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	[ "The food was average or above including some surprising tasty dishes ." ]	[['food', 'average or above', 'positive'], ['dishes', 'tasty', '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	[ "They do n't seem to place an emphasis on specials or fresh ingredients which to me is necessary for good thai ." ]	[['ingredients', 'good', 'negative'], ['thai', '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	[ "The crust is thin , the ingredients are fresh and the staff is friendly ." ]	[['crust', 'thin', 'positive'], ['staff', 'friendly', 'positive'], ['ingredients', 'fresh', '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 a little more expensive than your average bagel place ." ]	[['bagel', 'expensive', '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 food was undercooked -the sauce watery , and the vegetables raw ." ]	[['food', 'undercooked', 'negative'], ['vegetables', 'raw', 'negative'], ['sauce', 'watery', '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	[ "And the fried clams had just enough kick to them to make 'em worth eating ." ]	[['fried clams', 'enough', '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 sauces used are also not that exciting ." ]	[['sauces', 'not that exciting', '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 secret is the lunch menu which offers a complimentary appetizer with every entree ordered ." ]	[['lunch menu', 'secret', 'positive'], ['appetizer', 'complimentary', 'positive'], ['entree', 'complimentary', '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 shrimp scampi was excellent and the antipasti were plentiful ." ]	[['shrimp scampi', 'excellent', 'positive'], ['antipasti', 'plentiful', '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 got the $ 10 10-piece dim sum combo , every bite of which was great ." ]	[['dim sum combo', '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	[ "There is also very limited seating and there can be a substantial wait in getting food at peak times ." ]	[['seating', 'limited', 'negative'], ['wait', 'substantial', '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 it 's just a quick martini at the bar ( which I recommend Jeffery 's ) or a mind blowing Roast Chicken , go to Village !" ]	[['martini', 'quick', 'neutral'], ['bar', 'recommend', 'neutral'], ['Roast Chicken', 'mind blowing', '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	[ "There was a long wait for a table outside , but it was a little too hot in the sun anyway so our insde table was very nice ." ]	[['table', 'long wait', 'neutral'], ['insde table', 'nice', 'positive'], ['wait', 'long', '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 prices are wonderfully low ." ]	[['prices', 'wonderfully low', '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 never been disappointed but their true strength lays in their amazingly delicious and cheap lunch specials ." ]	[['lunch specials', 'delicious', 'positive'], ['lunch specials', 'cheap', '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	[ "So much more than the usual bar food , go there to enjoy the menu while sampling one of their hand-crafted beers ." ]	[['menu', 'enjoy', 'positive'], ['hand-crafted beers', 'hand-crafted', '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	[ "No free drink ." ]	[['drink', 'No free', '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 is my first time writing a review for a restaurant because the food and service was excellent ." ]	[['food', 'excellent', 'positive'], ['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	[ "Do n't waste money on decor ." ]	[['decor', 'waste', '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	[ "They also have a back garden open in the summer - cute and French with outdoor seating - what more could you ask for ?" ]	[['back garden', 'cute', 'positive'], ['back garden', 'French', '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 never before eaten 40 pieces of relatively good nigiri ." ]	[['nigiri', '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	[ "Given the incredible architecture surrounding it , this place has no character ." ]	[['architecture', 'incredible', 'positive'], ['place', 'no character', '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	[ "While the place is not a hotspot hangout , the drinks are unique and pack a lot of bang for the buck ." ]	[['drinks', '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	[ "Their eggplant is so delicate , sweet tender !" ]	[['eggplant', 'delicate', 'positive'], ['eggplant', 'sweet tender', '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	[ "Each bite of food at Kai was indeed delicious , fresh , and elegant ." ]	[['food', 'delicious', 'positive'], ['food', 'fresh', 'positive'], ['food', 'elegant', '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	[ "all the food was excellent - considering the quality of food in most moderately priced restaurants is mediocre this was slightly more pricey and well worth it ." ]	[['food', 'excellent', 'positive'], ['quality of food', 'mediocre', 'positive'], ['priced', 'moderately', '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 had the cod with paella ( spicy and very filling , I 'm a big eater and could only eat half ) while my boyfriend had the classic fish and chips ( again , a big serving - at least 5 pieces of fish and a basketful of fries ) ." ]	[['cod with paella', 'spicy', 'negative'], ['cod with paella', 'filling', 'negative'], ['fish and chips', 'classic', 'negative'], ['fish and chips', 'big', 'negative'], ['serving', 'big', '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	[ "It 's a shame that a nice , convenient place like the Pink Pony can be so ruined by lousy service ." ]	[['place', 'convenient', 'positive'], ['service', 'lousy', '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 wontons and the salt pepper shrimps ." ]	[['spicy wontons', 'Try', 'positive'], ['salt pepper shrimps', '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 fries are yummy ." ]	[['fries', '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	[ "Friendly and informative staff , very attentive and prompt raw bar service ." ]	[['staff', 'Friendly', 'positive'], ['staff', 'informative', 'positive'], ['staff', 'attentive', 'positive'], ['bar service', 'raw', '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 Taiwanese food in NY !" ]	[['Taiwanese food', '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	[ "This place is a great stop for great food ." ]	[['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	[ "All the pastas are fantastic and the homemade lasagna is some of the best that I have had in the City ." ]	[['pastas', 'fantastic', 'positive'], ['homemade lasagna', '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	[ "And the prices were way to high for what you get ." ]	[['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	[ "The staff ignored my friends and I the entire time we were there ." ]	[['staff', 'ignored', '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	[ "Yet paired with such rude service , would never recommend for anyone interested in carrying any kind of conversation while there ." ]	[['service', 'rude', '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 in-house lady DJ on Saturday nights has outrageously good taste in music , and moreover , takes requests ." ]	[['in-house lady DJ', 'good taste', '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 wine list , reasonably priced . -- Sara" ]	[['wine list', 'Great', 'positive'], ['priced', 'reasonably', '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 hot dogs were cold in the middle and the buns were stale ." ]	[['hot dogs', 'cold', 'negative'], ['buns', 'stale', '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	[ "While the food was excellent , it was n't cheap ( though not extremely expensive either ) ." ]	[['food', '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	[ "Beef noodle soup is good as well ." ]	[['Beef noodle soup', '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	[ "Delivery service is great too ." ]	[['Delivery 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	[ "The food 's dazzling flavors overwhelm the palate , truly embracing the beauty of authentic Thai cuisine ." ]	[['food', 'overwhelm', 'positive'], ['Thai cuisine', 'authentic', 'positive'], ['flavors', 'overwhelm', '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 recieved prompt service with a smile ." ]	[['service', 'prompt', '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	[ "They pray to their Food Gods to make them into a good pizza like VT 's ." ]	[['pizza', 'good', '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 place was quiet and delightful ." ]	[['place', 'quiet', 'positive'], ['place', 'delightful', '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 a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes ." ]	[['food', 'diamond', 'positive'], ['food', 'delicious', 'positive'], ['food', 'homemade', 'positive'], ['herbs', 'perfect', 'positive'], ['tomatoes', '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	[ "As much as I like the food there , I ca n't bring myself to go back ." ]	[['food', '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	[ "The prices and ambience are especially great considering it 's in the West Village ." ]	[['prices', 'great', 'positive'], ['ambience', '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 soup is pretty good too ." ]	[['soup', '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	[ "It is so easy to get a reservation at a top place in NYC with a week 's notice ." ]	[['reservation', '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	[ "not the food , not the ambiance , not the service , I agree with the previous reviews you wait and wait , the wait staff are very rude and when you get in they are looking to get you right out ." ]	[['wait staff', 'rude', '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 always get the Shabu-Shabu dinner and the beef is always fresh ." ]	[['beef', 'fresh', '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 delivered cold and the cheese was n't even fully melted !" ]	[['pizza', 'cold', 'negative'], ['cheese', "was n't even fully melted", '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 very surprised by how good the food was on our first visit here on a Sunday night ." ]	[['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	[ "Nha Trang , while being notorious for utter lack of comfort and decor , horribly slow wait staff and horribly quick meals , is one of the best vietnamese restaurants i 've ever been to . the pho is delicious and comes with very fresh vegtables ." ]	[['comfort', 'lack', 'negative'], ['decor', 'lack', 'negative'], ['wait staff', 'horribly slow', 'negative'], ['meals', 'horribly quick', 'negative'], ['pho', 'delicious', 'positive'], ['vegtables', 'fresh', '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	[ "On the other hand , if you are not fooled easily , you will find hundreds of restaurants that will give you service and ambiance that is on par with Alain Ducasse , and food that will outshine in presentaion , taste , choice , quality and quantity ." ]	[['service', 'on par', 'neutral'], ['ambiance', 'on par', 'neutral'], ['food', 'outshine', '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 I could rate the people this place would be off the charts - unfortunately - the pizza , sorry - not the best in NYC ." ]	[['people', 'best', 'positive'], ['pizza', 'best', '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	[ "Having not been home in the last 2 years may skew this reviewer a bit , but the food was tasty and spicy sans the oil that comes floating along at similar venues ." ]	[['food', 'tasty', 'positive'], ['food', 'spicy', '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 portions are now very small , the sauces are overly ambitious usually inedible while the service is still good , the restaurant , due to its popularity , seems frantic ." ]	[['portions', 'small', 'negative'], ['sauces', 'ambitious', 'negative'], ['sauces', 'inedible', 'negative'], ['service', '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 owner is very friendly and a great guy , go try his pizza , you 'll like it !" ]	[['owner', 'friendly', 'positive'], ['owner', 'great', 'positive'], ['pizza', 'try', 'positive'], ['pizza', '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	[ "The atmosphere is great ! ! !" ]	[['atmosphere', '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	[ "With so many good restaurants on the UWS , I do n't need overpriced food , absurdly arrogant wait-staff who do n't recognize they work at a glorified diner , clumsy service , and management that does n't care ." ]	[['food', 'overpriced', 'negative'], ['wait-staff', 'arrogant', 'negative'], ['service', 'clumsy', 'negative'], ['management', "does n't care", 'negative'], ['diner', 'glorified', '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 tend to judge a sushi restaurant by its sea urchin , which was heavenly at sushi rose ." ]	[['sea urchin', 'heavenly', '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 a little scatty at times but all is forgiven when the food arrives ." ]	[['service', 'scatty', 'negative'], ['food', 'forgiven', '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 bruscetta is a bit soggy , but the salads were fresh , included a nice mix of greens ( not iceberg ) all dishes are served piping hot from the kitchen ." ]	[['bruscetta', 'soggy', 'negative'], ['salads', 'fresh', 'positive'], ['dishes', 'hot', 'positive'], ['mix of greens', '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 atmosphere is n't the greatest , but I suppose that 's how they keep the prices down ." ]	[['atmosphere', "is n't the greatest", 'neutral'], ['prices', 'down', '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 pickles were great addition ." ]	[['pickles', '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	[ "If your favorite Chinese food is General Tao chicken , then this is NOT your place ." ]	[['General Tao chicken', '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	[ "You must try the shrimp appetizers ." ]	[['shrimp appetizers', '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	[ "Not only is the cuisine the best around , the service has always been attentive and charming ." ]	[['cuisine', 'best', 'positive'], ['service', 'attentive', 'positive'], ['service', 'charming', '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 production is a symphony , alot of fun to experience.The food sublime for the most part ." ]	[['food', 'sublime', '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	[ "Waiters tend to forget drinks completely , food portions are so tiny , two people have trouble sharing one entree ." ]	[['Waiters', 'forget', 'negative'], ['food portions', 'tiny', 'negative'], ['drinks', 'forget', 'neutral'], ['entree', 'trouble', '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	[ "But the thing that my wife and I hated was it was so loud and it felt like ' bar ' or ' pub ' ." ]	[['bar', 'loud', 'negative'], ['pub', 'loud', '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	[ "While there are plenty of places to go for a good corned beef sandwich , Katz 's has a charm about it ." ]	[['corned beef sandwich', '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	[ "However , looking at the table next to ours , we both sort of wished we had ordered pizza , which looked perfect" ]	[['pizza', '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	[ "Priced at upper intermediate range ." ]	[['Priced', 'upper intermediate', '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 you live in new york city , you 'll find better food at small restaurants outside of time square and spend half the amount ." ]	[['food', 'better', '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	[ "they did n't disappoint , service from the second i arrived at the door was extremely pleasant and attentive with almost one server per table ." ]	[['service', 'pleasant', 'positive'], ['service', 'attentive', '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 do n't know who they think they are but they have no respect for the residents of the neighborhood ever since they opened their cabaret next door and blasts loud music till three in the morning every weekend during the summer ." ]	[['music', 'loud', '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 only positive was the wait staff , which was prompt , knowledgable , and likeable ." ]	[['wait staff', 'positive', 'positive'], ['wait staff', 'prompt', 'positive'], ['wait staff', 'knowledgable', 'positive'], ['wait staff', 'likeable', '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 am not a vegetarian but , almost all the dishes were great ." ]	[['dishes', '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 was very impressed by this low-key upper eastsider and their authentically thai cuisine ! ! !" ]	[['thai cuisine', 'authentically', '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 the location , the prices are very reasonable ." ]	[['prices', 'reasonable', 'positive'], ['location', 'reasonable', '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 food is okay and the prices here are mediocre ." ]	[['food', 'okay', 'neutral'], ['prices', 'mediocre', '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	[ "My friend 's food was also the complete opposite of what it 's supposed to taste like ( aND look like ) ." ]	[['food', 'opposite', '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 have been to this place many times , and always have great food , wine , and service ." ]	[['food', 'great', 'positive'], ['wine', 'great', 'positive'], ['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	[ "Not a typical pizza joint , but good for a low key and fairly cheap nice sit down dinner ." ]	[['dinner', 'cheap 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 corned beef was tender and melted in my mouth ." ]	[['corned beef', 'tender', 'positive'], ['corned beef', 'melted', '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 best Chicken pad tai , I 've ever had ." ]	[['Chicken pad tai', '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	[ "$ 20 for all you can eat sushi can not be beaten ." ]	[['sushi', 'can not be beaten', '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	[ "Haru serves very fresh fish , has a trendy , modern ambiance , prime location on Park Avenue South and friendly service ." ]	[['fish', 'fresh', 'positive'], ['service', 'friendly', 'positive'], ['ambiance', 'trendy', 'positive'], ['ambiance', 'modern', 'positive'], ['location', 'prime', '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	[ "Warm and friendly in the winter and terrific outdoor seating in the warmer months ." ]	[['outdoor seating', 'terrific', '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	[ "Very romantic fires - I 've literally spent hours at Lanterna , drinking wine from their extensive wine and enjoying the ambience ." ]	[['wine', 'extensive', 'positive'], ['ambience', 'enjoying', '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 got a little tipsy from the sake but is n't that what Saturday nights with the girlfriends are all about ?" ]	[['sake', 'tipsy', '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	[ "My turkey burger was not cooked at all , my friends salmon was completely raw ." ]	[['turkey burger', 'not cooked', 'negative'], ['salmon', 'raw', '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	[ "His drinks are very inventive , delicious and classy ." ]	[['drinks', 'inventive', 'positive'], ['drinks', 'delicious', 'positive'], ['drinks', 'classy', '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 , great prices , great service ." ]	[['food', 'Great', 'positive'], ['prices', 'great', 'positive'], ['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	[ "Awesome Pizza especially the Margheritta slice ." ]	[['Pizza', 'Awesome', 'positive'], ['Margheritta', '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

[ "The food was average or above including some surprising tasty dishes ." ]

[['food', 'average or above', 'positive'], ['dishes', 'tasty', '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

[ "They do n't seem to place an emphasis on specials or fresh ingredients which to me is necessary for good thai ." ]

[['ingredients', 'good', 'negative'], ['thai', '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

[ "The crust is thin , the ingredients are fresh and the staff is friendly ." ]

[['crust', 'thin', 'positive'], ['staff', 'friendly', 'positive'], ['ingredients', 'fresh', '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 a little more expensive than your average bagel place ." ]

[['bagel', 'expensive', '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 food was undercooked -the sauce watery , and the vegetables raw ." ]

[['food', 'undercooked', 'negative'], ['vegetables', 'raw', 'negative'], ['sauce', 'watery', '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

[ "And the fried clams had just enough kick to them to make 'em worth eating ." ]

[['fried clams', 'enough', '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 sauces used are also not that exciting ." ]

[['sauces', 'not that exciting', '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 secret is the lunch menu which offers a complimentary appetizer with every entree ordered ." ]

[['lunch menu', 'secret', 'positive'], ['appetizer', 'complimentary', 'positive'], ['entree', 'complimentary', '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 shrimp scampi was excellent and the antipasti were plentiful ." ]

[['shrimp scampi', 'excellent', 'positive'], ['antipasti', 'plentiful', '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 got the $ 10 10-piece dim sum combo , every bite of which was great ." ]

[['dim sum combo', '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

[ "There is also very limited seating and there can be a substantial wait in getting food at peak times ." ]

[['seating', 'limited', 'negative'], ['wait', 'substantial', '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 it 's just a quick martini at the bar ( which I recommend Jeffery 's ) or a mind blowing Roast Chicken , go to Village !" ]

[['martini', 'quick', 'neutral'], ['bar', 'recommend', 'neutral'], ['Roast Chicken', 'mind blowing', '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

[ "There was a long wait for a table outside , but it was a little too hot in the sun anyway so our insde table was very nice ." ]

[['table', 'long wait', 'neutral'], ['insde table', 'nice', 'positive'], ['wait', 'long', '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 prices are wonderfully low ." ]

[['prices', 'wonderfully low', '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 never been disappointed but their true strength lays in their amazingly delicious and cheap lunch specials ." ]

[['lunch specials', 'delicious', 'positive'], ['lunch specials', 'cheap', '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

[ "So much more than the usual bar food , go there to enjoy the menu while sampling one of their hand-crafted beers ." ]

[['menu', 'enjoy', 'positive'], ['hand-crafted beers', 'hand-crafted', '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

[ "No free drink ." ]

[['drink', 'No free', '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 is my first time writing a review for a restaurant because the food and service was excellent ." ]

[['food', 'excellent', 'positive'], ['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

[ "Do n't waste money on decor ." ]

[['decor', 'waste', '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

[ "They also have a back garden open in the summer - cute and French with outdoor seating - what more could you ask for ?" ]

[['back garden', 'cute', 'positive'], ['back garden', 'French', '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 never before eaten 40 pieces of relatively good nigiri ." ]

[['nigiri', '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

[ "Given the incredible architecture surrounding it , this place has no character ." ]

[['architecture', 'incredible', 'positive'], ['place', 'no character', '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

[ "While the place is not a hotspot hangout , the drinks are unique and pack a lot of bang for the buck ." ]

[['drinks', '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

[ "Their eggplant is so delicate , sweet tender !" ]

[['eggplant', 'delicate', 'positive'], ['eggplant', 'sweet tender', '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

[ "Each bite of food at Kai was indeed delicious , fresh , and elegant ." ]

[['food', 'delicious', 'positive'], ['food', 'fresh', 'positive'], ['food', 'elegant', '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

[ "all the food was excellent - considering the quality of food in most moderately priced restaurants is mediocre this was slightly more pricey and well worth it ." ]

[['food', 'excellent', 'positive'], ['quality of food', 'mediocre', 'positive'], ['priced', 'moderately', '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 had the cod with paella ( spicy and very filling , I 'm a big eater and could only eat half ) while my boyfriend had the classic fish and chips ( again , a big serving - at least 5 pieces of fish and a basketful of fries ) ." ]

[['cod with paella', 'spicy', 'negative'], ['cod with paella', 'filling', 'negative'], ['fish and chips', 'classic', 'negative'], ['fish and chips', 'big', 'negative'], ['serving', 'big', '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

[ "It 's a shame that a nice , convenient place like the Pink Pony can be so ruined by lousy service ." ]

[['place', 'convenient', 'positive'], ['service', 'lousy', '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 wontons and the salt pepper shrimps ." ]

[['spicy wontons', 'Try', 'positive'], ['salt pepper shrimps', '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 fries are yummy ." ]

[['fries', '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

[ "Friendly and informative staff , very attentive and prompt raw bar service ." ]

[['staff', 'Friendly', 'positive'], ['staff', 'informative', 'positive'], ['staff', 'attentive', 'positive'], ['bar service', 'raw', '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 Taiwanese food in NY !" ]

[['Taiwanese food', '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

[ "This place is a great stop for great food ." ]

[['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

[ "All the pastas are fantastic and the homemade lasagna is some of the best that I have had in the City ." ]

[['pastas', 'fantastic', 'positive'], ['homemade lasagna', '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

[ "And the prices were way to high for what you get ." ]

[['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

[ "The staff ignored my friends and I the entire time we were there ." ]

[['staff', 'ignored', '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

[ "Yet paired with such rude service , would never recommend for anyone interested in carrying any kind of conversation while there ." ]

[['service', 'rude', '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 in-house lady DJ on Saturday nights has outrageously good taste in music , and moreover , takes requests ." ]

[['in-house lady DJ', 'good taste', '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 wine list , reasonably priced . -- Sara" ]

[['wine list', 'Great', 'positive'], ['priced', 'reasonably', '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 hot dogs were cold in the middle and the buns were stale ." ]

[['hot dogs', 'cold', 'negative'], ['buns', 'stale', '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

[ "While the food was excellent , it was n't cheap ( though not extremely expensive either ) ." ]

[['food', '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

[ "Beef noodle soup is good as well ." ]

[['Beef noodle soup', '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

[ "Delivery service is great too ." ]

[['Delivery 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

[ "The food 's dazzling flavors overwhelm the palate , truly embracing the beauty of authentic Thai cuisine ." ]

[['food', 'overwhelm', 'positive'], ['Thai cuisine', 'authentic', 'positive'], ['flavors', 'overwhelm', '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 recieved prompt service with a smile ." ]

[['service', 'prompt', '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

[ "They pray to their Food Gods to make them into a good pizza like VT 's ." ]

[['pizza', 'good', '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 place was quiet and delightful ." ]

[['place', 'quiet', 'positive'], ['place', 'delightful', '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 a diamond in rough -- the food is delicious and homemade with the perfect balance of herbs and tomatoes ." ]

[['food', 'diamond', 'positive'], ['food', 'delicious', 'positive'], ['food', 'homemade', 'positive'], ['herbs', 'perfect', 'positive'], ['tomatoes', '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

[ "As much as I like the food there , I ca n't bring myself to go back ." ]

[['food', '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

[ "The prices and ambience are especially great considering it 's in the West Village ." ]

[['prices', 'great', 'positive'], ['ambience', '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 soup is pretty good too ." ]

[['soup', '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

[ "It is so easy to get a reservation at a top place in NYC with a week 's notice ." ]

[['reservation', '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

[ "not the food , not the ambiance , not the service , I agree with the previous reviews you wait and wait , the wait staff are very rude and when you get in they are looking to get you right out ." ]

[['wait staff', 'rude', '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 always get the Shabu-Shabu dinner and the beef is always fresh ." ]

[['beef', 'fresh', '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 delivered cold and the cheese was n't even fully melted !" ]

[['pizza', 'cold', 'negative'], ['cheese', "was n't even fully melted", '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 very surprised by how good the food was on our first visit here on a Sunday night ." ]

[['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

[ "Nha Trang , while being notorious for utter lack of comfort and decor , horribly slow wait staff and horribly quick meals , is one of the best vietnamese restaurants i 've ever been to . the pho is delicious and comes with very fresh vegtables ." ]

[['comfort', 'lack', 'negative'], ['decor', 'lack', 'negative'], ['wait staff', 'horribly slow', 'negative'], ['meals', 'horribly quick', 'negative'], ['pho', 'delicious', 'positive'], ['vegtables', 'fresh', '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

[ "On the other hand , if you are not fooled easily , you will find hundreds of restaurants that will give you service and ambiance that is on par with Alain Ducasse , and food that will outshine in presentaion , taste , choice , quality and quantity ." ]

[['service', 'on par', 'neutral'], ['ambiance', 'on par', 'neutral'], ['food', 'outshine', '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 I could rate the people this place would be off the charts - unfortunately - the pizza , sorry - not the best in NYC ." ]

[['people', 'best', 'positive'], ['pizza', 'best', '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

[ "Having not been home in the last 2 years may skew this reviewer a bit , but the food was tasty and spicy sans the oil that comes floating along at similar venues ." ]

[['food', 'tasty', 'positive'], ['food', 'spicy', '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 portions are now very small , the sauces are overly ambitious usually inedible while the service is still good , the restaurant , due to its popularity , seems frantic ." ]

[['portions', 'small', 'negative'], ['sauces', 'ambitious', 'negative'], ['sauces', 'inedible', 'negative'], ['service', '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 owner is very friendly and a great guy , go try his pizza , you 'll like it !" ]

[['owner', 'friendly', 'positive'], ['owner', 'great', 'positive'], ['pizza', 'try', 'positive'], ['pizza', '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

[ "The atmosphere is great ! ! !" ]

[['atmosphere', '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

[ "With so many good restaurants on the UWS , I do n't need overpriced food , absurdly arrogant wait-staff who do n't recognize they work at a glorified diner , clumsy service , and management that does n't care ." ]

[['food', 'overpriced', 'negative'], ['wait-staff', 'arrogant', 'negative'], ['service', 'clumsy', 'negative'], ['management', "does n't care", 'negative'], ['diner', 'glorified', '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 tend to judge a sushi restaurant by its sea urchin , which was heavenly at sushi rose ." ]

[['sea urchin', 'heavenly', '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 a little scatty at times but all is forgiven when the food arrives ." ]

[['service', 'scatty', 'negative'], ['food', 'forgiven', '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 bruscetta is a bit soggy , but the salads were fresh , included a nice mix of greens ( not iceberg ) all dishes are served piping hot from the kitchen ." ]

[['bruscetta', 'soggy', 'negative'], ['salads', 'fresh', 'positive'], ['dishes', 'hot', 'positive'], ['mix of greens', '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 atmosphere is n't the greatest , but I suppose that 's how they keep the prices down ." ]

[['atmosphere', "is n't the greatest", 'neutral'], ['prices', 'down', '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 pickles were great addition ." ]

[['pickles', '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

[ "If your favorite Chinese food is General Tao chicken , then this is NOT your place ." ]

[['General Tao chicken', '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

[ "You must try the shrimp appetizers ." ]

[['shrimp appetizers', '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

[ "Not only is the cuisine the best around , the service has always been attentive and charming ." ]

[['cuisine', 'best', 'positive'], ['service', 'attentive', 'positive'], ['service', 'charming', '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 production is a symphony , alot of fun to experience.The food sublime for the most part ." ]

[['food', 'sublime', '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

[ "Waiters tend to forget drinks completely , food portions are so tiny , two people have trouble sharing one entree ." ]

[['Waiters', 'forget', 'negative'], ['food portions', 'tiny', 'negative'], ['drinks', 'forget', 'neutral'], ['entree', 'trouble', '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

[ "But the thing that my wife and I hated was it was so loud and it felt like ' bar ' or ' pub ' ." ]

[['bar', 'loud', 'negative'], ['pub', 'loud', '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

[ "While there are plenty of places to go for a good corned beef sandwich , Katz 's has a charm about it ." ]

[['corned beef sandwich', '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

[ "However , looking at the table next to ours , we both sort of wished we had ordered pizza , which looked perfect" ]

[['pizza', '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

[ "Priced at upper intermediate range ." ]

[['Priced', 'upper intermediate', '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 you live in new york city , you 'll find better food at small restaurants outside of time square and spend half the amount ." ]

[['food', 'better', '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

[ "they did n't disappoint , service from the second i arrived at the door was extremely pleasant and attentive with almost one server per table ." ]

[['service', 'pleasant', 'positive'], ['service', 'attentive', '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 do n't know who they think they are but they have no respect for the residents of the neighborhood ever since they opened their cabaret next door and blasts loud music till three in the morning every weekend during the summer ." ]

[['music', 'loud', '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 only positive was the wait staff , which was prompt , knowledgable , and likeable ." ]

[['wait staff', 'positive', 'positive'], ['wait staff', 'prompt', 'positive'], ['wait staff', 'knowledgable', 'positive'], ['wait staff', 'likeable', '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 am not a vegetarian but , almost all the dishes were great ." ]

[['dishes', '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 was very impressed by this low-key upper eastsider and their authentically thai cuisine ! ! !" ]

[['thai cuisine', 'authentically', '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 the location , the prices are very reasonable ." ]

[['prices', 'reasonable', 'positive'], ['location', 'reasonable', '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 food is okay and the prices here are mediocre ." ]

[['food', 'okay', 'neutral'], ['prices', 'mediocre', '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

[ "My friend 's food was also the complete opposite of what it 's supposed to taste like ( aND look like ) ." ]

[['food', 'opposite', '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 have been to this place many times , and always have great food , wine , and service ." ]

[['food', 'great', 'positive'], ['wine', 'great', 'positive'], ['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

[ "Not a typical pizza joint , but good for a low key and fairly cheap nice sit down dinner ." ]

[['dinner', 'cheap 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 corned beef was tender and melted in my mouth ." ]

[['corned beef', 'tender', 'positive'], ['corned beef', 'melted', '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 best Chicken pad tai , I 've ever had ." ]

[['Chicken pad tai', '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

[ "$ 20 for all you can eat sushi can not be beaten ." ]

[['sushi', 'can not be beaten', '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

[ "Haru serves very fresh fish , has a trendy , modern ambiance , prime location on Park Avenue South and friendly service ." ]

[['fish', 'fresh', 'positive'], ['service', 'friendly', 'positive'], ['ambiance', 'trendy', 'positive'], ['ambiance', 'modern', 'positive'], ['location', 'prime', '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

[ "Warm and friendly in the winter and terrific outdoor seating in the warmer months ." ]

[['outdoor seating', 'terrific', '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

[ "Very romantic fires - I 've literally spent hours at Lanterna , drinking wine from their extensive wine and enjoying the ambience ." ]

[['wine', 'extensive', 'positive'], ['ambience', 'enjoying', '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 got a little tipsy from the sake but is n't that what Saturday nights with the girlfriends are all about ?" ]

[['sake', 'tipsy', '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

[ "My turkey burger was not cooked at all , my friends salmon was completely raw ." ]

[['turkey burger', 'not cooked', 'negative'], ['salmon', 'raw', '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

[ "His drinks are very inventive , delicious and classy ." ]

[['drinks', 'inventive', 'positive'], ['drinks', 'delicious', 'positive'], ['drinks', 'classy', '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 , great prices , great service ." ]

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

[ "Awesome Pizza especially the Margheritta slice ." ]

[['Pizza', 'Awesome', 'positive'], ['Margheritta', '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']]