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	[ "I only tried a simple dish of spinach ravioli in a light oil and garlic sauce , but it actually faired better than most NYC Italian joints I 've tried similar dishes at ." ]	[['spinach ravioli in a light oil and garlic sauce', 'better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The worst excuse for Japanese food I 've ever encountered ." ]	[['Japanese food', 'worst', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We had Pam 's special fried fish and it was amazing ." ]	[["Pam 's special fried fish", 'amazing', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque ." ]	[['New England Chowder', 'good', 'positive'], ['Lobster Bisque', 'award', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 enough wines by the glass either ." ]	[['wines by the glass', 'Not enough', '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 must say it 's a little pricey for the food because it was not as spectacular as the view ." ]	[['food', 'pricey', '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 worried we would have trouble getting in , but somehow managed to have a short wait ." ]	[['wait', 'short', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My wife had the fried shrimp which are huge and loved it ." ]	[['fried shrimp', 'huge', 'positive'], ['fried shrimp', 'loved', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service is awful -- the last time I was there ( and I do mean the last time ) we were told that they needed our table so we would have to leave ." ]	[['service', 'awful', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Try the green curry ! ! !" ]	[['green curry', '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	[ "We had the scallops as an appetizer and they were delicious and the sauce was wonderful ." ]	[['scallops', 'delicious', 'positive'], ['appetizer', 'delicious', 'positive'], ['sauce', 'wonderful', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "We were also seated promptly at the time of our reservation and the service was very quick and professional ." ]	[['service', 'quick', 'positive'], ['service', 'professional', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food there are sastifying ." ]	[['food', 'sastifying', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 highly recommend visiting this restaurant and having dinner and drinks !" ]	[['dinner', 'recommend', 'positive'], ['drinks', 'recommend', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Great wine selection , Gigondas is worth the price , and the house champagne is a great value ." ]	[['wine selection', 'Great', 'positive'], ['Gigondas', 'worth the price', 'positive'], ['house champagne', 'great value', 'positive'], ['price', 'worth', '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	[ "at night , but it 's hard to hear your own conversation with everyone else competing for that same luxury - the music playing in the background is also voluminous ." ]	[['music', 'voluminous', '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 particularly love their yellowfun tuna and their mussel selection ." ]	[['yellowfun tuna', 'love', 'positive'], ['mussel selection', 'love', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "I love to visit Murrays for my bagel fix ." ]	[['bagel', 'love', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 made early dinner reservations and were thoroughly impressed , reminds me of my grandfather , its old school Italian scenery with lots of fun stuff to admire ." ]	[['scenery', 'fun', 'positive'], ['dinner reservations', 'early', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Cheese plate is a varied delight and great bargain at $ 10 ." ]	[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Most of the servers are very attentive , friendly and quite attractive ." ]	[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive'], ['servers', 'attractive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service is average ." ]	[['Service', 'average', '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	[ "But they 've done a really nice job of offering all the typical pizzeria faves plus some terrific specials like the Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual ) ." ]	[['Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual )', 'terrific', 'positive'], ['specials', 'terrific', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 steak is good , the fish is good and the sushi was surprisingly great ." ]	[['steak', 'good', 'positive'], ['fish', 'good', 'positive'], ['sushi', '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 service was poor , restaurant poorly lit , staff not very attentive and I would have rather eaten at a Mcdonald 's than this joint ." ]	[['service', 'poor', 'negative'], ['staff', 'not very attentive', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "My GF and I still choose to eat there a lot because of diverse cocktails , the chill decor , and the decent sushi ." ]	[['cocktails', 'diverse', 'positive'], ['decor', 'chill', 'positive'], ['sushi', 'decent', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 ended the dinner with a surprisingly light and flaky apple tarte tatin ." ]	[['apple tarte tatin', 'flaky', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 buffet had a nice selection ." ]	[['buffet', 'nice', 'positive'], ['selection', '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	[ "Waitstaff are very friendly ." ]	[['Waitstaff', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Service was slow had to wait to order and get food although not crowded ." ]	[['Service', 'slow', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The food was below average , the service was pathetic , there was no ambience at all ." ]	[['food', 'below average', 'negative'], ['service', 'pathetic', 'negative'], ['ambience', 'no', '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 REALLY ENJOYED THE SHOWS PUT ON BY THE ACTORS ." ]	[['SHOWS', 'ENJOYED', 'positive'], ['ACTORS', 'ENJOYED', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "service was efficient courteous ." ]	[['service', 'efficient courteous', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 miso soup lacked flavor and the fish was unfortunately not as well prepared as in the past ." ]	[['miso soup', 'lacked flavor', 'negative'], ['fish', 'unfortunately', 'negative'], ['flavor', 'lacked', '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 are the best bagels I 've had ." ]	[['bagels', '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	[ "Toons has recently been redone , so it 's now a very attractive space ." ]	[['space', 'attractive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 prices are nothing special , the portions are huge ." ]	[['prices', 'special', 'neutral'], ['portions', 'special', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Its a nice quiet location to go eat a good meal , relax , be able to talk and have a very good time ." ]	[['location', 'nice quiet', 'positive'], ['meal', '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 , I think this place is a good hang out spot ." ]	[['spot', '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 wine list is extensive and impressive ." ]	[['wine list', 'extensive', 'positive'], ['wine list', 'impressive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 staff at this little bistro is very friendly , I have never experienced more incompetency ." ]	[['staff', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The quail was fantastic and unique and the pastas were full of flavor ." ]	[['quail', 'fantastic', 'positive'], ['quail', 'unique', 'positive'], ['pastas', 'full', 'positive'], ['flavor', 'full', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The staff is courteous and friendly ." ]	[['staff', 'courteous', 'positive'], ['staff', 'friendly', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Aside from the rushed service , we were very impressed with the food and the drinks ." ]	[['service', 'rushed', 'negative'], ['food', 'impressed', 'positive'], ['drinks', 'impressed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 would highly recommend this place to anyone who is looking for a fine Indian dining experience that is definitely a value for your dollar ." ]	[['Indian dining experience', 'fine', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "This big draw is the all you can sushi here for $ 19.95 !" ]	[['sushi', 'draw', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Some of the workers ignore me and talk to the female customers , other times , they 've skipped my order ." ]	[['workers', 'ignore', 'negative'], ['order', 'skipped', '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 specials are usually quite good too ." ]	[['specials', '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	[ "They 've the best desserts and mixed drinks as well as snack foods ." ]	[['desserts', 'best', 'positive'], ['mixed drinks', 'best', 'positive'], ['snack foods', '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	[ "Really cool stauff inside ." ]	[['stauff', 'cool', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 new restaurant still features much of the same classical furniture that made Tiffin so attractive , the menu has been overhauled ." ]	[['classical furniture', 'classical', 'positive'], ['menu', 'overhauled', '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 best burger I have had in the Village ." ]	[['burger', '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	[ "Only drawback - they wo n't toast your bagel , and they do n't make eggs for the bagel ." ]	[['bagel', 'drawback', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "As always we had a great glass of wine while we waited ." ]	[['glass of wine', '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 wait staff is pleasant , fun , and for the most part gorgeous ( in the wonderful aesthetic beautification way , not in that she's-way-cuter-than-me-that-b @ # $ * way ) ." ]	[['wait staff', 'pleasant', 'positive'], ['wait staff', 'fun', 'positive'], ['wait staff', 'gorgeous', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Of course this atmosphere is lacking , but what do you expect from a 24 hour bagel place anyways ?" ]	[['atmosphere', 'lacking', '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	[ "Service was very good and warm ." ]	[['Service', 'good', 'positive'], ['Service', 'warm', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really ca n't top the setting for a romantic dinner in NYC ." ]	[['dinner', 'romantic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Food was good and the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went ." ]	[['Food', 'good', 'positive'], ['view', '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	[ "The food is decent at best , and the ambience , well , it 's a matter of opinion , some may consider it to be a sweet thing , I thought it was just annoying ." ]	[['food', 'decent', '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 service was a bit slow , but they were very friendly ." ]	[['service', 'slow', 'negative'], ['service', 'friendly', '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	[ "Leon is an East Village gem : casual but hip , with well prepared basic French bistro fare , good specials , a warm and lively atmosphere ." ]	[['specials', 'good', 'positive'], ['atmosphere', 'warm', 'positive'], ['atmosphere', 'lively', 'positive'], ['French bistro fare', 'well prepared', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 above average for midtown and sligtly better than some of the other Heartland Breweries in the city ." ]	[['food', 'above average', 'positive'], ['food', 'better', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Thius is a must for anyone who loves Shabu-Shabu ." ]	[['Shabu-Shabu', 'loves', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 absolutely horrible !" ]	[['food', 'horrible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Similar to other Indian restaurants , they use the dinner special to attract customers at the door ." ]	[['dinner special', 'attract', '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 people with carts of food do n't understand you because they do n't speak English , their job is to give you the delicious food you point at ." ]	[['food', 'delicious', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The crackling calamari salad , which is usually a cheap disaster at many restaurants , is crispy and lightly dressed ." ]	[['crackling calamari salad', 'crispy', 'positive'], ['crackling calamari salad', 'lightly dressed', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 greatest sushi place , but excellent for a $ 19.95 all you can eat ." ]	[['sushi place', 'Not the greatest', 'negative'], ['sushi place', 'excellent', '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	[ "Shockingly easy to throw a group dinner here : simple contract , deposit only to hold the date the entire 2nd fl mezz for our grp of 20 ." ]	[['group dinner', 'easy', '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 Thai ice tea was amazingly smooth and yummy !" ]	[['Thai ice tea', 'smooth', 'positive'], ['Thai ice tea', '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	[ "Drinks way over priced ." ]	[['Drinks', 'over priced', 'negative'], ['priced', 'over', '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 main downside to the place is the nazi-like guy running it who constantly complains about the noise level ." ]	[['noise level', 'downside', 'negative'], ['guy', 'downside', '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	[ "Moderate prices ." ]	[['prices', 'Moderate', '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 think I 've had some the best meals of my life at minnow ." ]	[['meals', '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	[ "Most importantly , food is excellent ." ]	[['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	[ "Great roofdeck , nice group of 30 somethings , but no music , kind of quiet ." ]	[['roofdeck', 'Great', 'positive'], ['music', 'no', 'negative'], ['music', 'quiet', '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	[ "However , service was as plain as sesame crusted Salmon I had ." ]	[['service', 'plain', 'neutral'], ['sesame crusted Salmon', 'plain', 'neutral']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "It 's great to go for a quick lunch either alone or with a friend ." ]	[['lunch', 'quick', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 mediocre at best but it was the horrible service that made me vow never to go back ." ]	[['food', 'mediocre', 'neutral'], ['service', 'horrible', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "You get what you pay for and with that logic in mind , Spice is a great place to grab some cheap eats and drinks in a beautiful setting ." ]	[['eats', 'cheap', 'positive'], ['drinks', 'cheap', 'positive'], ['setting', 'beautiful', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The service was terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ." ]	[['service', 'terrible', '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	[ "Other than being a little crowded and a bit overpriced , the atmosphere is filled with energy ( and the beautiful people of course ) and the food was surprising good !" ]	[['atmosphere', 'energy', 'positive'], ['people', 'beautiful', 'positive'], ['food', 'surprising 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 music is the best among all the Indian restaurants I have visited ." ]	[['music', 'best', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "The bread and lamb chops I had before the meal were quite good , however ." ]	[['bread', 'good', 'positive'], ['lamb chops', '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	[ "Rao 's has the best service and atmosphere in NYC ." ]	[['service', 'best', 'positive'], ['atmosphere', '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	[ "They never brought us complimentary noodles , ignored repeated requests for sugar , and threw our dishes on the table ." ]	[['noodles', 'complimentary', 'negative'], ['sugar', 'ignored', 'negative'], ['dishes', 'threw', '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	[ "Excellent dumplings served amid clean , chic decor ." ]	[['dumplings', 'Excellent', 'positive'], ['decor', 'clean', 'positive'], ['decor', 'chic', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 kitchen however , is almost always slow ." ]	[['kitchen', 'slow', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Cute place , nice wait staff but would never go there again ." ]	[['wait staff', 'nice', 'positive'], ['place', 'Cute', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "people are rude bit again it 's new york !" ]	[['people', '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 plain slice is great and if you get toppings , the whole slice is topped with them , not sparsely sprinkled on like some places ." ]	[['plain slice', '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	[ "Service was also horrible and the ambience is not that great ." ]	[['Service', 'horrible', 'negative'], ['ambience', 'not that great', '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	[ "Service is great , takeout is good too ." ]	[['Service', 'great', 'positive'], ['takeout', '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	[ "Everything is excellent , the menu is quite extensive , and you eat with a view on both sides of the city ." ]	[['menu', 'extensive', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 quality of food , a little too expensive ." ]	[['quality of food', 'expensive', 'negative']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "Here 's to the fake fish tanks too ..." ]	[['fish tanks', 'fake', '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 've never had bad service and the fish is fresh and delicious ." ]	[['service', 'never had bad', 'positive'], ['fish', 'fresh', 'positive'], ['fish', 'delicious', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "we decided to eat in tea room which was small and cute ." ]	[['tea room', 'small', 'positive'], ['tea room', 'cute', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "It has so much more speed and the screen is very sharp ." Output: [['speed', 'much more', 'positive'], ['screen', 'sharp', 'positive']]
generation	aste-data-v2	[ "What an amazing meal and experience !" ]	[['meal', 'amazing', 'positive']]	none	Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 only tried a simple dish of spinach ravioli in a light oil and garlic sauce , but it actually faired better than most NYC Italian joints I 've tried similar dishes at ." ]

[['spinach ravioli in a light oil and garlic sauce', 'better', 'positive']]

none

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

generation

aste-data-v2

[ "The worst excuse for Japanese food I 've ever encountered ." ]

[['Japanese food', 'worst', 'negative']]

none

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

generation

aste-data-v2

[ "We had Pam 's special fried fish and it was amazing ." ]

[["Pam 's special fried fish", 'amazing', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 boyfriend had the New England Chowder it was good but I think the award should go to the Lobster Bisque ." ]

[['New England Chowder', 'good', 'positive'], ['Lobster Bisque', 'award', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 enough wines by the glass either ." ]

[['wines by the glass', 'Not enough', '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 must say it 's a little pricey for the food because it was not as spectacular as the view ." ]

[['food', 'pricey', '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 worried we would have trouble getting in , but somehow managed to have a short wait ." ]

[['wait', 'short', 'positive']]

none

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

generation

aste-data-v2

[ "My wife had the fried shrimp which are huge and loved it ." ]

[['fried shrimp', 'huge', 'positive'], ['fried shrimp', 'loved', 'positive']]

none

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

generation

aste-data-v2

[ "The service is awful -- the last time I was there ( and I do mean the last time ) we were told that they needed our table so we would have to leave ." ]

[['service', 'awful', 'negative']]

none

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

generation

aste-data-v2

[ "Try the green curry ! ! !" ]

[['green curry', '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

[ "We had the scallops as an appetizer and they were delicious and the sauce was wonderful ." ]

[['scallops', 'delicious', 'positive'], ['appetizer', 'delicious', 'positive'], ['sauce', 'wonderful', 'positive']]

none

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

generation

aste-data-v2

[ "We were also seated promptly at the time of our reservation and the service was very quick and professional ." ]

[['service', 'quick', 'positive'], ['service', 'professional', 'positive']]

none

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

generation

aste-data-v2

[ "The food there are sastifying ." ]

[['food', 'sastifying', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 highly recommend visiting this restaurant and having dinner and drinks !" ]

[['dinner', 'recommend', 'positive'], ['drinks', 'recommend', 'positive']]

none

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

generation

aste-data-v2

[ "Great wine selection , Gigondas is worth the price , and the house champagne is a great value ." ]

[['wine selection', 'Great', 'positive'], ['Gigondas', 'worth the price', 'positive'], ['house champagne', 'great value', 'positive'], ['price', 'worth', '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

[ "at night , but it 's hard to hear your own conversation with everyone else competing for that same luxury - the music playing in the background is also voluminous ." ]

[['music', 'voluminous', '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 particularly love their yellowfun tuna and their mussel selection ." ]

[['yellowfun tuna', 'love', 'positive'], ['mussel selection', 'love', 'positive']]

none

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

generation

aste-data-v2

[ "I love to visit Murrays for my bagel fix ." ]

[['bagel', 'love', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 made early dinner reservations and were thoroughly impressed , reminds me of my grandfather , its old school Italian scenery with lots of fun stuff to admire ." ]

[['scenery', 'fun', 'positive'], ['dinner reservations', 'early', 'positive']]

none

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

generation

aste-data-v2

[ "Cheese plate is a varied delight and great bargain at $ 10 ." ]

[['Cheese plate', 'varied delight', 'positive'], ['Cheese plate', 'great bargain', 'positive']]

none

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

generation

aste-data-v2

[ "Most of the servers are very attentive , friendly and quite attractive ." ]

[['servers', 'attentive', 'positive'], ['servers', 'friendly', 'positive'], ['servers', 'attractive', 'positive']]

none

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

generation

aste-data-v2

[ "Service is average ." ]

[['Service', 'average', '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

[ "But they 've done a really nice job of offering all the typical pizzeria faves plus some terrific specials like the Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual ) ." ]

[['Godmother pizza ( a sort of traditional flat pizza with an olive oil-brushed crust and less tomato sauce than usual )', 'terrific', 'positive'], ['specials', 'terrific', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 steak is good , the fish is good and the sushi was surprisingly great ." ]

[['steak', 'good', 'positive'], ['fish', 'good', 'positive'], ['sushi', '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 service was poor , restaurant poorly lit , staff not very attentive and I would have rather eaten at a Mcdonald 's than this joint ." ]

[['service', 'poor', 'negative'], ['staff', 'not very attentive', 'negative']]

none

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

generation

aste-data-v2

[ "My GF and I still choose to eat there a lot because of diverse cocktails , the chill decor , and the decent sushi ." ]

[['cocktails', 'diverse', 'positive'], ['decor', 'chill', 'positive'], ['sushi', 'decent', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 ended the dinner with a surprisingly light and flaky apple tarte tatin ." ]

[['apple tarte tatin', 'flaky', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 buffet had a nice selection ." ]

[['buffet', 'nice', 'positive'], ['selection', '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

[ "Waitstaff are very friendly ." ]

[['Waitstaff', 'friendly', 'positive']]

none

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

generation

aste-data-v2

[ "Service was slow had to wait to order and get food although not crowded ." ]

[['Service', 'slow', 'negative']]

none

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

generation

aste-data-v2

[ "The food was below average , the service was pathetic , there was no ambience at all ." ]

[['food', 'below average', 'negative'], ['service', 'pathetic', 'negative'], ['ambience', 'no', '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 REALLY ENJOYED THE SHOWS PUT ON BY THE ACTORS ." ]

[['SHOWS', 'ENJOYED', 'positive'], ['ACTORS', 'ENJOYED', 'positive']]

none

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

generation

aste-data-v2

[ "service was efficient courteous ." ]

[['service', 'efficient courteous', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 miso soup lacked flavor and the fish was unfortunately not as well prepared as in the past ." ]

[['miso soup', 'lacked flavor', 'negative'], ['fish', 'unfortunately', 'negative'], ['flavor', 'lacked', '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 are the best bagels I 've had ." ]

[['bagels', '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

[ "Toons has recently been redone , so it 's now a very attractive space ." ]

[['space', 'attractive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 prices are nothing special , the portions are huge ." ]

[['prices', 'special', 'neutral'], ['portions', 'special', 'positive']]

none

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

generation

aste-data-v2

[ "Its a nice quiet location to go eat a good meal , relax , be able to talk and have a very good time ." ]

[['location', 'nice quiet', 'positive'], ['meal', '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 , I think this place is a good hang out spot ." ]

[['spot', '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 wine list is extensive and impressive ." ]

[['wine list', 'extensive', 'positive'], ['wine list', 'impressive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 staff at this little bistro is very friendly , I have never experienced more incompetency ." ]

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

none

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

generation

aste-data-v2

[ "The quail was fantastic and unique and the pastas were full of flavor ." ]

[['quail', 'fantastic', 'positive'], ['quail', 'unique', 'positive'], ['pastas', 'full', 'positive'], ['flavor', 'full', 'positive']]

none

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

generation

aste-data-v2

[ "The staff is courteous and friendly ." ]

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

none

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

generation

aste-data-v2

[ "Aside from the rushed service , we were very impressed with the food and the drinks ." ]

[['service', 'rushed', 'negative'], ['food', 'impressed', 'positive'], ['drinks', 'impressed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 would highly recommend this place to anyone who is looking for a fine Indian dining experience that is definitely a value for your dollar ." ]

[['Indian dining experience', 'fine', 'positive']]

none

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

generation

aste-data-v2

[ "This big draw is the all you can sushi here for $ 19.95 !" ]

[['sushi', 'draw', 'positive']]

none

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

generation

aste-data-v2

[ "Some of the workers ignore me and talk to the female customers , other times , they 've skipped my order ." ]

[['workers', 'ignore', 'negative'], ['order', 'skipped', '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 specials are usually quite good too ." ]

[['specials', '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

[ "They 've the best desserts and mixed drinks as well as snack foods ." ]

[['desserts', 'best', 'positive'], ['mixed drinks', 'best', 'positive'], ['snack foods', '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

[ "Really cool stauff inside ." ]

[['stauff', 'cool', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 new restaurant still features much of the same classical furniture that made Tiffin so attractive , the menu has been overhauled ." ]

[['classical furniture', 'classical', 'positive'], ['menu', 'overhauled', '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 best burger I have had in the Village ." ]

[['burger', '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

[ "Only drawback - they wo n't toast your bagel , and they do n't make eggs for the bagel ." ]

[['bagel', 'drawback', 'negative']]

none

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

generation

aste-data-v2

[ "As always we had a great glass of wine while we waited ." ]

[['glass of wine', '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 wait staff is pleasant , fun , and for the most part gorgeous ( in the wonderful aesthetic beautification way , not in that she's-way-cuter-than-me-that-b @ # $ * way ) ." ]

[['wait staff', 'pleasant', 'positive'], ['wait staff', 'fun', 'positive'], ['wait staff', 'gorgeous', 'positive']]

none

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

generation

aste-data-v2

[ "Of course this atmosphere is lacking , but what do you expect from a 24 hour bagel place anyways ?" ]

[['atmosphere', 'lacking', '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

[ "Service was very good and warm ." ]

[['Service', 'good', 'positive'], ['Service', 'warm', 'positive']]

none

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

generation

aste-data-v2

[ "Cornelia Street looks like a Broadway set for West Side Story and the inside of Po is so cool quaint you really ca n't top the setting for a romantic dinner in NYC ." ]

[['dinner', 'romantic', 'positive']]

none

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

generation

aste-data-v2

[ "Food was good and the view of the new york city skiline was terrific even on a foggy rainy day like that of when I went ." ]

[['Food', 'good', 'positive'], ['view', '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

[ "The food is decent at best , and the ambience , well , it 's a matter of opinion , some may consider it to be a sweet thing , I thought it was just annoying ." ]

[['food', 'decent', '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 service was a bit slow , but they were very friendly ." ]

[['service', 'slow', 'negative'], ['service', 'friendly', '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

[ "Leon is an East Village gem : casual but hip , with well prepared basic French bistro fare , good specials , a warm and lively atmosphere ." ]

[['specials', 'good', 'positive'], ['atmosphere', 'warm', 'positive'], ['atmosphere', 'lively', 'positive'], ['French bistro fare', 'well prepared', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 above average for midtown and sligtly better than some of the other Heartland Breweries in the city ." ]

[['food', 'above average', 'positive'], ['food', 'better', 'positive']]

none

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

generation

aste-data-v2

[ "Thius is a must for anyone who loves Shabu-Shabu ." ]

[['Shabu-Shabu', 'loves', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 absolutely horrible !" ]

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

none

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

generation

aste-data-v2

[ "Similar to other Indian restaurants , they use the dinner special to attract customers at the door ." ]

[['dinner special', 'attract', '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 people with carts of food do n't understand you because they do n't speak English , their job is to give you the delicious food you point at ." ]

[['food', 'delicious', 'positive']]

none

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

generation

aste-data-v2

[ "The crackling calamari salad , which is usually a cheap disaster at many restaurants , is crispy and lightly dressed ." ]

[['crackling calamari salad', 'crispy', 'positive'], ['crackling calamari salad', 'lightly dressed', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 greatest sushi place , but excellent for a $ 19.95 all you can eat ." ]

[['sushi place', 'Not the greatest', 'negative'], ['sushi place', 'excellent', '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

[ "Shockingly easy to throw a group dinner here : simple contract , deposit only to hold the date the entire 2nd fl mezz for our grp of 20 ." ]

[['group dinner', 'easy', '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 Thai ice tea was amazingly smooth and yummy !" ]

[['Thai ice tea', 'smooth', 'positive'], ['Thai ice tea', '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

[ "Drinks way over priced ." ]

[['Drinks', 'over priced', 'negative'], ['priced', 'over', '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 main downside to the place is the nazi-like guy running it who constantly complains about the noise level ." ]

[['noise level', 'downside', 'negative'], ['guy', 'downside', '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

[ "Moderate prices ." ]

[['prices', 'Moderate', '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 think I 've had some the best meals of my life at minnow ." ]

[['meals', '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

[ "Most importantly , food is excellent ." ]

[['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

[ "Great roofdeck , nice group of 30 somethings , but no music , kind of quiet ." ]

[['roofdeck', 'Great', 'positive'], ['music', 'no', 'negative'], ['music', 'quiet', '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

[ "However , service was as plain as sesame crusted Salmon I had ." ]

[['service', 'plain', 'neutral'], ['sesame crusted Salmon', 'plain', 'neutral']]

none

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

generation

aste-data-v2

[ "It 's great to go for a quick lunch either alone or with a friend ." ]

[['lunch', 'quick', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 mediocre at best but it was the horrible service that made me vow never to go back ." ]

[['food', 'mediocre', 'neutral'], ['service', 'horrible', 'negative']]

none

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

generation

aste-data-v2

[ "You get what you pay for and with that logic in mind , Spice is a great place to grab some cheap eats and drinks in a beautiful setting ." ]

[['eats', 'cheap', 'positive'], ['drinks', 'cheap', 'positive'], ['setting', 'beautiful', 'positive']]

none

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

generation

aste-data-v2

[ "The service was terrible , we had to wait for everything and ask several of different people for the same thing before we were allowed to be served ." ]

[['service', 'terrible', '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

[ "Other than being a little crowded and a bit overpriced , the atmosphere is filled with energy ( and the beautiful people of course ) and the food was surprising good !" ]

[['atmosphere', 'energy', 'positive'], ['people', 'beautiful', 'positive'], ['food', 'surprising 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 music is the best among all the Indian restaurants I have visited ." ]

[['music', 'best', 'positive']]

none

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

generation

aste-data-v2

[ "The bread and lamb chops I had before the meal were quite good , however ." ]

[['bread', 'good', 'positive'], ['lamb chops', '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

[ "Rao 's has the best service and atmosphere in NYC ." ]

[['service', 'best', 'positive'], ['atmosphere', '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

[ "They never brought us complimentary noodles , ignored repeated requests for sugar , and threw our dishes on the table ." ]

[['noodles', 'complimentary', 'negative'], ['sugar', 'ignored', 'negative'], ['dishes', 'threw', '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

[ "Excellent dumplings served amid clean , chic decor ." ]

[['dumplings', 'Excellent', 'positive'], ['decor', 'clean', 'positive'], ['decor', 'chic', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 kitchen however , is almost always slow ." ]

[['kitchen', 'slow', 'negative']]

none

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

generation

aste-data-v2

[ "Cute place , nice wait staff but would never go there again ." ]

[['wait staff', 'nice', 'positive'], ['place', 'Cute', 'positive']]

none

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

generation

aste-data-v2

[ "people are rude bit again it 's new york !" ]

[['people', '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 plain slice is great and if you get toppings , the whole slice is topped with them , not sparsely sprinkled on like some places ." ]

[['plain slice', '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

[ "Service was also horrible and the ambience is not that great ." ]

[['Service', 'horrible', 'negative'], ['ambience', 'not that great', '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

[ "Service is great , takeout is good too ." ]

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

[ "Everything is excellent , the menu is quite extensive , and you eat with a view on both sides of the city ." ]

[['menu', 'extensive', 'positive']]

none

Task: Extracting aspect terms ,their opinion words and their corresponding sentiment polarities. Input: A sentence. Output: A list of 3-tuples, where each tuple contains the extracted aspect term ,their opinion words and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "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 quality of food , a little too expensive ." ]

[['quality of food', 'expensive', 'negative']]

none

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

generation

aste-data-v2

[ "Here 's to the fake fish tanks too ..." ]

[['fish tanks', 'fake', '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 've never had bad service and the fish is fresh and delicious ." ]

[['service', 'never had bad', 'positive'], ['fish', 'fresh', 'positive'], ['fish', 'delicious', 'positive']]

none

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

generation

aste-data-v2

[ "we decided to eat in tea room which was small and cute ." ]

[['tea room', 'small', 'positive'], ['tea room', 'cute', 'positive']]

none

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

generation

aste-data-v2

[ "What an amazing meal and experience !" ]

[['meal', 'amazing', 'positive']]

none

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