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generation
mams
[ "Informal servers sashay past plastic chairs and patterned booths, ducking enormous lampshades with cheerful insouciance." ]
[['staff', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When we showed up, the guy at the door said it would be 15 minutes and that we could wait by the bar." ]
[['staff', 'negative'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "our waitress (who was ok) disappeared in the middle of our dinner, leaving us to an obnoxious amateur (must answer the phones or something) who could not answer our questions and treated us extremely rudely." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Wait staff started swarming around us as if we just ordered cokes throughout lunch." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Smallish menu, but more than adequate, and not that heavy on sauces which is so typical of italian restaurants." ]
[['menu', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Besides ordering single dishes you can also order family style." ]
[['food', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "the staff there was really freindly the owner even sat down at one point to chat with us, it was hard to chose from the menu it all sounded good, so my wife and i shared plates to try a little of each dish , we ordered." ]
[['staff', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Even at lunch, when lawyers and publishers flock in to wheel and deal over the justly-popular lunch buffet, the atmosphere remains serene." ]
[['food', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I highly recommend the chicken hearts, but remember: ask the waiters, since they're not usually available and will be cooked upon request (and will go fast)." ]
[['food', 'positive'], ['staff', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Had a late-night dinner there on Friday, and while the decor is fabulous, we waited a long time for our check." ]
[['food', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "the decor isn't quite like Shun Lee but the service will definitely make up for any shortcoming." ]
[['ambience', 'negative'], ['service', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "In the middle of dessert, the waitress silently passes by and drops the check." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The waiter's recommendation for the entree (seabass in a lime and mango chutney) exceeded our expectations and we ate the chutney to the last drop." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "For the cost of the lunch I expected much better service." ]
[['price', 'neutral'], ['food', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Even though it's a trek for me to get there and the place is a little of a Hole in the wall, I've gone many times for the food alone." ]
[['place', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "In the main dining room, finding your waiter is Hell and aside from when they take your order and bring the bill, you'll rarely see them." ]
[['place', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We sat there with the check and ordered dessert and more drinks." ]
[['price', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "As a former waitress, I get this conceptually, and I am even understanding of the fact that I had to wait 30minutes to get my first drink because the bar was backed up." ]
[['staff', 'positive'], ['food', 'neutral'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "But my lunch was very light with a wrap, not tortilla, but something thinner, a rice paper sort of crepe, that had lettuce and spicy cabbage and thin sliced beef." ]
[['food', 'positive'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I have been a waiter for many years and I can tell you that if bad service is given you at least apologize to the costumer." ]
[['staff', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Those less interested in people-watching dine inside the whimsical, wood-trimmed room under a canopy of Italian inscriptions, or at the long, art-lined bar, which hosts a hopping after-work crowd." ]
[['place', 'positive'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "And I'm saying that dinner has actually taken about an hour more than it should, just because of the slow service." ]
[['food', 'neutral'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We sat near the sluggish, hot and very loud kitchen and the service area was not wiped down once during the entire time." ]
[['place', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Manager couldn't be bothered to come over and acknowledge the mistake." ]
[['staff', 'negative'], ['service', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Soy abounds, in all forms: as firm patties, pure squares of glistening tofu, and something called a hijiki patty--mixed tastily with shreds of seaweed, then fried." ]
[['food', 'negative'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Evening service--featuring waiters all in black--is a little slow; plan on a leisurely dinner unless you're headed for the theater." ]
[['service', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Try the stir fried cube steak, shabu sahbu, or the Oden, or anything else you want to try on the menu." ]
[['food', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I sat at the bar to receive faster service, and boy was i wrong!" ]
[['place', 'neutral'], ['service', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Within 3 minutes after we sat the waiter was hovering over us to get our food order." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "My mouth almost dropped, and for good reason, when the server brought my sandwhich and side of macaroni." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "If you think the prices are outrageous, just take the family, enjoy the ride and go in and order a few appetizers as prelude to a real dinner." ]
[['price', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "(Note: Price variations were listed nowhere--and I had asked for a to-go drink, deciding--after paying--to sit at a no-service counter until my drink cooled off." ]
[['price', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "This restaurant was a great value, even though I know nothing about the prix fixe menu." ]
[['miscellaneous', 'positive'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "To enhance the dining experience, there is a live jazz band, which further isolates you from the world outside the gates." ]
[['food', 'positive'], ['ambience', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Surf-and-turf encompasses the menu's star entrees: deliciously charred sesame-crusted tuna with ginger ponzu gently juxtaposes espresso-rubbed filet mignon." ]
[['menu', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The menu is quite substantial, with a number of chicken, beef, and seafood specialties not found at your typical chinese restaurant." ]
[['menu', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Other than the too fruity drinks at the bar which wasn't my cup of tea, everything else was excellent." ]
[['place', 'neutral'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The porterhouse is as good a steak you are going to find in NYC or the surrounding area." ]
[['food', 'positive'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After a short wait at the bar (which was very crowded), we were seated upstairs at a private table." ]
[['service', 'neutral'], ['place', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "My only two complaints are that (1) our server was a real space cadet and kinda inattentive and (2) the sodas were really small; overall, though, I had a great time and really enjoyed my dinner!" ]
[['place', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After paying for our meal, we left some feedback with the manager (a chap named J." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Down right comfortable, pleasant, enormous portions, have lunch and bring home a doggie bag wth your dinner." ]
[['miscellaneous', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The host actually came over to my table and told me and my date we had to leave because we already paid our bill." ]
[['staff', 'negative'], ['miscellaneous', 'neutral'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Their Korean menu was also equally impressive, A must try is the Kimchee cabbage pancakes as an appetiser ( the portions were as big as an entree!)" ]
[['food', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Waterview is one of the best diners I've evr been to interms of the quality and taste of the food." ]
[['price', 'positive'], ['miscellaneous', 'neutral'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "40 minutes later, the waitress finally looked at our table and we asked about our dishes." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The staff were all partying with each other at the bar, so even though we were the only ones there for food, it took 15 minutes to get menus." ]
[['staff', 'negative'], ['place', 'neutral'], ['menu', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "we told the waitress and she told us that we ordered the dead fish as opposed to the swimming fish." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Our waiter was confused and forgot an additional soda when we asked for it." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Scene Neither trendy and slick nor haute and haughty, it this cozy wine bar adds a bit of Mediterranean sun to the chilly east 70s." ]
[['place', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "This is one of two Ping's in Queens, the other one on Queens Blvd in Elmhurst serves great seafood dishes fished straight off clean tanks." ]
[['miscellaneous', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The place was beautiful, I sat at the bar for two hours and eat oysters and had way too many martinis." ]
[['place', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Unfortunately it gets very crowded on the weekends, so if you don't mind dining at the bar you can skip the wait for a table." ]
[['food', 'negative'], ['service', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "If you are under 24 this might seem to be a great place in the big city but for the rest of us it's just a liitle too chheesy and the food is under par for the price." ]
[['food', 'negative'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "They spoon the FAT GREASE over your steak when they bring it to the table." ]
[['food', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "In Short This old-fashioned luncheonette, festooned with artificial flowers and signs touting the cherry lime rickeys, egg creams and banana-walnut pancakes, is favorite pitstop for folks visiting the Brooklyn Museum and Botanical Gardens." ]
[['food', 'positive'], ['place', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I'm a chef (30 years), and I can honestly say that I've finally found Italian food worth eating at a reasonable price." ]
[['staff', 'neutral'], ['price', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "unbeknownst to the three of us, the hostess made note of the fact that i was celebrating my b-day after a member of my dinner party made a very brief reference to it as we were seated." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Although we were seated quickly, ambiance was cozy, service was decent the overall menu selection and overall food taste and presentation was less to be desired!" ]
[['ambience', 'positive'], ['service', 'positive'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Count on fresh, fairly priced cuts of fish that represent a good value, even if portions are a bit on the small side." ]
[['food', 'positive'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Food is pretty good but the service is horrific." ]
[['food', 'positive'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Warming clam miso soup and expertly rolled Mexican maki (made with yellowtail, scallions, avocado, and jalapeno mayonnaise) pair well with a stiff glass of shochu, Japanese liquor with a bite as strong as tequila." ]
[['food', 'positive'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Food Mafrici's approach to modern Italian fare may seem gimmicky: The menu lists eight seasonal ingredients, each prepared as an appetizer, pasta and entree." ]
[['menu', 'neutral'], ['ambience', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The food was cold and did not match the description on the menu, the waiter could not be bothered with me (and I am nice to deal with since I work in the industry), and it was way over priced." ]
[['miscellaneous', 'negative'], ['menu', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The tables are close so you can hear every conversation going on around you, but if you're here with someone who enthralls you, you will notice no one else but your dinner date." ]
[['place', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "00 bottle of wine, we had to endure the waiter's attitude, like he was doing us a solid, if you're into huge Euro crowds and don't care about what you eat and how it is served to you, Baraonda is your kind of place." ]
[['service', 'neutral'], ['miscellaneous', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "After waiting almost an hour for a table (with resies) our waiter told us that they don't have a sommelier because no steakhouse has a sommelier (patently false), and finished with the notion that he had absolutely no idea about any of the wines on the list." ]
[['service', 'neutral'], ['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had to wait by the door, and the host failed to acknowledge our existence for a whole 15 minutes!" ]
[['miscellaneous', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "A friend and I went for dinner, the host was rude to us as we walked in, we stayed because the decor is charming and we wanted french food." ]
[['food', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Not the best ambiance, but meat that'll make you drool." ]
[['ambience', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The food is good and cheap BUT the attitudes of the bartender and wait staff are almost unbearable." ]
[['food', 'positive'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "When we got there, the wait was just as everyone here has described, Domenico's process was just as described, but the pizza?" ]
[['service', 'neutral'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I don't think the menu is particularly creative, but I've gotten solidly tasty sushi here and it's always enormous." ]
[['menu', 'negative'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The waiters are very kind and helpful, and I regularly get something on the house - coffee, dessert or a drink." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "It takes forever for them to serve you just drinks, and some of the waiters seem to not comprehend what you order." ]
[['food', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The servers were extremely professional, especially considering the entire room needed to be served at the same time." ]
[['staff', 'positive'], ['service', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The waitresses are so nice and will even help you pick a meal if you are new to spanish food." ]
[['staff', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Sit at the bar (no reservations necessary), eat, talk to the bartender, and enjoy, b/c come dinnertime you will pay quadruple the price (but it's still worth it)." ]
[['miscellaneous', 'neutral'], ['price', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Once at the table our waitress managed on two occasions to take 15 minutes bringing drinks to our table, our plates sat uncleared on the table for just as long." ]
[['staff', 'negative'], ['food', 'neutral'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had reserved space one one side of the bar, but when the staff tried to force the Pre-Fixe on all 15 members of the party to stay there, we moved to the other side (the difference in decor was minimal)." ]
[['place', 'neutral'], ['staff', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Also lovely was the atmosphere; the high ceilings and spacious room make it a nice contrast from the other brunch mills on the upper west side." ]
[['ambience', 'positive'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "never had a bad pizza, the staff has always been friendly, if not overly solicitous, and the only downside is the occasional wait on line outside." ]
[['food', 'positive'], ['staff', 'positive'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had a horrible night here stemming from intolerable service, no appologies after our food never came out after waiting longer than an hour and a half, and a plate of crusty bread thrown at us when we asked for their signature corn bread." ]
[['service', 'negative'], ['food', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Clams, shrimp, mussels, scungilli, and calamari served together in a spicy red sauce atop linguine are full of flavor; steak pizzaiola, a heroic portion of tender beef in a pool of garlicky marinara, comes with a side of spaghetti." ]
[['food', 'neutral'], ['ambience', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The Scene Vintage suitcases and black-and-white photos of old ocean liners evoke the Golden Age of travel in the front bar, where a worldly clientele sips cocktails around a flickering faux fireplace." ]
[['miscellaneous', 'neutral'], ['place', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had reservations and when we showed up the manager told us the wait was over 45 mins." ]
[['miscellaneous', 'neutral'], ['staff', 'negative'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Diners choose between deep banquettes or seats at the bar, which offer a front-row view of the small preparation area and a chance to watch the two chefs as they whip together the elegantly constructed desserts." ]
[['price', 'positive'], ['miscellaneous', 'neutral'], ['place', 'neutral'], ['staff', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We had to ask for the bill twice, and our water was refilled only when we asked for it." ]
[['price', 'neutral'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The waiter had a slight attitude and brought our wine aprroximately 10 minutes into our appetizer." ]
[['staff', 'negative'], ['service', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "We did enjoy the recommended, yet simple $40 sangiovese, atmosphere and loosey-goosey service, but we were disappointed overall." ]
[['ambience', 'positive'], ['service', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "The waiter poured our wine into my water glass, rolled his eyes when I asked for a new water, and definitely didn't offer to comp the wasted glass of wine." ]
[['staff', 'negative'], ['miscellaneous', 'neutral'], ['food', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I am a martini guy - vodka, not gin - and their classic martini with blue cheese olives is pretty damn near definitive." ]
[['staff', 'neutral'], ['food', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "With the exception of one late day when I came in for caffe and the waitress nearly rushed us out since dinner was coming around." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "I can't imagine waiting for 20 minutes to have my plates removed, given that usually the waitstaff hover around like birds of prey waiting for a fork to drop etc." ]
[['miscellaneous', 'neutral'], ['staff', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Oh, but on a brighter note, when the waiter poured water into my vodka glass by mistake, we got a free drink out of it." ]
[['staff', 'negative'], ['miscellaneous', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "My girlfriend asked the bartender what kind of wine they had and since she couldn't hear she leaned on the bar to get closer to him and he made a face and told her not to get near him." ]
[['staff', 'negative'], ['food', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "sashimi was meh, salmon was good but the tuna was a little white and seemed like the day before as the flavor had faded." ]
[['food', 'positive'], ['ambience', 'negative']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "They do make great burgers for the money and give big portions of fries with it." ]
[['food', 'positive'], ['price', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Went to dinner with some girlfriends on Wednesday at Calico Jacks and had a fun time." ]
[['food', 'neutral'], ['miscellaneous', 'positive']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]
generation
mams
[ "Philippe should re-train their wait staff to communicate with one another and better orchestrate the timing of food service." ]
[['staff', 'negative'], ['service', 'neutral']]
none
Task: Extracting aspect terms' aspect categories and their corresponding sentiment polarities. Input: A sentence. Output: A list of 2-tuples, where each tuple contains the extracted aspect category and their corresponding sentiment polarity. Supplement: "Null" means that there is no occurrence in the sentence. Example: Input: "Hostess was extremely accommodating when we arrived an hour early for our reservation." Output: [['staff', 'positive'], ['miscellaneous', 'neutral']]