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generation
mams
[ "I made the mistake of coming here with 5 friends for brunch so the wait was extremely long and then we got stuck at the only table big enough for 6 (downstairs near the bathroom away from all of the other patrons) so that was dissapointing but I will be back soon with 1 or 2 friends." ]
[['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
[ "Our waiter told us he knew all the wines on it quite well, and he did!" ]
[['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
[ "There were about 4 tables filled in the entire restaurant yet the hostess made us sit at the bar for 20 mins--she never would have come for us had we not approached her asked to be seated." ]
[['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
[ "This newly opened restaurant is another one of those Indian places that has a hugely promising menu and a greatly disappointing food." ]
[['menu', '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
[ "Yes, this place is good, a cut above some of the other local diner food and a nice, friendly atmosphere." ]
[['place', 'positive'], ['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
[ "Nice ambience and bar while waiting for a table." ]
[['ambience', 'positive'], ['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 kicker was when there were three items on our check that were priced higher than stated on the menu and by the server." ]
[['price', '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
[ "If you're looking for barbeque like Dallas BBQ (soaked in sauce from a bottle, generic, homogeneous food) then you won't like Blue Smoke." ]
[['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
[ "For the price I paid for a cup of Bustelo coffee w/ milk I could buy 2 vacumed packs for 3 bucks." ]
[['price', 'negative'], ['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
[ "Three course meal for lunch was $13, the prices for dinner were just as great!" ]
[['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
[ "Lost reservations, out of liquor, jam-packed, waiting room, out of wine, sent steak out raw, no choices for dessert, no room to breathe, terrible service, etc." ]
[['miscellaneous', 'negative'], ['place', 'neutral'], ['food', '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
[ "Although we were seated 35 minutes after our reservation the service from then on was outstanding." ]
[['miscellaneous', '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
[ "The Food The menu includes lovingly made renditions of panini, bruschetta and tramezzini (cocktail-style sandwiches with fillings like tuna with black olive pesto and bresaola with arugula), along with a roster of cured meats, cheeses and olives that have been imported from Italy." ]
[['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
[ "My meal here was awesome, the appetizers, the bar finger food, the service, the drinks, the entrees of Smoked fish, Lamb salad, Clay pot salmon, Lobster rolls, and the dining room is spectacular." ]
[['food', 'positive'], ['service', '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
[ "The place is small, but loaded with plenty of goodies that range from Italian inspired treats to Greek pastries all well prepared." ]
[['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
[ "The pizza is thet always fresh and just made they hav an outdoor seating area that is partially covered they also have a full service restaurant on the premises they make everything on premises." ]
[['food', 'positive'], ['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
[ "A friend was dieing for chorizo but it was only in the tapas menu which we couldn't have." ]
[['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
[ "Just make sure you make reservations a few days in advance because there aren't a lot of tables." ]
[['miscellaneous', '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
[ "They had a prix fixe menu with the most amazing cooked quail appetizer, then lobster bisque, followed by a divine choice of entree, and then the chocolate mousse dessert." ]
[['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
[ "In summer, the small outdoor garden is an ideal place to sip coffee while reading under a canopy of trees and sky." ]
[['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
[ "If you had good service there, try to get your waiter's name and request him/her by name the next time." ]
[['service', '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
[ "Our waiter was stuffed with attitude and didn't bother explaining things on the menu that he clearly knew we could not understand." ]
[['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
[ "not having a menu was rather strange at first but the food was superb." ]
[['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
[ "If you are a person who wants perfect service, you should probably skip it, you may wait for your server to sing a song before you get your drinks but that is half the fun." ]
[['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
[ "Casual and kid-friendly, the red-and-gold colored restaurants offer quick drive-thru or dine-in service with a menu of burgers, sandwiches and more." ]
[['service', 'positive'], ['food', '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
[ "When a seemly accommodating Le Souk manager assured you that he had no problem serving a group of twenty on a Saturday evening, I expected him to keep his words or shall I say our table." ]
[['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
[ "dining with my mother this past Saturday must have signaled to the wait staff that I wasn't cool enough to merit their attention." ]
[['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 staff knows the regulars by name and the sushi chef even yells goodbye from behind the bar." ]
[['staff', '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
[ "Overall, the food makes up for what is missing in the ambience and service." ]
[['food', 'positive'], ['ambience', '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
[ "FINALLY the waitress came with our food after an HOUR!" ]
[['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
[ "Before our server took our drink order she told us that the prices on the menu were going to be higher that night because of the party." ]
[['staff', 'negative'], ['food', 'neutral'], ['price', '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
[ "when tables opened up, the manager sat another party before us." ]
[['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
[ "After arguing about this and requesting tap water instead of a bottled variety, we were exiled to customer Siberia, and the staff seemed eager get us out of the restaurant as soon as possible." ]
[['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
[ "Instead of being smart business people and treating us as paying customers, we were told they do not serve drinks, only food (only food?" ]
[['miscellaneous', '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
[ "However the casual atmosphere comes in handy if you want a good place to drop in and get food." ]
[['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
[ "A narrow corridor leads to a tiny space where there are three tiny white tiled counters, a great deal of mess (stacks of bottles, cans) and a small counter holding 12-14 entrees." ]
[['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
[ "We were ignored by our waitress after our entrees had been served." ]
[['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 was there with a friend the waiter who served us was pretty friendly." ]
[['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
[ "My greek salad cost about $9 and for that price, I would not have expected chopped olive (as opposed to whole), and shredded bits of lettuce." ]
[['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 retaurant is know for the long wait but they do take reservation for group of 5-8 people, so it was just perfect for my friend BD dinner for 3 couples." ]
[['service', 'negative'], ['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
[ "since we're informed its service isslow we had dinner in midtownwent for dessertb-day thing." ]
[['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
[ "the soups were superb and only $2 a bowl, and the entire dinner, with beers, cost less than $30 for two people." ]
[['food', 'positive'], ['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
[ "The place was practically empty when my friends and I got there for dinner." ]
[['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
[ "On top of that, when we tried to order more food half-way through our first entree order, the waitress told us that we couldn't because they needed the table for another reservation!" ]
[['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
[ "8pm reservation, place was half empty on a Saturday." ]
[['miscellaneous', '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
[ "The Scene The bright mix of colors painted on the cafe's walls matches the vivid margaritas that sit on nearly every table and litter the sceney bar." ]
[['miscellaneous', '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 busboy kept our glasses full; the waiter warmed up to our table at the end of the night by cracking jokes." ]
[['miscellaneous', '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
[ "Desserts were visually inventive but lacking in flavor." ]
[['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
[ "The place was packed and while our food took time to be prepared, our waiter earned points for his sparkling conversation to pass time and for also knowing practically every ingredient of every special under consideration." ]
[['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
[ "i recently had brunch at the new hill diner let me tell you it was great." ]
[['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 festive crew serves from a gigantic menu of American classics: chili, burgers, cobb salads, baked potatoes, wings, philly cheesesteaks, club sandwiches, you name it." ]
[['staff', 'neutral'], ['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
[ "The head-on shrimps with anchovy butter had me licking the plate." ]
[['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
[ "You can only sit on the stools with a slice, as the main dining area downstairs is for real food." ]
[['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
[ "The wine list didn't look all that great, but there was a very interesting selection of beers on tap." ]
[['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
[ "Unfortunately the food and the service don't live up to the spectacular setting." ]
[['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 food was OK, but trying to get anything, like a drink refill or the check, was an ordeal, and this was when the place was nearly empty!" ]
[['food', '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
[ "Seating is limited, so you will probably want to order take-out, but a better take-out pizza you will not find!" ]
[['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
[ "The clientel, however, make it a scene for creative, talented people--inlcuding a soon-to-be-famous theater director who used to waitress there!" ]
[['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
[ "I liked the overall setting A LOT and it was only improved by the fact that our waiter was pleasant and attentive even though we only ordered entrees (no drinks, no appetizers, no coffee)." ]
[['ambience', 'positive'], ['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
[ "However service was quite slow for a lunch hour." ]
[['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
[ "The menu was much too narrow - 4 pastas and 6 meat dishes or so." ]
[['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
[ "(We did make reservations, since we had a group of 8, but had a short wait when arriving a little early." ]
[['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
[ "first of all, the hostess was not pleasant and had a bit of an attitude when seating us." ]
[['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
[ "We are laidback diners and as we've both waited tables, we tend to be forgiving of irregular service." ]
[['price', 'neutral'], ['place', '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 only saw 2 - 3 boring appitizers on the menu and not a lot of choices of meat to select from." ]
[['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
[ "It gets crazy busy like any other bar on the weekends, so don't go there on a busy night if your looking for a quiete dinner party or fine dining service." ]
[['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
[ "The service may be a little slow (what can you expect in this laid back atmosphere), but a Sunday brunch is a rewarding experience." ]
[['service', '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
[ "Get in before peak dinner time (7-8 PM) to avoid harried 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
[ "The mussels and frits were great, but the host had an attitude and my friends and I waited about 1 1/2 hours to be seated on a random Tues." ]
[['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
[ "My date knew the waiters from years of dining here, so we were treated like royalty." ]
[['staff', 'positive'], ['food', '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
[ "While the appetizers I sampled (gnocchi; shrimp wrapped in coconut or somesuch) were not so impressive (the gnocchi portion is meager and overpriced), my table was 100% satisfied with their entrees too." ]
[['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
[ "Were told we could not share one menu and called over the horrible manager." ]
[['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 bill came out to quite a lot though, considering there were 14 of us some of us ordered way too many 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
[ "Many Thais top off spicy dishes with a fried egg, but in many places it's not on the menu and when requested, I will either get charged $1." ]
[['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
[ "It had not been made fresh at the bar, but kept in the freezer till we ordered, they also forgot our soup, kept us waiting for the frozen sushi for close to an hour." ]
[['place', 'neutral'], ['food', '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
[ "The owners couldn't have been more accomodating -- we had the entire restaurant to ourselves on a Saturday (before it opens to the public for dinner)." ]
[['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
[ "We would have left and gone to another restaurant but the host kept saying that a table was opening up in 5 minutes, people had just paid, etc - except when I went to check the table, they were ordering dessert." ]
[['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 pushing us all night to take our plates, and swiped my dessert before I was finised with it." ]
[['staff', 'negative'], ['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
[ "Or better yet, if on a budget and want to do something romantic, stop at the bar for a drink and enjoy the sunset." ]
[['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
[ "It is a nice diner atmosphere, they have booths all around and a couple of middle tables." ]
[['ambience', '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 waitress had an ongoing diatribe with a waiter the whole time she served us-it was ALL BAD!!" ]
[['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
[ "Food was good, but not worth the 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
[ "The service was rather slow but our waiter was very pleasant and obliging." ]
[['service', 'negative'], ['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
[ "Didn't like having to flag down waiters for drinks, nor having to wait almost 15 minutes for a check after asking two servers." ]
[['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 don't usually go there over the weekends or during prime dinner hours--but for a weekday dinner it's great, and I've never had any problems with crowds, waiting, or bad service." ]
[['food', 'neutral'], ['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
[ "A+ for the food but the wait staffs need to educate themselves better." ]
[['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
[ "The food was awful and took forever to arrive - which considering the limited menu, few diners and the fact that we ordered chili, mac cheese and a grill cheese was annoying." ]
[['menu', 'negative'], ['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
[ "Finally got our food after waiting a long time for oysters, doesn't take that long to shuck 'em, the place isn't that big, and it was OK." ]
[['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
[ "After a crazy day @ work, with no reservation, we were so lucky to score a seat at the bar on an incredibly busy evening." ]
[['miscellaneous', '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
[ "I also asked for a chef (thought that may be able to talk about the food for the party), but the waitress said that there was no chef at the restaurant." ]
[['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
[ "Our waiter (who also seemed to be the manager) dropped red wine all over me the contents of my purse and all he did was apologize quickly, hand me some club soda and avoid me for the rest of the time I was there." ]
[['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 place was so dark, I needed the table candle to read the menu and could not properly see what I was eating." ]
[['place', 'negative'], ['miscellaneous', '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
[ "People were leaving because they had been waiting for hours, however we decided to stay and have a complimentary drink at the bar which was absoloutely beautiful along with the view, the only plus." ]
[['service', '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
[ "Dining experience begins with cracked, filthy vinyl tile flooring tables so small close together that you couldn't move." ]
[['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
[ "*Food:Just about anything on the menu, however the sandwhiches are most popular and recommended." ]
[['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
[ "To be fair, I realize I was there for lunch and that the food is probbably better at dinner service when a full kitchen staff has arrived and prepped, but I doubt I'd return to find out with so many other options in the neighborhood i already trust." ]
[['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
[ "Food and Service of the same high quality elsewhere in NY would have been twice the cost." ]
[['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
[ "Silky black bass with porcini mushrooms carries smoky, earthy and buttery overtones that somehow never overpower the fish, and whole-roasted baby pig includes belly meat, braised for 24 hours in five spice-ginger glaze, and yet the pork flavor is still fully present." ]
[['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
[ "Overall,it's a good place to have dinner and hang out if you do not mind waiting for food,weird music and rude manager." ]
[['food', 'neutral'], ['service', '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
[ "Went there for dinner last night w/ my boyfriend and a friend after work and got there around 7 so we were able to score seats in this tiny cramped space." ]
[['food', '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']]