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generation
mams
[ "The waiter disappeared after dropping off the food so I had no choice but to eat it as is." ]
[['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 did not find the wait staff to rude at all, how involved do you really want them in your meal right?" ]
[['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
[ "Half way through the meal my husband had to go to the bar to order his own beer, since the server never came back." ]
[['food', 'neutral'], ['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
[ "To the amusement of our server, I wrote everything down, lest I forget a single morsel (about 21 different dishes)." ]
[['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
[ "Order the porterhouse and they put it between you and you kind of eat family style at a wooden table." ]
[['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
[ "It's just a diner, but three decent hearty lunches for 12 bucks?" ]
[['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
[ "I ordered a medium Cub burger and it came out well done, not that my server would have noticed since we didn't see her again until she brought the check." ]
[['staff', '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
[ "The bar gets out of control busy due to it's proximity to Fordham University--but the Fordham kids are cool, so it's alright!" ]
[['place', '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 waiter spent a long time telling us about the menu (and more about his own life history in the process." ]
[['staff', 'negative'], ['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
[ "Comfort standbys--including bacon-wrapped meat loaf and barbecued ribs, and upscaled interpretations--like tuna club made with wasabi mayo, share space with brunch favorites (Belgian waffles, fluffy buttermilk pancakes and wrecked eggs, or tofu)." ]
[['ambience', 'positive'], ['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
[ "In other words, conserative types craving simpler things like grilled chicken or salmon probably would not appreciate Tabla's distinctive and unusual menu." ]
[['food', 'neutral'], ['menu', '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 write that in quotes becuase iceberg lettuce, stale Pepperidge Farm croutons and bottled dressing does not a salad make." ]
[['food', '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
[ "The menu sticks to standard Italian dishes--linguine with clam sauce, chicken parmigiana, and fettuccine Alfredo--but the reasonable prices add to the charm." ]
[['menu', 'neutral'], ['food', '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
[ "The waiter nearly yelled at me when I asked for more water." ]
[['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
[ "When I asked for a particular drink, the waitress gave me dirty look and annoyed b/c they didn't know what it was." ]
[['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
[ "WAY OVER PRICED , HAD MUCH BETTER MEALS FOR JUST OVER HALF THE PRICE IN PLACES JUST AS NICE." ]
[['price', '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
[ "then, the waiter had nerve to charge me for the fruit salad and bloody mary (which we didn't drink) that came with the omelet (brunch special)." ]
[['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 had the waiters bring back so much meat that that asked me if I wanted Flank steak for dessert." ]
[['staff', '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
[ "This was followed by various wacky hijinks: overly sweet foie de gras, lack of extra ginger/soy sauce, minute portions even for sushi, appetizers arriving at different times." ]
[['miscellaneous', '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 waiter kept pestering us for our order even though we were among the last diners." ]
[['staff', '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
[ "Waiter suggests a beer, and offers to bring a small glass, to taste it and see if I like it, before I even order the beer!" ]
[['staff', '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 ordered dessert and it was they gave me the wrong flavor of ice cream." ]
[['food', 'neutral'], ['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
[ "We started at the bar with a nice bottle of wine, which was priced fairly and sampled several different cheeses." ]
[['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
[ "A 3 course-meal took 2 1/2 hours, including 20 - 30 minutes waiting to get the check after dessert." ]
[['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
[ "And the room is VERY noisy, but I suppose that's because everyone is having a good time." ]
[['place', '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
[ "We fully relied on our very capable waiter for choices of the menu and we were not disappointed." ]
[['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
[ "The food was abundant and good but wasn't worth the unpleasant wait." ]
[['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
[ "perhaps the place is better after the theatre crowd is gone but we were in the midst of it and it wasn't a very enjoyable experience." ]
[['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
[ "The waiter didn't know the menu, didn't bring more than one item at a time, and put some orders in twice with the kitchen." ]
[['staff', 'negative'], ['menu', '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
[ "The Scene You won't blink twice at the restaurant's spartan decor: As the packed crowds and critics' praises wallpapering the front wall agree, this longtime local favorite is truly one of the area's most exquisite finds." ]
[['miscellaneous', '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 rolls are tiny so you have to order more anyway and they will often get your order wrong if you stray from the menu." ]
[['food', 'negative'], ['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
[ "Into our appetizer, an adjacent table became available, and we asked if we could use it, but the waiter said it most likely was being used." ]
[['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 service has always been outstanding and even when we didn't have a reservation they worked something out, where I agreed to keep our meal to just eating." ]
[['service', '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
[ "We reserved the downstair lounge for private parties and the price was fairly reasonable." ]
[['place', '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
[ "To start with - the maitre'd forgot our reservation and then when it came time to sit us down - he told us we only had an hour." ]
[['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
[ "In Short The bi-level dining room, which resembles a bamboo-thatched hut, is a brightly-lit, wide-open space with high ceilings and laminated depictions of Indian village life." ]
[['food', 'neutral'], ['place', '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
[ "At least the entertainment was free, as we were able to witness one customer wooing a waitress, and another being drenched in milk." ]
[['ambience', 'positive'], ['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 table next to us recommended that share because the portions are big(we split two entrees)The food was so good I wish that there was some left over to take home for the next day." ]
[['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
[ "We were immediately seated (the restaurant was no where close to being packed, surprise, surprise) There are very few selections on the menu and the food is not that great and the dining experience at Butter is completely overrated." ]
[['menu', '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 service was good, but not excellent; however, the waiter was initially huffy with me when my guest was only 5 minutes late, threatening to make me move!" ]
[['service', '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 our entrees came, at least 3 or 4 waiters / waitresses came by at different times to wish us bon apetit." ]
[['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 server absolutely did not know what in the world he was talking about when we aske questios about the menu, and he barely spoke English." ]
[['staff', 'negative'], ['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
[ "Warning Service is decent, but it takes forever to get the check." ]
[['service', 'positive'], ['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
[ "Good food, but bad service." ]
[['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
[ "The waiters actually roll their eyes when you order something, as if you are imposing on them by ordering food." ]
[['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 had started to circle around our table like a shark after our 2nd dish, taking out plates when we were not even done." ]
[['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 reservation for 2 was during lunch and it seemed that because I was literally 2 minutes late, the hostess felt the need to seat every party before mine." ]
[['miscellaneous', 'neutral'], ['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
[ "I can't even remember if they serve anything else -- a busy hole in the wall sized place and atmosphere." ]
[['place', 'negative'], ['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
[ "We had to wait an hour before our food was served, then another hour inbetween courses, all the while whilst the staff were naughtily hiding in an attempt to avoid our 'where's out food?'" ]
[['service', 'neutral'], ['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 Kitchen is only separated from its patrons by glass is immaculate and the service is undeniable heartfelt." ]
[['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
[ "It was also very reasonably priced, we had 4 bottles of wine, appetizers, dinner, and coffee and our bill was just over 50 per person." ]
[['price', '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
[ "While I would agree with the initial review that Asia de Cuba isn't really Asian or Cuban in its decor, the food was a nice fusion." ]
[['ambience', '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
[ "It took a long time for the waiter to bring the check and we had to flag him down." ]
[['staff', '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
[ "Only drawback is the sound level - quite a loud space downstairs - and that might be accounted for with their trendy bar and right off Times Square." ]
[['food', 'negative'], ['place', '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 Prix Fixe, so be prepared to spend at least $60 per person, but it is Well worth itsuperb food." ]
[['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
[ "Went the next day for lunch - menu too pricey for lunch and the waiter was the WORST !!" ]
[['miscellaneous', 'neutral'], ['menu', 'negative'], ['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 Food It's billed as Asian street food, but since the menu is a creative collaboration between expert chefs Vongerichten and Gray Kunz, dishes show unmistakable finesse." ]
[['food', 'neutral'], ['menu', '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
[ "Al Di La serves up an impressive selection of options ranging from meditarranean fish to rabbit to to duck to pasta." ]
[['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
[ "when someone from our table of 5 asked the waitress for refill on water, she comes back and fills only that person's glass, leaving the rest of the table with almost empty glasses." ]
[['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 told the manager it was not worth a few appetizers to be treated that way and left." ]
[['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
[ "The food is decent, but WAY TOO SMALL of portions for what you pay for." ]
[['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
[ "We would have to flag down the bored looking wait staff to refill our tea." ]
[['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
[ "Watch out for the overworked, stressed out waitress who dumps tapa dishes on the table and leaves w/out announcing what it is." ]
[['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
[ "I would not recommend this place until they get a new staff that can complement the food." ]
[['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 food was pretty good, but due to our large size (~16) the manager asked us to limit our appetizers to just 3 selections b/c he didn't want to overburden his cooks." ]
[['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 waitress seemed less than happy about the prix fixe dinner choices and at one point said, Do you really need to hear the specials?" ]
[['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
[ "On the table you will also find individual bottles of fine imported olive oil which we put on the bread-fantastic!" ]
[['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 service was good enough for a crowded place." ]
[['service', 'positive'], ['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
[ "Then the staff behind the buffett just haven't gotten their groove yet, so you order your food and wait five minutes while it sits behind the glass on a plate, getting cold." ]
[['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
[ "They are negligent in alerting customers when an order is ready - you could end up waiting for half an hour while your food is sitting on their counter getting cold." ]
[['service', 'neutral'], ['food', '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
[ "The bar tender didn't know where the tea was, waiters started making the drinks if the bar tender wasn't around." ]
[['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
[ "It took forever to seat us even though the restaurant was almost completely empty, then we had to ask to be waited on, it took another 15 minutes to get our drinks, and then another 30 minutes to get our salad and then even more time to get our pizza and then our bill." ]
[['miscellaneous', '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 waitress/hostess seemed a bit sad when we told her we weren't ordering dessert (those arepas are deceptively filling!" ]
[['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
[ "Nice decor and an extensive menu lured me in, but the horrible service and rude staff drove me out." ]
[['menu', '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
[ "As expected, the beer selection is perfectly in synch with the 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
[ "yes Shrimp not lobster (those are 6 Lbs) try the exotic Fish not on the menu and a must have is the Flower stuffed with lump crab meat." ]
[['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
[ "The House salad is big enough to split, The Fried Calamari is some of the best I ever ate, the bowties broccoli, broccoli rabe, square slices, broiled filet of sole, clam sauce." ]
[['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 only problem my party found was that when people asked for knives and forks (there were only chopsticks on the table) the waitress laughed at them." ]
[['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
[ "I have a litany of complaints -- being over-charged for wine that I didn't order, shady waiters, so-so food that arrived at the table luke warm, main course portion sizes barely large enough to be appetizer sizes, lack of fabulosity that Mr." ]
[['food', 'negative'], ['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
[ "Unlike the reviewer before me, what made me KEEP going back was the great reception I received from the bouncers and I needed several cocktails to endure the waitstaff." ]
[['food', 'neutral'], ['staff', '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 were the only two people sitting out front and the waiter was unable to provide us with attentive service OR our dinner." ]
[['service', '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
[ "We finally flagged down another server who brought us more to drink, and then they took forever with the check." ]
[['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 waitress forgot our coffee, took forever to take our order, never checked in with us after the food came and when we were done, didn't bring us the check for the longest time." ]
[['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
[ "Wish the Greenwich street location had more seating like their 2nd Ave location, because one invariably leaves it smelling of grease." ]
[['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
[ "Aside from that, the service is adequate (visible, and will help you if you ask, but lack initiative), and the food, well, could be a lot worse." ]
[['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
[ "The wait staff was better the second time around and our water glasses were always full." ]
[['staff', '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 highly suggest you make reservations, as wait times can be extremely long." ]
[['miscellaneous', '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
[ "For a restaurant with such limited menu and wine list, each dish should better be darn good." ]
[['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
[ "Waitress kept trying to get us to order more drinks while apologizing but wouldn't even bring bread to keep us from starving." ]
[['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
[ "You must think that the quality is poor for them to sell it for such a low price." ]
[['miscellaneous', 'negative'], ['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
[ "Both appetizers arrived cold/luke-warm, which we had to send back, only to have the waiter tell us that one was supposed to be cold." ]
[['food', 'negative'], ['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
[ "The Food Consulting Chef Douglas Rodriguez's forte is blending the diversity of traditional Latin cuisine with modern culinary chic: A celery sorbet cools the spicy-citrus bite of lobster; shrimp seviche and crunchy green plantains coat thick, juicy halibut resting on sweet plantain hash; and tart tomato escabeche moistens a chewy skirt steak." ]
[['food', 'positive'], ['staff', '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 perfect meal; delux combo raw bar as an appetizer, King crab as your entree." ]
[['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
[ "The place was not crowded for dinner on a Sunday night at 8:30pm." ]
[['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
[ "Waiter dropped check on table while I was in the middle of handing my wife her anniversary present." ]
[['staff', '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
[ "Meat wasn't fall-off-the bone (a sign of over-cooking) but was tender and had deep flavor." ]
[['food', 'negative'], ['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 waiter came back after I had finished my appetizer to correct himself and let me know that it wasn't vegetarian (chicken stock) after all." ]
[['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
[ "Food took over an hour despite at least two chasers, we had to track the server down to get extra drinks, the manager seemed to try and deliberately mislead us about the reason behind the delay and in the end the food was poor." ]
[['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 waiters are nice, but weren't particularly good - waited forever to order and resented not being told that my dinner companion and I had ordered enough for a table of 10 (given the size of the sushi)." ]
[['staff', 'positive'], ['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
[ "The place is very loud, good for drinks by the bar not to eat and yell." ]
[['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']]