service', 'not exactly 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": ["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": ["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": ["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": ["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 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": ["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": ["The pizza is delicious - they use fresh mozzarella instead of the cheap , frozen , shredded cheese common to most pizzaria 's ."], "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": ["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": ["My husband and I thougt it would be great to go to the Jekyll and Hyde Pub for our anniversary , and to our surprise it was fantastic ."], "output": "[['Jekyll and Hyde Pub', 'great', 'positive'], ['Jekyll and Hyde Pub', '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": ["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": ["I have to highly recommend the lobster roll - not to much mayo ; you can tell it was a fresh lobster ."], "output": "[['lobster roll', 'recommend', 'positive'], ['lobster', '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": ["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": ["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": ["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 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["Great staff ."], "output": "[['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 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": ["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": ["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 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": ["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": ["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": ["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": ["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": ["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 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 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": ["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": ["Nice Family owned traditional restaurant ."], "output": "[['restaurant', '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": ["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": ["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": ["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": ["I had a huge pastrami sandwich on a roll ."], "output": "[['pastrami sandwich on a roll', '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 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 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": ["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": ["While their kitchen food is delicious , their Sushi is out of this world ."], "output": "[['kitchen food', 'delicious', 'positive'], ['Sushi', 'out of this world', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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 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": ["Authentic Taiwanese food that 's cheap ... what more could you ask for ?"], "output": "[['Taiwanese food', 'Authentic', 'positive'], ['Taiwanese food', 'cheap', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["My friend devoured her chicken and mashed potatos ."], "output": "[['chicken and mashed potatos', 'devoured', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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": ["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": ["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": ["The fish was adequate , but inexpertly sliced ."], "output": "[['fish', 'adequate', 'negative'], ['fish', 'inexpertly sliced', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["Drawbacks : service is slow and they do n't toast !"], "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": ["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": ["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": ["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": ["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": ["Service was very prompt but slightly rushed ."], "output": "[['Service', 'prompt', 'negative'], ['Service', 'rushed', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more 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": ["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": ["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": ["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": ["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": ["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 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": ["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": ["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": ["Best drumsticks over rice and sour spicy soup in town !"], "output": "[['drumsticks over rice', 'Best', 'positive'], ['sour spicy soup', 'Best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service 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": ["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": ["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": ["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": ["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": ["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": ["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": ["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": ["$ 20 for all you can eat sushi can not be beaten ."], "output": "[['all you can eat sushi', '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": ["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": ["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 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": ["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": ["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": ["Love Al Di La"], "output": "[['Al Di La', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["An awesome organic dog , and a conscious eco friendly establishment ."], "output": "[['dog', 'organic', 'positive'], ['establishment', 'eco friendly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["But the best pork souvlaki I ever had is the main thing ."], "output": "[['pork souvlaki', 'best', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I LOOOVE their eggplant pizza , as well as their pastas !"], "output": "[['eggplant pizza', 'LOOOVE', 'positive'], ['pastas', 'LOOOVE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["We had half/half pizza , mine was eggplant and my friend had the buffalo and it was sooo huge for a small size pizza !"], "output": "[['half/half pizza', 'huge', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Reliable , Fresh Sushi"], "output": "[['Sushi', 'Reliable', 'positive'], ['Sushi', 'Fresh', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The sashimi is always fresh and the rolls are innovative and delicious ."], "output": "[['sashimi', 'fresh', 'positive'], ['rolls', 'innovative', 'positive'], ['rolls', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Delivery guy sometimes get upset if you do n't tip more than 10 % ."], "output": "[['Delivery guy', 'upset', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The place is a bit hidden away , but once you get there , it 's all worth it ."], "output": "[['place', 'hidden away', 'positive'], ['place', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Good food : my favorite is the seafood spaghetti ."], "output": "[['food', 'Good', 'positive'], ['seafood spaghetti', 'favorite', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wait staff is very courteous and accomodating ."], "output": "[['wait staff', 'courteous', 'positive'], ['wait staff', 'accomodating', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I thought the restaurant was nice and clean ."], "output": "[['restaurant', 'nice', 'positive'], ['restaurant', 'clean', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["WORST PLACE ON SMITH STREET IN BROOKLYN"], "output": "[['PLACE', 'WORST', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The waitress was not attentive at all ."], "output": "[['waitress', 'not attentive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The Seafood Dynamite is also otherworldly ."], "output": "[['Seafood Dynamite', 'otherworldly', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["In the summer months , the back garden area is really nice ."], "output": "[['back garden area', 'nice', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The rolls are creative and I have yet to find another sushi place that serves up more inventive yet delicious japanese food ."], "output": "[['rolls', 'creative', 'positive'], ['japanese food', 'inventive', 'positive'], ['japanese food', 'delicious', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I CAN EAT HERE EVERY DAY OF THE WEEK REALLY LOL LOVE THIS PLACE ... )"], "output": "[['PLACE', 'LOVE', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["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": ["This is one of my favorite spot , very relaxing the food is great all the times , celebrated my engagement and my wedding here , it was very well organized ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Love their drink menu ."], "output": "[['drink menu', 'Love', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["A beautifully designed dreamy Egyptian restaurant that gets sceney at night ."], "output": "[['Egyptian restaurant', 'dreamy', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Watch the talented belly dancers as you enjoy delicious baba ganoush that 's more lemony than smoky ."], "output": "[['baba ganoush', 'enjoy delicious', 'positive'], ['belly dancers', 'talented', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The drinks are great , especially when made by Raymond ."], "output": "[['drinks', 'great', 'positive'], ['Raymond', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Decor needs to be upgraded but the food is amazing !"], "output": "[['Decor', 'upgraded', 'negative'], ['food', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Great food , amazing service , this place is a class act ."], "output": "[['food', 'Great', 'positive'], ['service', 'amazing', 'positive'], ['place', 'class act', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Paul , the maitre d ' , was totally professional and always on top of things ."], "output": "[['Paul', 'professional', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bar drinks were Eh , ok to say the least ."], "output": "[['bar drinks', 'ok', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The bread we received was horrible - rock hard and cold - and the `` free '' appetizer of olives was disappointing ."], "output": "[['bread', 'horrible', 'negative'], ['bread', 'rock hard', 'negative'], ['bread', 'cold', 'negative'], ['appetizer of olives', 'disappointing', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["short and sweet \u2013 seating is great : it 's romantic , cozy and private ."], "output": "[['seating', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service was extremely fast and attentive ( thanks to the service button on your table ) but I barely understood 1 word when the waiter took our order ."], "output": "[['service', 'fast', 'positive'], ['service', 'attentive', 'positive'], ['service button', 'thanks to', 'positive'], ['waiter', 'barely understood', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Highly impressed from the decor to the food to the hospitality to the great night I had !"], "output": "[['decor', 'impressed', 'positive'], ['food', 'impressed', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Food took some time to prepare , all worth waiting for ."], "output": "[['Food', 'worth', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu looked great , and the waiter was very nice , but when the food came , it was average ."], "output": "[['menu', 'great', 'positive'], ['waiter', 'nice', 'positive'], ['food', 'average', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It 's a great place to order from or sit-in ."], "output": "[['place', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Yamato is an excellent place to go if youre not into sashimi , or if you have friends who doesnt like sushi much ."], "output": "[['Yamato', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I 've had my fair share of modern Japanese and this spot delivers ."], "output": "[['modern Japanese', 'delivers', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Everything on the menu is great ."], "output": "[['menu', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Bison was quite excellent however ."], "output": "[['Bison', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["All in all , the food was great ( except for the dessserts ) ."], "output": "[['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["However , our $ 14 drinks were were horrible !"], "output": "[['drinks', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The menu is fairly simple without much descriptions ."], "output": "[['menu', 'simple', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Not much of a selection of bottled beer either , we went with Brahma ."], "output": "[['selection of bottled beer', 'Not much', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["All in all the food was good - a little on the expensive side , but fresh ."], "output": "[['food', 'good', 'negative'], ['food', 'expensive', 'negative'], ['food', 'fresh', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["It was n't as if this restaurant had any major bragging points before hand , but now it 's simply repulsive ."], "output": "[['restaurant', 'repulsive', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Gorgeous place ideal for a romantic dinner"], "output": "[['place', 'Gorgeous', 'positive'], ['place', 'ideal', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The nakgi-bokum was horrible ."], "output": "[['nakgi-bokum', 'horrible', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The side dishes were passable , and I did get a refill upon request ."], "output": "[['side dishes', 'passable', 'neutral']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["My wife had barely touched that mess of a dish ."], "output": "[['dish', 'mess', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The wife had the risotto which was amazing ."], "output": "[['risotto', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The crust has a great bite and a good chew , the sauce is light with a nice acidity to it , the salt from the cheese is great , really heightens the flavor of all the other components ."], "output": "[['crust', 'great', 'positive'], ['crust', 'good', 'positive'], ['sauce', 'light', 'positive'], ['cheese', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I picked the Grilled Black Cod as my entree , which I absolutely devoured while someone commented that the Grilled Salmon dish was better ."], "output": "[['Grilled Black Cod', 'devoured', 'positive'], ['Grilled Salmon dish', 'better', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The service leaves much to be desired , from feeling like you are rushed the place your order , to being ignored the rest of the night ."], "output": "[['service', 'leaves much to be desired', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hot dogs are good , yes , but the reason to get over here is the fantastic pork croquette sandwich , perfect on its supermarket squishy bun ."], "output": "[['hot dogs', 'good', 'positive'], ['pork croquette sandwich', 'fantastic', 'positive'], ['bun', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The family seafood entree was very good ."], "output": "[['family seafood entree', 'good', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Price is high but the food is good , so I would come back again ."], "output": "[['food', 'good', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["This place is not inviting and the food is totally weird ."], "output": "[['place', 'not inviting', 'negative'], ['food', 'weird', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["A coworker and I tried Pacifico after work a few Fridays and loved it ."], "output": "[['Pacifico', 'loved', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The food we ordered was excellent , although I would n't say the margaritas were anything to write home about ."], "output": "[['food', 'excellent', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["The hot dogs are top notch , and they 're Slamwich is amazing !"], "output": "[['hot dogs', 'top notch', 'positive'], ['Slamwich', 'amazing', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["But nonetheless -- great spot , great food ."], "output": "[['spot', 'great', 'positive'], ['food', 'great', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["This guy refused to seat her and she left , followed shortly by the four of us , but not before I told him that in my 40 years of world travel , including Paris , that I had never seen such a display of bad behavior by a frontman in a restaurant ."], "output": "[['frontman', 'bad', 'negative']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["Mussles and calamari were superb Saturday evening ."], "output": "[['Mussles', 'superb', 'positive'], ['calamari', 'superb', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "} {"task_type": "generation", "dataset": "aste-data-v2", "input": ["I had the Lamb special which was perfect ."], "output": "[['Lamb special', 'perfect', 'positive']]", "situation": "none", "label": "", "extra": "", "instruction": "Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: \"Null\" means that there is no occurrence in the sentence. Example: Input: \"It has so much more speed and the screen is very sharp .\" Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']] "}