NEUDM/aste-data-v2 · Datasets at Hugging Face

task_type stringclasses 1 value	dataset stringclasses 1 value	input list	output stringlengths 28 294	situation stringclasses 1 value	instruction stringclasses 1 value
generation	aste-data-v2	[ "Unique apppetizers ." ]	[['apppetizers', 'Unique', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The staff has always been attentive and kind , and I 've always been amazed at how they 've handled all the various different group sizes that come in ." ]	[['staff', 'attentive', 'positive'], ['staff', 'kind', 'positive'], ['staff', 'amazed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "IT is the best deal in town for a Monday night dinner at a fine restaurant ." ]	[['dinner', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The wait here is long for dim sum , but if you do n't like sharing tables or if the typical raucous dim sum atmosphere is not your gig , this is a sleek ( for Chinatown ) alternative ." ]	[['wait', 'long', 'negative'], ['dim sum', 'long', 'neutral'], ['dim sum atmosphere', 'typical raucous', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This place has good potential , but needs a significant amount of work before we can justify spending that much money on indian food you can get everywhere else ." ]	[['money', 'much', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Everything is always cooked to perfection , the service is excellent , the decor cool and understated ." ]	[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The Thai food is good ." ]	[['Thai food', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Great selection of wine , and seafood ." ]	[['selection of wine', 'Great', 'positive'], ['seafood', 'Great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Acceptable prices ." ]	[['prices', 'Acceptable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "As I made the title , it 's an affordable restaurant for great taste ." ]	[['taste', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Definitely not worth the price !" ]	[['price', 'not worth', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Orsay , is a very pleasant throw back to traditional French food , and French service as well ." ]	[['French food', 'pleasant', 'positive'], ['French food', 'traditional', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'traditional', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "It 's easy to get a table for a large group and you do n't get hustled out ." ]	[['table', 'easy', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Great food at reasonable prices ." ]	[['food', 'Great', 'positive'], ['prices', 'reasonable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Salads are a delicious way to begin the meal ." ]	[['Salads', 'delicious', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I ordered tamarind duck and my wife ordered noodles with ground beef , and we were both delighted by the way the dishes evoked Thai flavors in unexpected ways ." ]	[['tamarind duck', 'delighted', 'positive'], ['noodles with ground beef', 'delighted', 'positive'], ['dishes', 'delighted', 'positive'], ['Thai flavors', 'delighted', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The prices are about $ 9 for an entree for dinner and even less for lunch ." ]	[['prices', 'less', 'positive'], ['entree', 'less', 'positive'], ['dinner', 'less', 'neutral'], ['lunch', 'less', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Should you happen to be impressed by the cuisine definitely try it ." ]	[['cuisine', 'impressed', 'positive'], ['cuisine', 'try', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I had the black cod with yuzu sauce , which was wonderful ." ]	[['black cod with yuzu sauce', 'wonderful', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Prices too high for this cramped and unappealing resturant ." ]	[['Prices', 'high', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Total hipster-wannabe attitude in an otherwise sweet spot ." ]	[['spot', 'sweet', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Everything , from the soft bread , soggy salad , and 50 minute wait time , with an incredibly rude service to deliver below average food ." ]	[['service', 'rude', 'negative'], ['food', 'below average', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The sicilian is my favorite it is moist not dry like most places but all their pizza is great !" ]	[['pizza', 'great', 'positive'], ['sicilian', 'favorite', 'positive'], ['sicilian', 'moist not dry', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The menu prices are a bit expensive for what you get in quality and portion size ." ]	[['menu prices', 'expensive', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was amazing , and the service was prompt and helpful , but not over-bearing or rushed ." ]	[['food', 'amazing', 'positive'], ['service', 'prompt', 'positive'], ['service', 'helpful', 'positive'], ['service', 'not over-bearing or rushed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "( food was delivered by a busboy , not waiter ) We got no cheese offered for the pasta , our water and wine glasses remained EMPTY our entire meal , when we would have easily spent another $ 20 on wine ." ]	[['water and wine glasses', 'EMPTY', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The takeout is great too since they give high quality tupperware as well ." ]	[['takeout', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was not fresh , the sauces were bland and very oily ." ]	[['food', 'not fresh', 'negative'], ['sauces', 'bland', 'negative'], ['sauces', 'oily', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This is definitely an excellent date spot because of the ambiance and on the weekends the night scene is more than alive ." ]	[['night scene', 'alive', 'positive'], ['spot', 'excellent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Again , the waitress was awesome ." ]	[['waitress', 'awesome', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I loved everythig about it-especially the shows and actors ." ]	[['shows', 'loved', 'positive'], ['actors', 'loved', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals ." ]	[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['food', 'tasty', 'positive'], ['hot sauce', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Scalina Fedeli reminded me why service is so integral to fine dining ." ]	[['service', 'integral', 'positive'], ['dining', 'fine', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "i recommend the thai popcorn : )" ]	[['thai popcorn', 'recommend', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Everything looks great , the drinks , the decor , the food , even the people ." ]	[['drinks', 'great', 'positive'], ['decor', 'great', 'positive'], ['food', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The parathas and kebabs are made when ordered ensuring a level of freshness that is unsurpassed ." ]	[['parathas', 'unsurpassed', 'positive'], ['kebabs', 'unsurpassed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The tuna and wasabe potatoes are excellent ." ]	[['tuna', 'excellent', 'positive'], ['wasabe potatoes', 'excellent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The only disappointment was the coat check girls who did n't seem to know what a customer is on a realtively non-busy night ( for the coat check girls ) ." ]	[['coat check girls', 'disappointment', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We had great desserts ( including the best cannoli I 've ever had ) and then they offered an after dinner drink , on the house ." ]	[['desserts', 'great', 'positive'], ['cannoli', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Good crowd , good outdoor seating , with a hip japanese vibe ." ]	[['outdoor seating', 'good', 'positive'], ['vibe', 'hip', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We asked to be moved ( which took half an hour ) , and then were seated in a high traffic area in the back , even though the rest of the room was practically empty ." ]	[['room', 'empty', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "However , their popularity has yet to slow down , and I still find myself drawn to their ambiance and delectable reputation ." ]	[['ambiance', 'drawn', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Where tanks in other Chinatown restaurants display a lurking myriad of sad-looking marine life in their murky waters , the tanks at Ping 's are clear as glass with healthy-looking creatures who do not yet know that they will be part of some dim sum lover 's brunch ." ]	[['tanks', 'sad-looking', 'positive'], ['tanks', 'clear', 'positive'], ['dim sum', 'healthy-looking', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The Halibut was too salty , dessert was so so ( do n't waste any of your calories ) and service was poor ." ]	[['Halibut', 'salty', 'negative'], ['dessert', 'so so', 'neutral'], ['service', 'poor', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The view is spectacular , and the food is great ." ]	[['view', 'spectacular', 'positive'], ['food', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Good bagels and good cream cheese ." ]	[['bagels', 'good', 'positive'], ['cream cheese', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food is wonderful , tasty and filling , and the service is professional and friendly ." ]	[['food', 'wonderful', 'positive'], ['food', 'tasty', 'positive'], ['food', 'filling', 'positive'], ['service', 'professional', 'positive'], ['service', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "It is also extremely well priced ." ]	[['priced', 'well', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Always great service !" ]	[['service', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I LOVED THE SHOWS ." ]	[['SHOWS', 'LOVED', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We could have made a meal of the yummy dumplings from the dumpling menu ." ]	[['dumplings', 'yummy', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Then , get ripped on free box wine ." ]	[['box wine', 'free', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My wife and I ate here earlier this week and have not stopped ranting and raving about the food ." ]	[['food', 'ranting', 'positive'], ['food', 'raving', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food itself was just ok - nothing spectacular - but the service was awful ." ]	[['food', 'ok', 'neutral'], ['service', 'awful', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The pizza is yummy and I like the atmoshpere ." ]	[['pizza', 'yummy', 'positive'], ['atmoshpere', 'like', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Also , do n't plan on asking for your favorite roll , if it 's not on the menu , you ca n't have it ." ]	[['roll', 'favorite', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Good food ." ]	[['food', 'Good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "those rolls were big , but not good and sashimi was n't fresh ." ]	[['sashimi', "was n't fresh", 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "try the spicy shrimp appetizer ( again , not the greatest value in the world but worth the price ) and the lamb vindaloo is great ." ]	[['shrimp appetizer', 'try', 'positive'], ['shrimp appetizer', 'spicy', 'positive'], ['shrimp appetizer', 'worth the price', 'positive'], ['lamb vindaloo', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Food was good not great not worth the wait or another visit" ]	[['wait', 'not worth', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I have had so many dinners here and it 's always been perfect - on a date with my husband , with my mom , with girlfriends and larger groups ." ]	[['dinners', 'perfect', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The menu has lots of options : I hope to go back to try those potato pancakes ." ]	[['menu', 'lots', 'positive'], ['potato pancakes', 'try', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The staff is n't the friendliest or most competent , and I am stickler for service , but everything else about this place makes up for it ." ]	[['staff', 'friendliest', 'negative'], ['staff', 'competent', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My wife and I will usually only order one primi and one secondi and split them , as they tend to offer large portions ." ]	[['portions', 'large', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Delicious crab cakes too ." ]	[['crab cakes', 'Delicious', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "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 ." ]	[['service', 'good', 'positive'], ['staff', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The bruschetta and panini 's are so yummy !" ]	[['bruschetta', 'yummy', 'positive'], ['panini', 'yummy', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Always popular , always full , always a wait ." ]	[['wait', 'always', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "If the omakase is to showcase technique and variety , serving almost 40 % of items BBQ-ed and a spicy tuna roll wrapped with not-so-fresh nori seems to be a rather limp performance ." ]	[['nori', 'not-so-fresh', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I ca n't wait for summer , when they serve outside on their gigantic patio ." ]	[['patio', 'gigantic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Best Pastrami I ever had and great portion without being ridiculous ." ]	[['Pastrami', 'Best', 'positive'], ['portion', 'great', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The first 2 courses were very good , but the chocolate sampler was too rich for me and the dessert wine far too sweet ." ]	[['courses', 'good', 'positive'], ['chocolate sampler', 'too rich', 'negative'], ['dessert wine', 'too sweet', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Butter was melted , white wine warm , cheese oozing everywhere ." ]	[['Butter', 'melted', 'negative'], ['white wine', 'warm', 'negative'], ['cheese', 'oozing', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We had a party in their private room and they made it truly memorable and were very helpful in the planning ." ]	[['private room', 'truly memorable', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "It can not be the ambience , because the place is very cramped and some guests have to sit in an aisle ." ]	[['place', 'cramped', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We were disappointed with the pre-fixe menu of only 2 choices per course ( other restaurants offer 3 choices ) and ended up ordering a la carte ." ]	[['pre-fixe menu', 'disappointed', 'negative'], ['choices per course', 'disappointed', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Authentic Pakistani food ." ]	[['Pakistani food', 'Authentic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The staff has always been friendly without seeming grating , and the chef has greeted us on a couple of occasions ." ]	[['staff', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The eggplant parmesan is also great , and my friend who grew up in Manhattan claims that no one serves a better baked ziti with meatsauce ." ]	[['eggplant parmesan', 'great', 'positive'], ['baked ziti with meatsauce', 'better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Quality ingredients preparation all around , and a very fair price for NYC ." ]	[['ingredients', 'Quality', 'positive'], ['price', 'fair', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service was very good - prompt , attentive and non-intrusive ." ]	[['Service', 'good', 'positive'], ['Service', 'prompt', 'positive'], ['Service', 'attentive', 'positive'], ['Service', 'non-intrusive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My entree of hot pot with seafood was full of imitation crabmeat with a couple pieces of shrimp and squid , and was unnecessarily heated with a burner ." ]	[['crabmeat', 'unnecessarily', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "In such a crappy part of town to find a good value for lunch , this place is great ." ]	[['value', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "In fact , while leaving the place we saw two people looking at the menu , and I could n't help telling them that the food was horrible ." ]	[['food', 'horrible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Even though the restaurant was packed , we were seated promptly and even asked for a table upstairs with no problems ." ]	[['seated', 'promptly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service is friendly , prices are good - delivery time was a little slow , but for the way this pizza tastes , I 'm willing to overlook it ." ]	[['Service', 'friendly', 'positive'], ['prices', 'good', 'positive'], ['delivery time', 'slow', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you do n't like ." ]	[['food', 'pricey', 'negative'], ['price', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service is excellent , the decor is great , and the food is delicious and comes in large portions ." ]	[['service', 'excellent', 'positive'], ['decor', 'great', 'positive'], ['food', 'delicious', 'positive'], ['portions', 'large', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "An excellent service" ]	[['service', 'excellent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I LOVE their Thai noodles with shrimp and chicken and coconut juice is the MUST !" ]	[['Thai noodles with shrimp and chicken and coconut juice', 'LOVE', 'positive'], ['Thai noodles with shrimp and chicken and coconut juice', 'MUST', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The pizza was really good ." ]	[['pizza', 'good', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The only possible drawback to this last point is that as of the date of this posting , the additional menu items are only written in Chinese ." ]	[['menu items', 'drawback', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Kosher dills are the perfect compliment for your unforgetable sandwich and they give you plenty of them ." ]	[['Kosher dills', 'perfect', 'positive'], ['sandwich', 'unforgetable', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food is so cheap and the waiters are nice ." ]	[['food', 'cheap', 'positive'], ['waiters', 'nice', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food there is so good that even to order out the wait is incredible ." ]	[['food', 'good', 'positive'], ['wait', 'incredible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Their sushi , Kamikaze and other Rolls are fresh and well presented ." ]	[['sushi', 'fresh', 'positive'], ['sushi', 'well presented', 'positive'], ['Kamikaze', 'fresh', 'positive'], ['Kamikaze', 'well presented', 'positive'], ['Rolls', 'fresh', 'positive'], ['Rolls', 'well presented', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "For authentic Thai food , look no further than Toons ." ]	[['Thai food', 'authentic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The highlight of the night was the mayonaisse for my side of fries I received from one of the food runners , which is not good considering the bill was nearly $ 100 ." ]	[['mayonaisse', 'highlight', 'negative'], ['food runners', 'not good', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I choose to go with one of the special , the braised lamb shank in red wine , which was excellent ." ]	[['braised lamb shank in red wine', 'excellent', 'positive'], ['special', 'excellent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Small servings for main entree , i had salmon ( wasnt impressed ) girlfriend had chicken , it was good ." ]	[['salmon', 'wasnt impressed', 'negative'], ['chicken', 'good', 'positive'], ['servings', 'Small', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Unique apppetizers ." ]

[['apppetizers', 'Unique', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The staff has always been attentive and kind , and I 've always been amazed at how they 've handled all the various different group sizes that come in ." ]

[['staff', 'attentive', 'positive'], ['staff', 'kind', 'positive'], ['staff', 'amazed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "IT is the best deal in town for a Monday night dinner at a fine restaurant ." ]

[['dinner', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The wait here is long for dim sum , but if you do n't like sharing tables or if the typical raucous dim sum atmosphere is not your gig , this is a sleek ( for Chinatown ) alternative ." ]

[['wait', 'long', 'negative'], ['dim sum', 'long', 'neutral'], ['dim sum atmosphere', 'typical raucous', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This place has good potential , but needs a significant amount of work before we can justify spending that much money on indian food you can get everywhere else ." ]

[['money', 'much', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Everything is always cooked to perfection , the service is excellent , the decor cool and understated ." ]

[['service', 'excellent', 'positive'], ['decor', 'cool', 'positive'], ['decor', 'understated', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The Thai food is good ." ]

[['Thai food', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Great selection of wine , and seafood ." ]

[['selection of wine', 'Great', 'positive'], ['seafood', 'Great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Acceptable prices ." ]

[['prices', 'Acceptable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "As I made the title , it 's an affordable restaurant for great taste ." ]

[['taste', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Definitely not worth the price !" ]

[['price', 'not worth', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Orsay , is a very pleasant throw back to traditional French food , and French service as well ." ]

[['French food', 'pleasant', 'positive'], ['French food', 'traditional', 'positive'], ['service', 'pleasant', 'positive'], ['service', 'traditional', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "It 's easy to get a table for a large group and you do n't get hustled out ." ]

[['table', 'easy', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Great food at reasonable prices ." ]

[['food', 'Great', 'positive'], ['prices', 'reasonable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Salads are a delicious way to begin the meal ." ]

[['Salads', 'delicious', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I ordered tamarind duck and my wife ordered noodles with ground beef , and we were both delighted by the way the dishes evoked Thai flavors in unexpected ways ." ]

[['tamarind duck', 'delighted', 'positive'], ['noodles with ground beef', 'delighted', 'positive'], ['dishes', 'delighted', 'positive'], ['Thai flavors', 'delighted', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The prices are about $ 9 for an entree for dinner and even less for lunch ." ]

[['prices', 'less', 'positive'], ['entree', 'less', 'positive'], ['dinner', 'less', 'neutral'], ['lunch', 'less', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Should you happen to be impressed by the cuisine definitely try it ." ]

[['cuisine', 'impressed', 'positive'], ['cuisine', 'try', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I had the black cod with yuzu sauce , which was wonderful ." ]

[['black cod with yuzu sauce', 'wonderful', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Prices too high for this cramped and unappealing resturant ." ]

[['Prices', 'high', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Total hipster-wannabe attitude in an otherwise sweet spot ." ]

[['spot', 'sweet', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Everything , from the soft bread , soggy salad , and 50 minute wait time , with an incredibly rude service to deliver below average food ." ]

[['service', 'rude', 'negative'], ['food', 'below average', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The sicilian is my favorite it is moist not dry like most places but all their pizza is great !" ]

[['pizza', 'great', 'positive'], ['sicilian', 'favorite', 'positive'], ['sicilian', 'moist not dry', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The menu prices are a bit expensive for what you get in quality and portion size ." ]

[['menu prices', 'expensive', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food was amazing , and the service was prompt and helpful , but not over-bearing or rushed ." ]

[['food', 'amazing', 'positive'], ['service', 'prompt', 'positive'], ['service', 'helpful', 'positive'], ['service', 'not over-bearing or rushed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "( food was delivered by a busboy , not waiter ) We got no cheese offered for the pasta , our water and wine glasses remained EMPTY our entire meal , when we would have easily spent another $ 20 on wine ." ]

[['water and wine glasses', 'EMPTY', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The takeout is great too since they give high quality tupperware as well ." ]

[['takeout', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food was not fresh , the sauces were bland and very oily ." ]

[['food', 'not fresh', 'negative'], ['sauces', 'bland', 'negative'], ['sauces', 'oily', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "This is definitely an excellent date spot because of the ambiance and on the weekends the night scene is more than alive ." ]

[['night scene', 'alive', 'positive'], ['spot', 'excellent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Again , the waitress was awesome ." ]

[['waitress', 'awesome', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I loved everythig about it-especially the shows and actors ." ]

[['shows', 'loved', 'positive'], ['actors', 'loved', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The service was fast and friendly and the food was very tasty and they had the best hot sauce to add to your meals ." ]

[['service', 'fast', 'positive'], ['service', 'friendly', 'positive'], ['food', 'tasty', 'positive'], ['hot sauce', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Scalina Fedeli reminded me why service is so integral to fine dining ." ]

[['service', 'integral', 'positive'], ['dining', 'fine', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "i recommend the thai popcorn : )" ]

[['thai popcorn', 'recommend', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Everything looks great , the drinks , the decor , the food , even the people ." ]

[['drinks', 'great', 'positive'], ['decor', 'great', 'positive'], ['food', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The parathas and kebabs are made when ordered ensuring a level of freshness that is unsurpassed ." ]

[['parathas', 'unsurpassed', 'positive'], ['kebabs', 'unsurpassed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The tuna and wasabe potatoes are excellent ." ]

[['tuna', 'excellent', 'positive'], ['wasabe potatoes', 'excellent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The only disappointment was the coat check girls who did n't seem to know what a customer is on a realtively non-busy night ( for the coat check girls ) ." ]

[['coat check girls', 'disappointment', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We had great desserts ( including the best cannoli I 've ever had ) and then they offered an after dinner drink , on the house ." ]

[['desserts', 'great', 'positive'], ['cannoli', 'best', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Good crowd , good outdoor seating , with a hip japanese vibe ." ]

[['outdoor seating', 'good', 'positive'], ['vibe', 'hip', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We asked to be moved ( which took half an hour ) , and then were seated in a high traffic area in the back , even though the rest of the room was practically empty ." ]

[['room', 'empty', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "However , their popularity has yet to slow down , and I still find myself drawn to their ambiance and delectable reputation ." ]

[['ambiance', 'drawn', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Where tanks in other Chinatown restaurants display a lurking myriad of sad-looking marine life in their murky waters , the tanks at Ping 's are clear as glass with healthy-looking creatures who do not yet know that they will be part of some dim sum lover 's brunch ." ]

[['tanks', 'sad-looking', 'positive'], ['tanks', 'clear', 'positive'], ['dim sum', 'healthy-looking', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The Halibut was too salty , dessert was so so ( do n't waste any of your calories ) and service was poor ." ]

[['Halibut', 'salty', 'negative'], ['dessert', 'so so', 'neutral'], ['service', 'poor', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The view is spectacular , and the food is great ." ]

[['view', 'spectacular', 'positive'], ['food', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Good bagels and good cream cheese ." ]

[['bagels', 'good', 'positive'], ['cream cheese', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food is wonderful , tasty and filling , and the service is professional and friendly ." ]

[['food', 'wonderful', 'positive'], ['food', 'tasty', 'positive'], ['food', 'filling', 'positive'], ['service', 'professional', 'positive'], ['service', 'friendly', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "It is also extremely well priced ." ]

[['priced', 'well', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Always great service !" ]

[['service', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I LOVED THE SHOWS ." ]

[['SHOWS', 'LOVED', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We could have made a meal of the yummy dumplings from the dumpling menu ." ]

[['dumplings', 'yummy', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Then , get ripped on free box wine ." ]

[['box wine', 'free', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "My wife and I ate here earlier this week and have not stopped ranting and raving about the food ." ]

[['food', 'ranting', 'positive'], ['food', 'raving', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food itself was just ok - nothing spectacular - but the service was awful ." ]

[['food', 'ok', 'neutral'], ['service', 'awful', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The pizza is yummy and I like the atmoshpere ." ]

[['pizza', 'yummy', 'positive'], ['atmoshpere', 'like', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Also , do n't plan on asking for your favorite roll , if it 's not on the menu , you ca n't have it ." ]

[['roll', 'favorite', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Good food ." ]

[['food', 'Good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "those rolls were big , but not good and sashimi was n't fresh ." ]

[['sashimi', "was n't fresh", 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "try the spicy shrimp appetizer ( again , not the greatest value in the world but worth the price ) and the lamb vindaloo is great ." ]

[['shrimp appetizer', 'try', 'positive'], ['shrimp appetizer', 'spicy', 'positive'], ['shrimp appetizer', 'worth the price', 'positive'], ['lamb vindaloo', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Food was good not great not worth the wait or another visit" ]

[['wait', 'not worth', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I have had so many dinners here and it 's always been perfect - on a date with my husband , with my mom , with girlfriends and larger groups ." ]

[['dinners', 'perfect', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The menu has lots of options : I hope to go back to try those potato pancakes ." ]

[['menu', 'lots', 'positive'], ['potato pancakes', 'try', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The staff is n't the friendliest or most competent , and I am stickler for service , but everything else about this place makes up for it ." ]

[['staff', 'friendliest', 'negative'], ['staff', 'competent', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "My wife and I will usually only order one primi and one secondi and split them , as they tend to offer large portions ." ]

[['portions', 'large', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Delicious crab cakes too ." ]

[['crab cakes', 'Delicious', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "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 ." ]

[['service', 'good', 'positive'], ['staff', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The bruschetta and panini 's are so yummy !" ]

[['bruschetta', 'yummy', 'positive'], ['panini', 'yummy', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Always popular , always full , always a wait ." ]

[['wait', 'always', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "If the omakase is to showcase technique and variety , serving almost 40 % of items BBQ-ed and a spicy tuna roll wrapped with not-so-fresh nori seems to be a rather limp performance ." ]

[['nori', 'not-so-fresh', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I ca n't wait for summer , when they serve outside on their gigantic patio ." ]

[['patio', 'gigantic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Best Pastrami I ever had and great portion without being ridiculous ." ]

[['Pastrami', 'Best', 'positive'], ['portion', 'great', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The first 2 courses were very good , but the chocolate sampler was too rich for me and the dessert wine far too sweet ." ]

[['courses', 'good', 'positive'], ['chocolate sampler', 'too rich', 'negative'], ['dessert wine', 'too sweet', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Butter was melted , white wine warm , cheese oozing everywhere ." ]

[['Butter', 'melted', 'negative'], ['white wine', 'warm', 'negative'], ['cheese', 'oozing', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We had a party in their private room and they made it truly memorable and were very helpful in the planning ." ]

[['private room', 'truly memorable', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "It can not be the ambience , because the place is very cramped and some guests have to sit in an aisle ." ]

[['place', 'cramped', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "We were disappointed with the pre-fixe menu of only 2 choices per course ( other restaurants offer 3 choices ) and ended up ordering a la carte ." ]

[['pre-fixe menu', 'disappointed', 'negative'], ['choices per course', 'disappointed', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Authentic Pakistani food ." ]

[['Pakistani food', 'Authentic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The staff has always been friendly without seeming grating , and the chef has greeted us on a couple of occasions ." ]

[['staff', 'friendly', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The eggplant parmesan is also great , and my friend who grew up in Manhattan claims that no one serves a better baked ziti with meatsauce ." ]

[['eggplant parmesan', 'great', 'positive'], ['baked ziti with meatsauce', 'better', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Quality ingredients preparation all around , and a very fair price for NYC ." ]

[['ingredients', 'Quality', 'positive'], ['price', 'fair', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Service was very good - prompt , attentive and non-intrusive ." ]

[['Service', 'good', 'positive'], ['Service', 'prompt', 'positive'], ['Service', 'attentive', 'positive'], ['Service', 'non-intrusive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "My entree of hot pot with seafood was full of imitation crabmeat with a couple pieces of shrimp and squid , and was unnecessarily heated with a burner ." ]

[['crabmeat', 'unnecessarily', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "In such a crappy part of town to find a good value for lunch , this place is great ." ]

[['value', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "In fact , while leaving the place we saw two people looking at the menu , and I could n't help telling them that the food was horrible ." ]

[['food', 'horrible', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Even though the restaurant was packed , we were seated promptly and even asked for a table upstairs with no problems ." ]

[['seated', 'promptly', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Service is friendly , prices are good - delivery time was a little slow , but for the way this pizza tastes , I 'm willing to overlook it ." ]

[['Service', 'friendly', 'positive'], ['prices', 'good', 'positive'], ['delivery time', 'slow', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food can get pricey but the prixe fixe tasting menu is the greatest food for a good price and they cater the food to any food allergies or food you do n't like ." ]

[['food', 'pricey', 'negative'], ['price', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The service is excellent , the decor is great , and the food is delicious and comes in large portions ." ]

[['service', 'excellent', 'positive'], ['decor', 'great', 'positive'], ['food', 'delicious', 'positive'], ['portions', 'large', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "An excellent service" ]

[['service', 'excellent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I LOVE their Thai noodles with shrimp and chicken and coconut juice is the MUST !" ]

[['Thai noodles with shrimp and chicken and coconut juice', 'LOVE', 'positive'], ['Thai noodles with shrimp and chicken and coconut juice', 'MUST', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The pizza was really good ." ]

[['pizza', 'good', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The only possible drawback to this last point is that as of the date of this posting , the additional menu items are only written in Chinese ." ]

[['menu items', 'drawback', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Kosher dills are the perfect compliment for your unforgetable sandwich and they give you plenty of them ." ]

[['Kosher dills', 'perfect', 'positive'], ['sandwich', 'unforgetable', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food is so cheap and the waiters are nice ." ]

[['food', 'cheap', 'positive'], ['waiters', 'nice', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The food there is so good that even to order out the wait is incredible ." ]

[['food', 'good', 'positive'], ['wait', 'incredible', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Their sushi , Kamikaze and other Rolls are fresh and well presented ." ]

[['sushi', 'fresh', 'positive'], ['sushi', 'well presented', 'positive'], ['Kamikaze', 'fresh', 'positive'], ['Kamikaze', 'well presented', 'positive'], ['Rolls', 'fresh', 'positive'], ['Rolls', 'well presented', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "For authentic Thai food , look no further than Toons ." ]

[['Thai food', 'authentic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "The highlight of the night was the mayonaisse for my side of fries I received from one of the food runners , which is not good considering the bill was nearly $ 100 ." ]

[['mayonaisse', 'highlight', 'negative'], ['food runners', 'not good', 'neutral']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "I choose to go with one of the special , the braised lamb shank in red wine , which was excellent ." ]

[['braised lamb shank in red wine', 'excellent', 'positive'], ['special', 'excellent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]

generation

aste-data-v2

[ "Small servings for main entree , i had salmon ( wasnt impressed ) girlfriend had chicken , it was good ." ]

[['salmon', 'wasnt impressed', 'negative'], ['chicken', 'good', 'positive'], ['servings', 'Small', 'negative']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]