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Datasets:
tner
/
mit_restaurant

Tasks:
Token Classification
Sub-tasks: named-entity-recognition
Languages: English
Multilinguality: monolingual
Size Categories: 1K<n<10K
Tags:
License:
Dataset card Viewer Files Community
1
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tokens
sequence
tags
sequence
[ "can", "you", "find", "me", "the", "cheapest", "mexican", "restaurant", "nearby" ]
[ 0, 0, 0, 0, 0, 9, 14, 0, 5 ]
[ "can", "you", "find", "me", "the", "closed", "burger", "king" ]
[ 0, 0, 0, 0, 0, 5, 7, 8 ]
[ "can", "you", "find", "me", "the", "closest", "cheesecake", "factory" ]
[ 0, 0, 0, 0, 0, 5, 7, 8 ]
[ "can", "you", "find", "me", "the", "closet", "mc", "donalds" ]
[ 0, 0, 0, 0, 0, 5, 7, 8 ]
[ "can", "you", "find", "me", "the", "coast", "line", "grill", "nearby", "with", "seating", "at", "the", "bar" ]
[ 0, 0, 0, 0, 0, 7, 8, 8, 5, 0, 3, 4, 4, 4 ]
[ "can", "you", "find", "me", "the", "location", "of", "daisy", "gs", "it", "has", "hotel", "dining" ]
[ 0, 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 3, 4 ]
[ "can", "you", "find", "me", "the", "nearest", "mcdonalds" ]
[ 0, 0, 0, 0, 0, 5, 7 ]
[ "can", "you", "find", "me", "the", "nearest", "pizzeria" ]
[ 0, 0, 0, 0, 0, 5, 14 ]
[ "can", "you", "find", "me", "the", "nicest", "restaurant", "for", "italian", "food" ]
[ 0, 0, 0, 0, 0, 1, 0, 0, 14, 0 ]
[ "can", "you", "find", "me", "the", "phone", "number", "for", "ihop", "on", "tilburg", "street" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 5, 6 ]
[ "can", "you", "find", "me", "the", "restaurant", "with", "the", "best", "reviews" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 2 ]
[ "can", "you", "find", "some", "reviews", "on", "the", "new", "restaurant", "henpeckss" ]
[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 7 ]
[ "can", "you", "find", "the", "bar", "cadete", "enterprise", "near", "west", "prescott", "street" ]
[ 0, 0, 0, 0, 3, 7, 8, 5, 6, 6, 6 ]
[ "can", "you", "find", "the", "black", "olive", "within", "5", "miles", "that", "offers", "group", "dining" ]
[ 0, 0, 0, 0, 7, 8, 5, 6, 6, 0, 0, 3, 4 ]
[ "can", "you", "find", "the", "closest", "taco", "bell" ]
[ 0, 0, 0, 0, 5, 7, 8 ]
[ "can", "you", "find", "the", "closet", "ihop" ]
[ 0, 0, 0, 0, 5, 7 ]
[ "can", "you", "find", "the", "locations", "and", "phone", "numbers", "of", "all", "the", "italian", "restaurants", "in", "the", "area" ]
[ 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 0 ]
[ "can", "you", "find", "the", "nearest", "italian", "restaurant" ]
[ 0, 0, 0, 0, 5, 14, 0 ]
[ "can", "you", "find", "the", "nearest", "mexican", "restaurant" ]
[ 0, 0, 0, 0, 5, 14, 0 ]
[ "can", "you", "find", "the", "nearest", "pizza", "place", "that", "is", "still", "open" ]
[ 0, 0, 0, 0, 5, 14, 5, 0, 0, 10, 11 ]
[ "can", "you", "find", "the", "phone", "number", "for", "the", "closest", "family", "style", "restaurant" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 5, 3, 4, 0 ]
[ "can", "you", "find", "the", "restaurant", "carinos", "italian", "grill", "near", "here", "that", "has", "a", "family", "setting" ]
[ 0, 0, 0, 0, 0, 7, 8, 8, 5, 6, 0, 0, 0, 3, 4 ]
[ "can", "you", "find", "the", "restaurant", "lucky", "fortune", "with", "a", "superior", "rating" ]
[ 0, 0, 0, 0, 0, 7, 8, 0, 0, 1, 2 ]
[ "can", "you", "find", "the", "restaurant", "marco", "polo" ]
[ 0, 0, 0, 0, 0, 7, 8 ]
[ "can", "you", "find", "the", "restaurant", "passims", "kitchen", "near", "downtown", "that", "has", "late", "dining" ]
[ 0, 0, 0, 0, 0, 7, 8, 5, 6, 0, 0, 10, 11 ]
[ "can", "you", "find", "the", "restaurant", "that", "is", "closest", "to", "me" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 6, 6 ]
[ "can", "you", "find", "us", "a", "cheap", "place", "to", "eat" ]
[ 0, 0, 0, 0, 0, 9, 0, 0, 0 ]
[ "can", "you", "find", "us", "a", "cheap", "place", "to", "eat", "near", "the", "park" ]
[ 0, 0, 0, 0, 0, 9, 0, 0, 0, 5, 6, 6 ]
[ "can", "you", "find", "us", "a", "kid", "friendly", "restaurant", "near", "by" ]
[ 0, 0, 0, 0, 0, 3, 4, 0, 5, 6 ]
[ "can", "you", "find", "us", "a", "mexican", "restaurant", "nearby" ]
[ 0, 0, 0, 0, 0, 14, 0, 5 ]
[ "can", "you", "find", "us", "a", "place", "to", "eat", "near", "the", "marina" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6 ]
[ "can", "you", "fine", "me", "a", "moderate", "priced", "causual", "dining", "restraunt", "in", "harvard", "square" ]
[ 0, 0, 0, 0, 0, 9, 0, 3, 4, 0, 0, 5, 6 ]
[ "can", "you", "get", "me", "a", "fast", "food", "place", "that", "is", "really", "cheap" ]
[ 0, 0, 0, 0, 0, 14, 16, 5, 0, 0, 9, 15 ]
[ "can", "you", "get", "me", "a", "reservation", "at", "an", "expensive", "fine", "dining", "restaurant" ]
[ 0, 0, 0, 0, 0, 3, 0, 0, 9, 3, 4, 0 ]
[ "can", "you", "get", "me", "a", "reservation", "to", "cristinas", "in", "roslyn", "ny" ]
[ 0, 0, 0, 0, 0, 0, 0, 7, 0, 5, 6 ]
[ "can", "you", "get", "me", "directions", "to", "apple", "bees" ]
[ 0, 0, 0, 0, 0, 0, 7, 8 ]
[ "can", "you", "get", "me", "directions", "to", "the", "closest", "seafood", "restaurant" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 14, 0 ]
[ "can", "you", "get", "me", "directions", "to", "the", "nearest", "dennys" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 7 ]
[ "can", "you", "get", "me", "the", "location", "of", "the", "closest", "bertuccis" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 5, 7 ]
[ "can", "you", "get", "me", "the", "number", "of", "the", "burrito", "place", "on", "52nd", "street" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 14, 0, 0, 5, 6 ]
[ "can", "you", "get", "me", "the", "number", "to", "bertucci" ]
[ 0, 0, 0, 0, 0, 0, 0, 7 ]
[ "can", "you", "get", "me", "to", "a", "diner", "that", "accepts", "american", "express" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 3, 4, 4 ]
[ "can", "you", "get", "take", "out", "at", "this", "restaurant" ]
[ 0, 0, 0, 3, 4, 0, 0, 0 ]
[ "can", "you", "get", "the", "phone", "numbers", "of", "all", "pizza", "delivery", "places", "within", "10", "miles" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 14, 3, 0, 5, 6, 6 ]
[ "can", "you", "get", "us", "directions", "to", "cracker", "barrel" ]
[ 0, 0, 0, 0, 0, 0, 7, 8 ]
[ "can", "you", "give", "me", "a", "list", "of", "all", "the", "carry", "outs", "in", "our", "current", "area" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 6, 6 ]
[ "can", "you", "give", "me", "a", "list", "of", "georgian", "restauarants", "that", "have", "carry", "out", "nearby" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 3, 4, 5 ]
[ "can", "you", "give", "me", "a", "list", "of", "restaurants", "that", "accepts", "credit", "cards" ]
[ 0, 0, 0, 0, 0, 7, 8, 0, 0, 3, 4, 4 ]
[ "can", "you", "give", "me", "a", "list", "of", "restaurants", "that", "serve", "ethiopian", "in", "the", "area" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 5, 6, 6 ]
[ "can", "you", "give", "me", "a", "list", "of", "restaurants", "with", "specials", "today", "in", "a", "5", "mile", "radius" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 9, 0, 5, 6, 6, 6, 6 ]
[ "can", "you", "give", "me", "a", "list", "of", "the", "four", "star", "seafood", "places", "in", "annapolis" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 14, 0, 0, 5 ]
[ "can", "you", "give", "me", "a", "phone", "number", "for", "the", "nearest", "five", "star", "establishment" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 1, 2, 0 ]
[ "can", "you", "give", "me", "directions", "to", "the", "closet", "coffee", "shop" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 14, 0 ]
[ "can", "you", "give", "me", "directions", "to", "the", "nearest", "county", "kitchen", "buffet" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 7, 8, 8 ]
[ "can", "you", "give", "me", "directions", "to", "the", "wendys" ]
[ 0, 0, 0, 0, 0, 0, 0, 7 ]
[ "can", "you", "give", "me", "some", "good", "restaurants", "nearby", "that", "serve", "sushi" ]
[ 0, 0, 0, 0, 0, 1, 0, 5, 0, 0, 12 ]
[ "can", "you", "give", "me", "the", "address", "of", "the", "cuban", "restaurant" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 14, 0 ]
[ "can", "you", "give", "me", "the", "closest", "five", "guys", "burgers", "and", "fries", "both", "the", "address", "and", "the", "phone", "number" ]
[ 0, 0, 0, 0, 0, 5, 7, 8, 8, 8, 8, 0, 0, 0, 0, 0, 0, 0 ]
[ "can", "you", "give", "me", "the", "name", "of", "a", "restaurant", "that", "is", "very", "close", "to", "stop", "at" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 6, 6 ]
[ "can", "you", "give", "me", "the", "number", "for", "a", "sushi", "takeout", "place" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 12, 3, 0 ]
[ "can", "you", "give", "me", "the", "telephone", "number", "and", "address", "for", "a", "fast", "food", "restaurant", "in", "the", "centre", "of", "town" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 16, 0, 0, 0, 5, 6, 6 ]
[ "can", "you", "help", "me", "find", "a", "casual", "restaurant", "with", "a", "buffet" ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 3 ]
[ "can", "you", "help", "me", "find", "a", "cheap", "place", "for", "a", "lot", "of", "people", "to", "eat" ]
[ 0, 0, 0, 0, 0, 0, 9, 15, 3, 4, 4, 4, 4, 4, 4 ]
[ "can", "you", "help", "me", "find", "a", "dairy", "queen", "in", "the", "next", "fifteen", "minutes" ]
[ 0, 0, 0, 0, 0, 0, 7, 8, 0, 0, 5, 6, 6 ]
[ "can", "you", "help", "me", "find", "a", "fast", "food", "restaurant", "with", "reasonable", "prices", "and", "that", "is", "open", "until", "at", "least", "11", "pm" ]
[ 0, 0, 0, 0, 0, 0, 14, 16, 0, 0, 9, 0, 0, 0, 0, 10, 11, 11, 11, 11, 11 ]
[ "can", "you", "help", "me", "find", "a", "fine", "dining", "establishment", "that", "is", "reasonably", "priced", "and", "is", "within", "2", "miles", "of", "here" ]
[ 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 9, 0, 0, 0, 5, 6, 6, 0, 0 ]
[ "can", "you", "help", "me", "find", "a", "fine", "dining", "restaurant" ]
[ 0, 0, 0, 0, 0, 0, 3, 4, 0 ]
[ "can", "you", "help", "me", "find", "a", "fun", "restaurant", "that", "serves", "brisket" ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 12 ]
[ "can", "you", "help", "me", "find", "a", "good", "steak", "joint" ]
[ 0, 0, 0, 0, 0, 0, 1, 14, 16 ]
[ "can", "you", "help", "me", "find", "a", "health", "food", "restaurant", "that", "serves", "meat", "too" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 0, 12, 0 ]
[ "can", "you", "help", "me", "find", "a", "hidden", "tudors", "biscuit", "world" ]
[ 0, 0, 0, 0, 0, 0, 7, 8, 8, 8 ]
[ "can", "you", "help", "me", "find", "a", "mcdonalds" ]
[ 0, 0, 0, 0, 0, 0, 7 ]
[ "can", "you", "help", "me", "find", "a", "mexican", "restaurant", "that", "has", "vegetarian", "options", "on", "the", "menu" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 14, 0, 0, 0, 0 ]
[ "can", "you", "help", "me", "find", "a", "murphys", "country", "kitchen", "that", "has", "a", "view", "and", "is", "nearby" ]
[ 0, 0, 0, 0, 0, 0, 7, 8, 8, 0, 0, 0, 3, 0, 0, 5 ]
[ "can", "you", "help", "me", "find", "a", "nearby", "kid", "friendly", "restaurant", "that", "serves", "clam", "sauce" ]
[ 0, 0, 0, 0, 0, 0, 5, 3, 4, 0, 0, 0, 12, 13 ]
[ "can", "you", "help", "me", "find", "a", "nearby", "uno", "chicago", "grill" ]
[ 0, 0, 0, 0, 0, 0, 5, 7, 8, 8 ]
[ "can", "you", "help", "me", "find", "a", "place", "to", "eat" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
[ "can", "you", "help", "me", "find", "a", "place", "to", "eat", "breakfast" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 14 ]
[ "can", "you", "help", "me", "find", "a", "reasonably", "priced", "restaurant", "that", "serves", "halal", "food", "and", "is", "open", "before", "9", "am" ]
[ 0, 0, 0, 0, 0, 0, 9, 0, 0, 0, 0, 14, 0, 0, 0, 10, 11, 11, 11 ]
[ "can", "you", "help", "me", "find", "a", "restaurant", "that", "is", "open", "evenings", "has", "great", "service", "and", "is", "withing", "3", "miles", "of", "here" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 11, 0, 3, 4, 0, 0, 5, 6, 6, 0, 0 ]
[ "can", "you", "help", "me", "find", "a", "restaurant", "that", "serves", "sashimi", "is", "open", "until", "9", "pm", "and", "is", "moderately", "priced" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 10, 11, 11, 11, 0, 0, 9, 0 ]
[ "can", "you", "help", "me", "find", "a", "romantic", "restaurant", "near", "here", "where", "i", "can", "order", "a", "sub" ]
[ 0, 0, 0, 0, 0, 0, 3, 0, 5, 6, 0, 0, 0, 0, 0, 12 ]
[ "can", "you", "help", "me", "find", "a", "vegan", "restaurant", "that", "serves", "caeser", "salad", "and", "provides", "outdoor", "dining" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 12, 13, 0, 0, 3, 4 ]
[ "can", "you", "help", "me", "find", "an", "affordable", "casual", "restaurant", "in", "harvard", "square" ]
[ 0, 0, 0, 0, 0, 0, 9, 3, 0, 0, 5, 6 ]
[ "can", "you", "help", "me", "find", "an", "expensive", "restaurant", "that", "features", "dishes", "made", "with", "lots", "of", "garlic" ]
[ 0, 0, 0, 0, 0, 0, 9, 0, 0, 0, 12, 13, 13, 14, 16, 16 ]
[ "can", "you", "help", "me", "find", "food" ]
[ 0, 0, 0, 0, 0, 0 ]
[ "can", "you", "help", "me", "find", "great", "food", "at", "a", "long", "john", "silvers", "that", "is", "open", "late" ]
[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 7, 8, 8, 0, 0, 10, 11 ]
[ "can", "you", "help", "me", "find", "restaurants", "nearby" ]
[ 0, 0, 0, 0, 0, 0, 5 ]
[ "can", "you", "help", "me", "find", "the", "closest", "chinese", "restaurant", "that", "also", "has", "carry", "out", "available" ]
[ 0, 0, 0, 0, 0, 0, 5, 14, 0, 0, 0, 0, 3, 4, 0 ]
[ "can", "you", "help", "me", "find", "the", "closest", "restaurant", "that", "is", "a", "local", "favorite", "and", "has", "a", "lunch", "special" ]
[ 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 3, 1, 0, 0, 0, 3, 4 ]
[ "can", "you", "help", "me", "find", "the", "name", "of", "the", "floating", "restaurant", "at", "the", "sunswept", "pier" ]
[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 6 ]
[ "can", "you", "help", "me", "find", "the", "prix", "fixe", "menu", "for", "the", "brighton", "house", "of", "pizza", "near", "the", "government", "center" ]
[ 0, 0, 0, 0, 0, 0, 3, 4, 4, 0, 0, 7, 8, 8, 8, 5, 0, 5, 6 ]
[ "can", "you", "help", "me", "locate", "a", "vietnamese", "restaurant", "in", "the", "next", "25", "miles" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 5, 6, 6, 6, 6 ]
[ "can", "you", "help", "me", "pick", "the", "italian", "restaurant", "with", "the", "best", "reviews", "in", "a", "5", "mile", "radius", "from", "my", "job", "that", "serves", "lunch" ]
[ 0, 0, 0, 0, 0, 0, 14, 0, 0, 0, 1, 0, 0, 0, 5, 6, 6, 6, 6, 6, 0, 0, 10 ]
[ "can", "you", "list", "all", "italian", "restaurants" ]
[ 0, 0, 0, 0, 14, 0 ]
[ "can", "you", "list", "all", "the", "mcdonalds", "near", "by" ]
[ 0, 0, 0, 0, 0, 7, 5, 6 ]
[ "can", "you", "list", "japanese", "restaurants", "in", "area" ]
[ 0, 0, 0, 14, 0, 5, 6 ]
[ "can", "you", "list", "some", "of", "the", "restaurants", "in", "the", "area" ]
[ 0, 0, 0, 0, 0, 0, 0, 5, 6, 6 ]
[ "can", "you", "list", "some", "seafood", "restaurants" ]
[ 0, 0, 0, 0, 14, 0 ]
[ "can", "you", "locate", "a", "bamboo", "house", "chinese", "restaurant", "for", "me", "with", "so", "large", "portions", "within", "a", "mile" ]
[ 0, 0, 0, 0, 7, 8, 14, 0, 0, 0, 0, 0, 3, 4, 5, 6, 6 ]
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Dataset Card for "tner/mit_restaurant"

Dataset Summary

MIT Restaurant NER dataset formatted in a part of TNER project.

  • Entity Types: Rating, Amenity, Location, Restaurant_Name, Price, Hours, Dish, Cuisine.

Dataset Structure

Data Instances

An example of train looks as follows.

{
    'tags': [0, 0, 0, 0, 0, 0, 0, 0, 5, 3, 4, 0],
    'tokens': ['can', 'you', 'find', 'the', 'phone', 'number', 'for', 'the', 'closest', 'family', 'style', 'restaurant']
}

Label ID

The label2id dictionary can be found at here.

{
    "O": 0,
    "B-Rating": 1,
    "I-Rating": 2,
    "B-Amenity": 3,
    "I-Amenity": 4,
    "B-Location": 5,
    "I-Location": 6,
    "B-Restaurant_Name": 7,
    "I-Restaurant_Name": 8,
    "B-Price": 9,
    "B-Hours": 10,
    "I-Hours": 11,
    "B-Dish": 12,
    "I-Dish": 13,
    "B-Cuisine": 14,
    "I-Price": 15,
    "I-Cuisine": 16
}

Data Splits

name train validation test
mit_restaurant 6900 760 1521
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Edit dataset card
Repository:
T-NER
Dataset:
MIT restaurant
Domain:
Restaurant
Number of Entity:
8
Size of downloaded dataset files:
1.18 MB
Size of the auto-converted Parquet files:
270 kB
Number of rows:
9,181

Models trained or fine-tuned on tner/mit_restaurant

Space using tner/mit_restaurant 1