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15,315
image_and_language
bird:train.json:7561
Which images have more than 20 object samples?
SELECT IMG_ID FROM IMG_OBJ GROUP BY IMG_ID HAVING COUNT(IMG_ID) > 20
[ "Which", "images", "have", "more", "than", "20", "object", "samples", "?" ]
[ { "id": 0, "type": "table", "value": "img_obj" }, { "id": 1, "type": "column", "value": "img_id" }, { "id": 2, "type": "value", "value": "20" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O" ]
15,316
card_games
bird:dev.json:367
Please provide the names of the artists who illustrated the card art in Phyrexian.
SELECT T1.artist FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T1.uuid = T2.uuid WHERE T2.language = 'Phyrexian'
[ "Please", "provide", "the", "names", "of", "the", "artists", "who", "illustrated", "the", "card", "art", "in", "Phyrexian", "." ]
[ { "id": 2, "type": "table", "value": "foreign_data" }, { "id": 4, "type": "value", "value": "Phyrexian" }, { "id": 3, "type": "column", "value": "language" }, { "id": 0, "type": "column", "value": "artist" }, { "id": 1, "type": "table", "value": "cards" }, { "id": 5, "type": "column", "value": "uuid" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
15,317
food_inspection_2
bird:train.json:6168
Provide the fine paid and the complete address of the establishment with inspection ID 48216.
SELECT DISTINCT T3.fine, T1.state, T1.city, T1.address FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE T2.inspection_id = 48216
[ "Provide", "the", "fine", "paid", "and", "the", "complete", "address", "of", "the", "establishment", "with", "inspection", "ID", "48216", "." ]
[ { "id": 5, "type": "column", "value": "inspection_id" }, { "id": 7, "type": "table", "value": "establishment" }, { "id": 8, "type": "table", "value": "inspection" }, { "id": 9, "type": "column", "value": "license_no" }, { "id": 4, "type": "table", "value": "violation" }, { "id": 3, "type": "column", "value": "address" }, { "id": 1, "type": "column", "value": "state" }, { "id": 6, "type": "value", "value": "48216" }, { "id": 0, "type": "column", "value": "fine" }, { "id": 2, "type": "column", "value": "city" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
15,318
allergy_1
spider:train_spider.json:513
Which allergy has most number of students affected?
SELECT Allergy FROM Has_allergy GROUP BY Allergy ORDER BY count(*) DESC LIMIT 1
[ "Which", "allergy", "has", "most", "number", "of", "students", "affected", "?" ]
[ { "id": 0, "type": "table", "value": "has_allergy" }, { "id": 1, "type": "column", "value": "allergy" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
15,319
authors
bird:train.json:3596
Please provide the titles of any two papers that are either preprinted or unpublished along with the full name of the journal to which those papers belong.
SELECT T1.Title, T2.FullName FROM Paper AS T1 INNER JOIN Journal AS T2 ON T1.JournalId = T2.Id WHERE T1.Year < 1 LIMIT 2
[ "Please", "provide", "the", "titles", "of", "any", "two", "papers", "that", "are", "either", "preprinted", "or", "unpublished", "along", "with", "the", "full", "name", "of", "the", "journal", "to", "which", "those", "papers", "belong", "." ]
[ { "id": 6, "type": "column", "value": "journalid" }, { "id": 1, "type": "column", "value": "fullname" }, { "id": 3, "type": "table", "value": "journal" }, { "id": 0, "type": "column", "value": "title" }, { "id": 2, "type": "table", "value": "paper" }, { "id": 4, "type": "column", "value": "year" }, { "id": 7, "type": "column", "value": "id" }, { "id": 5, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O" ]
15,320
coinmarketcap
bird:train.json:6288
When is the highest closed price of CHNCoin?
SELECT T2.date FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'CHNCoin' ORDER BY T2.close DESC LIMIT 1
[ "When", "is", "the", "highest", "closed", "price", "of", "CHNCoin", "?" ]
[ { "id": 2, "type": "table", "value": "historical" }, { "id": 4, "type": "value", "value": "CHNCoin" }, { "id": 7, "type": "column", "value": "coin_id" }, { "id": 1, "type": "table", "value": "coins" }, { "id": 5, "type": "column", "value": "close" }, { "id": 0, "type": "column", "value": "date" }, { "id": 3, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O" ]
15,321
disney
bird:train.json:4632
Please list the movies directed by Wolfgang Reitherman that can be watched by the general audience.
SELECT T1.movie_title FROM `movies_total_gross` AS T1 INNER JOIN director AS T2 ON T1.movie_title = T2.name WHERE T1.MPAA_rating = 'G' AND T2.director = 'Wolfgang Reitherman'
[ "Please", "list", "the", "movies", "directed", "by", "Wolfgang", "Reitherman", "that", "can", "be", "watched", "by", "the", "general", "audience", "." ]
[ { "id": 7, "type": "value", "value": "Wolfgang Reitherman" }, { "id": 1, "type": "table", "value": "movies_total_gross" }, { "id": 0, "type": "column", "value": "movie_title" }, { "id": 4, "type": "column", "value": "mpaa_rating" }, { "id": 2, "type": "table", "value": "director" }, { "id": 6, "type": "column", "value": "director" }, { "id": 3, "type": "column", "value": "name" }, { "id": 5, "type": "value", "value": "G" } ]
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,322
cre_Doc_Tracking_DB
spider:train_spider.json:4185
Give me the name and description of the location with code x.
SELECT location_name , location_description FROM Ref_locations WHERE location_code = "x"
[ "Give", "me", "the", "name", "and", "description", "of", "the", "location", "with", "code", "x." ]
[ { "id": 2, "type": "column", "value": "location_description" }, { "id": 0, "type": "table", "value": "ref_locations" }, { "id": 1, "type": "column", "value": "location_name" }, { "id": 3, "type": "column", "value": "location_code" }, { "id": 4, "type": "column", "value": "x" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN" ]
15,323
products_gen_characteristics
spider:train_spider.json:5547
Return the color code and description for the product with the name 'chervil'.
SELECT t1.color_code , t2.color_description FROM products AS t1 JOIN ref_colors AS t2 ON t1.color_code = t2.color_code WHERE t1.product_name = "chervil"
[ "Return", "the", "color", "code", "and", "description", "for", "the", "product", "with", "the", "name", "'", "chervil", "'", "." ]
[ { "id": 1, "type": "column", "value": "color_description" }, { "id": 4, "type": "column", "value": "product_name" }, { "id": 0, "type": "column", "value": "color_code" }, { "id": 3, "type": "table", "value": "ref_colors" }, { "id": 2, "type": "table", "value": "products" }, { "id": 5, "type": "column", "value": "chervil" } ]
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[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,324
food_inspection_2
bird:train.json:6229
Please list the names of taverns that paid a $100 fine upon inspection.
SELECT DISTINCT T1.dba_name FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE T1.facility_type = 'Tavern' AND T3.fine = 100
[ "Please", "list", "the", "names", "of", "taverns", "that", "paid", "a", "$", "100", "fine", "upon", "inspection", "." ]
[ { "id": 2, "type": "table", "value": "establishment" }, { "id": 4, "type": "column", "value": "inspection_id" }, { "id": 5, "type": "column", "value": "facility_type" }, { "id": 3, "type": "table", "value": "inspection" }, { "id": 9, "type": "column", "value": "license_no" }, { "id": 1, "type": "table", "value": "violation" }, { "id": 0, "type": "column", "value": "dba_name" }, { "id": 6, "type": "value", "value": "Tavern" }, { "id": 7, "type": "column", "value": "fine" }, { "id": 8, "type": "value", "value": "100" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-TABLE", "O" ]
15,325
activity_1
spider:train_spider.json:6718
Find the list of distinct ranks for faculty.
SELECT DISTINCT rank FROM Faculty
[ "Find", "the", "list", "of", "distinct", "ranks", "for", "faculty", "." ]
[ { "id": 0, "type": "table", "value": "faculty" }, { "id": 1, "type": "column", "value": "rank" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,326
vehicle_rent
bird:test.json:398
What are the names of all vehicles, ordered by model year descending?
SELECT name FROM vehicles ORDER BY model_year DESC
[ "What", "are", "the", "names", "of", "all", "vehicles", ",", "ordered", "by", "model", "year", "descending", "?" ]
[ { "id": 2, "type": "column", "value": "model_year" }, { "id": 0, "type": "table", "value": "vehicles" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 10, 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
15,328
superhero
bird:dev.json:839
In superheroes with weight less than 100, list the full name of the superheroes with brown eyes.
SELECT T1.full_name FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.eye_colour_id = T2.id WHERE T1.weight_kg < 100 AND T2.colour = 'Brown'
[ "In", "superheroes", "with", "weight", "less", "than", "100", ",", "list", "the", "full", "name", "of", "the", "superheroes", "with", "brown", "eyes", "." ]
[ { "id": 3, "type": "column", "value": "eye_colour_id" }, { "id": 0, "type": "column", "value": "full_name" }, { "id": 1, "type": "table", "value": "superhero" }, { "id": 5, "type": "column", "value": "weight_kg" }, { "id": 2, "type": "table", "value": "colour" }, { "id": 7, "type": "column", "value": "colour" }, { "id": 8, "type": "value", "value": "Brown" }, { "id": 6, "type": "value", "value": "100" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,329
small_bank_1
spider:train_spider.json:1810
Find the saving balance of the account with the highest checking balance.
SELECT T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance DESC LIMIT 1
[ "Find", "the", "saving", "balance", "of", "the", "account", "with", "the", "highest", "checking", "balance", "." ]
[ { "id": 2, "type": "table", "value": "accounts" }, { "id": 3, "type": "table", "value": "checking" }, { "id": 0, "type": "column", "value": "balance" }, { "id": 1, "type": "table", "value": "savings" }, { "id": 4, "type": "column", "value": "custid" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,330
language_corpus
bird:train.json:5750
How many times on page number 44 does the word "votives" appear?
SELECT T2.occurrences FROM words AS T1 INNER JOIN pages_words AS T2 ON T1.wid = T2.wid WHERE T1.word = 'votives' AND T2.pid = 44
[ "How", "many", "times", "on", "page", "number", "44", "does", "the", "word", "\"", "votives", "\"", "appear", "?" ]
[ { "id": 0, "type": "column", "value": "occurrences" }, { "id": 2, "type": "table", "value": "pages_words" }, { "id": 5, "type": "value", "value": "votives" }, { "id": 1, "type": "table", "value": "words" }, { "id": 4, "type": "column", "value": "word" }, { "id": 3, "type": "column", "value": "wid" }, { "id": 6, "type": "column", "value": "pid" }, { "id": 7, "type": "value", "value": "44" } ]
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[ "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O" ]
15,332
county_public_safety
spider:train_spider.json:2541
What are the crime rates of counties sorted by number of offices ascending?
SELECT Crime_rate FROM county_public_safety ORDER BY Police_officers ASC
[ "What", "are", "the", "crime", "rates", "of", "counties", "sorted", "by", "number", "of", "offices", "ascending", "?" ]
[ { "id": 0, "type": "table", "value": "county_public_safety" }, { "id": 2, "type": "column", "value": "police_officers" }, { "id": 1, "type": "column", "value": "crime_rate" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,333
cars
bird:train.json:3086
How many cylinders does the cheapest car have?
SELECT T1.cylinders FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID ORDER BY price ASC LIMIT 1
[ "How", "many", "cylinders", "does", "the", "cheapest", "car", "have", "?" ]
[ { "id": 0, "type": "column", "value": "cylinders" }, { "id": 2, "type": "table", "value": "price" }, { "id": 3, "type": "column", "value": "price" }, { "id": 1, "type": "table", "value": "data" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,334
soccer_2016
bird:train.json:1906
Write the name of the player who was the man of the series more than one time.
SELECT T2.Player_Name FROM Season AS T1 INNER JOIN Player AS T2 ON T1.Man_of_the_Series = T2.Player_Id WHERE T1.Man_of_the_Series > 1
[ "Write", "the", "name", "of", "the", "player", "who", "was", "the", "man", "of", "the", "series", "more", "than", "one", "time", "." ]
[ { "id": 3, "type": "column", "value": "man_of_the_series" }, { "id": 0, "type": "column", "value": "player_name" }, { "id": 5, "type": "column", "value": "player_id" }, { "id": 1, "type": "table", "value": "season" }, { "id": 2, "type": "table", "value": "player" }, { "id": 4, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
15,335
retails
bird:train.json:6882
Among all the suppliers in debt, how many of them are in Europe?
SELECT COUNT(T1.n_nationkey) FROM nation AS T1 INNER JOIN region AS T2 ON T1.n_regionkey = T2.r_regionkey INNER JOIN supplier AS T3 ON T1.n_nationkey = T3.s_nationkey WHERE T2.r_name = 'EUROPE' AND T3.s_acctbal < 0
[ "Among", "all", "the", "suppliers", "in", "debt", ",", "how", "many", "of", "them", "are", "in", "Europe", "?" ]
[ { "id": 1, "type": "column", "value": "n_nationkey" }, { "id": 4, "type": "column", "value": "s_nationkey" }, { "id": 9, "type": "column", "value": "n_regionkey" }, { "id": 10, "type": "column", "value": "r_regionkey" }, { "id": 7, "type": "column", "value": "s_acctbal" }, { "id": 0, "type": "table", "value": "supplier" }, { "id": 2, "type": "table", "value": "nation" }, { "id": 3, "type": "table", "value": "region" }, { "id": 5, "type": "column", "value": "r_name" }, { "id": 6, "type": "value", "value": "EUROPE" }, { "id": 8, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-VALUE", "O" ]
15,336
hockey
bird:train.json:7673
Please list the nicknames of the players who have won the All-Rookie award and are born in March.
SELECT DISTINCT T1.nameNick FROM Master AS T1 INNER JOIN AwardsPlayers AS T2 ON T1.playerID = T2.playerID WHERE T2.award = 'All-Rookie' AND T1.birthMon = 3
[ "Please", "list", "the", "nicknames", "of", "the", "players", "who", "have", "won", "the", "All", "-", "Rookie", "award", "and", "are", "born", "in", "March", "." ]
[ { "id": 2, "type": "table", "value": "awardsplayers" }, { "id": 5, "type": "value", "value": "All-Rookie" }, { "id": 0, "type": "column", "value": "namenick" }, { "id": 3, "type": "column", "value": "playerid" }, { "id": 6, "type": "column", "value": "birthmon" }, { "id": 1, "type": "table", "value": "master" }, { "id": 4, "type": "column", "value": "award" }, { "id": 7, "type": "value", "value": "3" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,337
sales_in_weather
bird:train.json:8172
Show the sea level status recorded by the weather station of store no.19 on 2013/2/24.
SELECT T1.sealevel FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr WHERE T1.`date` = '2013-02-24' AND T2.store_nbr = 19
[ "Show", "the", "sea", "level", "status", "recorded", "by", "the", "weather", "station", "of", "store", "no.19", "on", "2013/2/24", "." ]
[ { "id": 3, "type": "column", "value": "station_nbr" }, { "id": 5, "type": "value", "value": "2013-02-24" }, { "id": 6, "type": "column", "value": "store_nbr" }, { "id": 0, "type": "column", "value": "sealevel" }, { "id": 2, "type": "table", "value": "relation" }, { "id": 1, "type": "table", "value": "weather" }, { "id": 4, "type": "column", "value": "date" }, { "id": 7, "type": "value", "value": "19" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-TABLE", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,338
car_racing
bird:test.json:1597
What are the average laps of all the drivers who are younger than 20?
SELECT avg(Laps) FROM driver WHERE age < 20
[ "What", "are", "the", "average", "laps", "of", "all", "the", "drivers", "who", "are", "younger", "than", "20", "?" ]
[ { "id": 0, "type": "table", "value": "driver" }, { "id": 3, "type": "column", "value": "laps" }, { "id": 1, "type": "column", "value": "age" }, { "id": 2, "type": "value", "value": "20" } ]
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[ "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O" ]
15,339
airline
bird:train.json:5870
Which airline does the aircraft with the fastest flight belong to?
SELECT T1.OP_CARRIER_AIRLINE_ID FROM Airlines AS T1 INNER JOIN Airports AS T2 ON T1.ORIGIN = T2.Code WHERE T1.ACTUAL_ELAPSED_TIME IS NOT NULL AND T1.CRS_ELAPSED_TIME IS NOT NULL ORDER BY T1.ACTUAL_ELAPSED_TIME - T1.CRS_ELAPSED_TIME ASC LIMIT 1
[ "Which", "airline", "does", "the", "aircraft", "with", "the", "fastest", "flight", "belong", "to", "?" ]
[ { "id": 0, "type": "column", "value": "op_carrier_airline_id" }, { "id": 5, "type": "column", "value": "actual_elapsed_time" }, { "id": 6, "type": "column", "value": "crs_elapsed_time" }, { "id": 1, "type": "table", "value": "airlines" }, { "id": 2, "type": "table", "value": "airports" }, { "id": 3, "type": "column", "value": "origin" }, { "id": 4, "type": "column", "value": "code" } ]
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[ "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O" ]
15,340
art_1
bird:test.json:1219
What is the birth year of each distinct artists who created sculptures after 1920?
SELECT DISTINCT T1.birthYear FROM artists AS T1 JOIN sculptures AS T2 ON T1.artistID = T2.sculptorID WHERE T2.year > 1920
[ "What", "is", "the", "birth", "year", "of", "each", "distinct", "artists", "who", "created", "sculptures", "after", "1920", "?" ]
[ { "id": 2, "type": "table", "value": "sculptures" }, { "id": 6, "type": "column", "value": "sculptorid" }, { "id": 0, "type": "column", "value": "birthyear" }, { "id": 5, "type": "column", "value": "artistid" }, { "id": 1, "type": "table", "value": "artists" }, { "id": 3, "type": "column", "value": "year" }, { "id": 4, "type": "value", "value": "1920" } ]
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[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
15,341
e_government
spider:train_spider.json:6340
Which is the email of the party that has used the services the most number of times?
SELECT t1.party_email FROM parties AS t1 JOIN party_services AS t2 ON t1.party_id = t2.customer_id GROUP BY t1.party_email ORDER BY count(*) DESC LIMIT 1
[ "Which", "is", "the", "email", "of", "the", "party", "that", "has", "used", "the", "services", "the", "most", "number", "of", "times", "?" ]
[ { "id": 2, "type": "table", "value": "party_services" }, { "id": 0, "type": "column", "value": "party_email" }, { "id": 4, "type": "column", "value": "customer_id" }, { "id": 3, "type": "column", "value": "party_id" }, { "id": 1, "type": "table", "value": "parties" } ]
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[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O" ]
15,342
e_commerce
bird:test.json:68
What is the status code of the items being ordered and shipped and its corresponding shipment tracking number?
SELECT T1.order_item_status_code , T3.shipment_tracking_number FROM Order_items AS T1 JOIN Shipment_Items AS T2 ON T1.order_item_id = T2.order_item_id JOIN Shipments AS T3 ON T2.shipment_id = T3.shipment_id
[ "What", "is", "the", "status", "code", "of", "the", "items", "being", "ordered", "and", "shipped", "and", "its", "corresponding", "shipment", "tracking", "number", "?" ]
[ { "id": 1, "type": "column", "value": "shipment_tracking_number" }, { "id": 0, "type": "column", "value": "order_item_status_code" }, { "id": 4, "type": "table", "value": "shipment_items" }, { "id": 6, "type": "column", "value": "order_item_id" }, { "id": 3, "type": "table", "value": "order_items" }, { "id": 5, "type": "column", "value": "shipment_id" }, { "id": 2, "type": "table", "value": "shipments" } ]
[ { "entity_id": 0, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 1, "token_idxs": [ 16, 17 ] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O" ]
15,343
address
bird:train.json:5122
For the county where DeSantis Ron is from, what is the average female median age?
SELECT SUM(T4.female_median_age) / COUNT(T1.county) FROM country AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id INNER JOIN zip_data AS T4 ON T1.zip_code = T4.zip_code WHERE T3.first_name = 'DeSantis' AND T3.last_name = 'Ron'
[ "For", "the", "county", "where", "DeSantis", "Ron", "is", "from", ",", "what", "is", "the", "average", "female", "median", "age", "?" ]
[ { "id": 7, "type": "column", "value": "female_median_age" }, { "id": 12, "type": "column", "value": "cognress_rep_id" }, { "id": 10, "type": "table", "value": "zip_congress" }, { "id": 3, "type": "column", "value": "first_name" }, { "id": 5, "type": "column", "value": "last_name" }, { "id": 0, "type": "table", "value": "zip_data" }, { "id": 1, "type": "table", "value": "congress" }, { "id": 2, "type": "column", "value": "zip_code" }, { "id": 4, "type": "value", "value": "DeSantis" }, { "id": 11, "type": "column", "value": "district" }, { "id": 9, "type": "table", "value": "country" }, { "id": 8, "type": "column", "value": "county" }, { "id": 6, "type": "value", "value": "Ron" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [ 13, 14, 15 ] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O" ]
15,345
party_host
spider:train_spider.json:2661
Count the number of parties.
SELECT count(*) FROM party
[ "Count", "the", "number", "of", "parties", "." ]
[ { "id": 0, "type": "table", "value": "party" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O" ]
15,347
disney
bird:train.json:4621
How much more total box office gross did the Walt Disney Company have in revenue in 1998 than in 1997?
SELECT SUM(CASE WHEN `Year` = 1998 THEN Total ELSE 0 END) - SUM(CASE WHEN `Year` = 1997 THEN Total ELSE 0 END) FROM revenue
[ "How", "much", "more", "total", "box", "office", "gross", "did", "the", "Walt", "Disney", "Company", "have", "in", "revenue", "in", "1998", "than", "in", "1997", "?" ]
[ { "id": 0, "type": "table", "value": "revenue" }, { "id": 2, "type": "column", "value": "total" }, { "id": 3, "type": "column", "value": "Year" }, { "id": 4, "type": "value", "value": "1998" }, { "id": 5, "type": "value", "value": "1997" }, { "id": 1, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "B-VALUE", "O" ]
15,348
retails
bird:train.json:6809
Please name any three parts that have an available quantity of more than 9998.
SELECT T1.p_name FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey WHERE T2.ps_availqty > 9998 LIMIT 3
[ "Please", "name", "any", "three", "parts", "that", "have", "an", "available", "quantity", "of", "more", "than", "9998", "." ]
[ { "id": 3, "type": "column", "value": "ps_availqty" }, { "id": 6, "type": "column", "value": "ps_partkey" }, { "id": 5, "type": "column", "value": "p_partkey" }, { "id": 2, "type": "table", "value": "partsupp" }, { "id": 0, "type": "column", "value": "p_name" }, { "id": 1, "type": "table", "value": "part" }, { "id": 4, "type": "value", "value": "9998" } ]
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[ "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,349
customer_complaints
spider:train_spider.json:5786
What is the description of the product named "Chocolate"?
SELECT product_description FROM products WHERE product_name = "Chocolate"
[ "What", "is", "the", "description", "of", "the", "product", "named", "\"", "Chocolate", "\"", "?" ]
[ { "id": 1, "type": "column", "value": "product_description" }, { "id": 2, "type": "column", "value": "product_name" }, { "id": 3, "type": "column", "value": "Chocolate" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "O", "O" ]
15,350
department_store
spider:train_spider.json:4783
List the order id, customer id for orders in Cancelled status, ordered by their order dates.
SELECT order_id , customer_id FROM customer_orders WHERE order_status_code = "Cancelled" ORDER BY order_date
[ "List", "the", "order", "i", "d", ",", "customer", "i", "d", "for", "orders", "in", "Cancelled", "status", ",", "ordered", "by", "their", "order", "dates", "." ]
[ { "id": 3, "type": "column", "value": "order_status_code" }, { "id": 0, "type": "table", "value": "customer_orders" }, { "id": 2, "type": "column", "value": "customer_id" }, { "id": 5, "type": "column", "value": "order_date" }, { "id": 4, "type": "column", "value": "Cancelled" }, { "id": 1, "type": "column", "value": "order_id" } ]
[ { "entity_id": 0, "token_idxs": [ 9, 10 ] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 18, 19 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-TABLE", "I-TABLE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,351
allergy_1
spider:train_spider.json:517
Show all allergy type with number of students affected.
SELECT T2.allergytype , count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy GROUP BY T2.allergytype
[ "Show", "all", "allergy", "type", "with", "number", "of", "students", "affected", "." ]
[ { "id": 2, "type": "table", "value": "allergy_type" }, { "id": 0, "type": "column", "value": "allergytype" }, { "id": 1, "type": "table", "value": "has_allergy" }, { "id": 3, "type": "column", "value": "allergy" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,352
world_development_indicators
bird:train.json:2125
In the countries for which the latest trade data are from 2013, what was the GDP growth in 2014? List them in the ascending order of GDP.
SELECT DISTINCT T1.CountryCode, T2.Value FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.LatestTradeData = 2013 AND T2.IndicatorName LIKE 'GDP growth (annual %)' AND T2.year = 2014 AND T2.Value > 0 ORDER BY T2.Value ASC
[ "In", "the", "countries", "for", "which", "the", "latest", "trade", "data", "are", "from", "2013", ",", "what", "was", "the", "GDP", "growth", "in", "2014", "?", "List", "them", "in", "the", "ascending", "order", "of", "GDP", "." ]
[ { "id": 7, "type": "value", "value": "GDP growth (annual %)" }, { "id": 4, "type": "column", "value": "latesttradedata" }, { "id": 6, "type": "column", "value": "indicatorname" }, { "id": 0, "type": "column", "value": "countrycode" }, { "id": 3, "type": "table", "value": "indicators" }, { "id": 2, "type": "table", "value": "country" }, { "id": 1, "type": "column", "value": "value" }, { "id": 5, "type": "value", "value": "2013" }, { "id": 8, "type": "column", "value": "year" }, { "id": 9, "type": "value", "value": "2014" }, { "id": 10, "type": "value", "value": "0" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,353
sales_in_weather
bird:train.json:8150
Please list the dates on which the sale of item no.5 in store no.3 exceeded 100 and the average wind speed exceeded 10.
SELECT T1.`date` FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr INNER JOIN weather AS T3 ON T2.station_nbr = T3.station_nbr WHERE T2.store_nbr = 3 AND T1.item_nbr = 5 AND T1.units > 100 AND T3.avgspeed > 10
[ "Please", "list", "the", "dates", "on", "which", "the", "sale", "of", "item", "no.5", "in", "store", "no.3", "exceeded", "100", "and", "the", "average", "wind", "speed", "exceeded", "10", "." ]
[ { "id": 2, "type": "table", "value": "sales_in_weather" }, { "id": 4, "type": "column", "value": "station_nbr" }, { "id": 5, "type": "column", "value": "store_nbr" }, { "id": 3, "type": "table", "value": "relation" }, { "id": 7, "type": "column", "value": "item_nbr" }, { "id": 11, "type": "column", "value": "avgspeed" }, { "id": 1, "type": "table", "value": "weather" }, { "id": 9, "type": "column", "value": "units" }, { "id": 0, "type": "column", "value": "date" }, { "id": 10, "type": "value", "value": "100" }, { "id": 12, "type": "value", "value": "10" }, { "id": 6, "type": "value", "value": "3" }, { "id": 8, "type": "value", "value": "5" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
15,354
chicago_crime
bird:train.json:8717
What are the general and specific descriptions of the most common crime incidents that happened in an aircraft?
SELECT T2.primary_description, T2.secondary_description FROM Crime AS T1 INNER JOIN IUCR AS T2 ON T1.iucr_no = T2.iucr_no WHERE T1.location_description = 'AIRCRAFT' GROUP BY T1.iucr_no ORDER BY COUNT(T1.iucr_no) DESC LIMIT 1
[ "What", "are", "the", "general", "and", "specific", "descriptions", "of", "the", "most", "common", "crime", "incidents", "that", "happened", "in", "an", "aircraft", "?" ]
[ { "id": 2, "type": "column", "value": "secondary_description" }, { "id": 5, "type": "column", "value": "location_description" }, { "id": 1, "type": "column", "value": "primary_description" }, { "id": 6, "type": "value", "value": "AIRCRAFT" }, { "id": 0, "type": "column", "value": "iucr_no" }, { "id": 3, "type": "table", "value": "crime" }, { "id": 4, "type": "table", "value": "iucr" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O" ]
15,355
party_people
spider:train_spider.json:2051
Show all ministers and parties they belong to in descending order of the time they took office.
SELECT minister , party_name FROM party ORDER BY took_office DESC
[ "Show", "all", "ministers", "and", "parties", "they", "belong", "to", "in", "descending", "order", "of", "the", "time", "they", "took", "office", "." ]
[ { "id": 3, "type": "column", "value": "took_office" }, { "id": 2, "type": "column", "value": "party_name" }, { "id": 1, "type": "column", "value": "minister" }, { "id": 0, "type": "table", "value": "party" } ]
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[ "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,356
movie_platform
bird:train.json:55
In which year was the movie "La Antena" released?
SELECT movie_release_year FROM movies WHERE movie_title = 'La Antena'
[ "In", "which", "year", "was", "the", "movie", "\"", "La", "Antena", "\"", "released", "?" ]
[ { "id": 1, "type": "column", "value": "movie_release_year" }, { "id": 2, "type": "column", "value": "movie_title" }, { "id": 3, "type": "value", "value": "La Antena" }, { "id": 0, "type": "table", "value": "movies" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7, 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O", "O", "O" ]
15,357
customers_and_addresses
spider:train_spider.json:6060
Find the average order quantity per order.
SELECT avg(order_quantity) FROM order_items
[ "Find", "the", "average", "order", "quantity", "per", "order", "." ]
[ { "id": 1, "type": "column", "value": "order_quantity" }, { "id": 0, "type": "table", "value": "order_items" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O" ]
15,358
retail_complains
bird:train.json:302
How many male clients born in the year 1977 were given priority 0 in their complaints?
SELECT COUNT(T1.sex) FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.sex = 'Male' AND T2.priority = 0 AND T1.year = 1997
[ "How", "many", "male", "clients", "born", "in", "the", "year", "1977", "were", "given", "priority", "0", "in", "their", "complaints", "?" ]
[ { "id": 1, "type": "table", "value": "callcenterlogs" }, { "id": 4, "type": "column", "value": "rand client" }, { "id": 3, "type": "column", "value": "client_id" }, { "id": 6, "type": "column", "value": "priority" }, { "id": 0, "type": "table", "value": "client" }, { "id": 5, "type": "value", "value": "Male" }, { "id": 8, "type": "column", "value": "year" }, { "id": 9, "type": "value", "value": "1997" }, { "id": 2, "type": "column", "value": "sex" }, { "id": 7, "type": "value", "value": "0" } ]
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[ "O", "O", "B-VALUE", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O" ]
15,359
driving_school
spider:train_spider.json:6698
How many lessons were in cancelled state?
SELECT count(*) FROM Lessons WHERE lesson_status_code = "Cancelled";
[ "How", "many", "lessons", "were", "in", "cancelled", "state", "?" ]
[ { "id": 1, "type": "column", "value": "lesson_status_code" }, { "id": 2, "type": "column", "value": "Cancelled" }, { "id": 0, "type": "table", "value": "lessons" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O" ]
15,360
college_1
spider:train_spider.json:3216
How many professors have a Ph.D. in each department?
SELECT count(*) , dept_code FROM professor WHERE prof_high_degree = 'Ph.D.' GROUP BY dept_code
[ "How", "many", "professors", "have", "a", "Ph.D.", "in", "each", "department", "?" ]
[ { "id": 2, "type": "column", "value": "prof_high_degree" }, { "id": 0, "type": "table", "value": "professor" }, { "id": 1, "type": "column", "value": "dept_code" }, { "id": 3, "type": "value", "value": "Ph.D." } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O" ]
15,361
inn_1
spider:train_spider.json:2606
How many rooms are there?
SELECT count(*) FROM Rooms;
[ "How", "many", "rooms", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "rooms" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O" ]
15,362
student_loan
bird:train.json:4432
State name of disabled students who have the longest duration of absense from school.
SELECT T1.name FROM disabled AS T1 INNER JOIN longest_absense_from_school AS T2 ON T1.name = T2.name ORDER BY T2.month DESC LIMIT 1
[ "State", "name", "of", "disabled", "students", "who", "have", "the", "longest", "duration", "of", "absense", "from", "school", "." ]
[ { "id": 2, "type": "table", "value": "longest_absense_from_school" }, { "id": 1, "type": "table", "value": "disabled" }, { "id": 3, "type": "column", "value": "month" }, { "id": 0, "type": "column", "value": "name" } ]
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[ "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O" ]
15,363
art_1
bird:test.json:1300
What are the ids of the paintings created before all of the paintings in gallery 240?
SELECT paintingID FROM paintings WHERE YEAR < (SELECT min(YEAR) FROM paintings WHERE LOCATION = 'Gallery 240')
[ "What", "are", "the", "ids", "of", "the", "paintings", "created", "before", "all", "of", "the", "paintings", "in", "gallery", "240", "?" ]
[ { "id": 4, "type": "value", "value": "Gallery 240" }, { "id": 1, "type": "column", "value": "paintingid" }, { "id": 0, "type": "table", "value": "paintings" }, { "id": 3, "type": "column", "value": "location" }, { "id": 2, "type": "column", "value": "year" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 14, 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
15,364
college_2
spider:train_spider.json:1432
Find the name and salary of instructors who are advisors of the students from the Math department.
SELECT T2.name , T2.salary FROM advisor AS T1 JOIN instructor AS T2 ON T1.i_id = T2.id JOIN student AS T3 ON T1.s_id = T3.id WHERE T3.dept_name = 'Math'
[ "Find", "the", "name", "and", "salary", "of", "instructors", "who", "are", "advisors", "of", "the", "students", "from", "the", "Math", "department", "." ]
[ { "id": 6, "type": "table", "value": "instructor" }, { "id": 3, "type": "column", "value": "dept_name" }, { "id": 2, "type": "table", "value": "student" }, { "id": 5, "type": "table", "value": "advisor" }, { "id": 1, "type": "column", "value": "salary" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "value", "value": "Math" }, { "id": 7, "type": "column", "value": "s_id" }, { "id": 9, "type": "column", "value": "i_id" }, { "id": 8, "type": "column", "value": "id" } ]
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[ "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,365
european_football_2
bird:dev.json:1050
What is the preferred foot when attacking of the youngest football player?
SELECT t2.preferred_foot FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id ORDER BY t1.birthday DESC LIMIT 1
[ "What", "is", "the", "preferred", "foot", "when", "attacking", "of", "the", "youngest", "football", "player", "?" ]
[ { "id": 2, "type": "table", "value": "player_attributes" }, { "id": 0, "type": "column", "value": "preferred_foot" }, { "id": 4, "type": "column", "value": "player_api_id" }, { "id": 3, "type": "column", "value": "birthday" }, { "id": 1, "type": "table", "value": "player" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,366
european_football_2
bird:dev.json:1025
Give the name of the league had the most goals in the 2016 season?
SELECT t2.name FROM Match AS t1 INNER JOIN League AS t2 ON t1.league_id = t2.id WHERE t1.season = '2015/2016' GROUP BY t2.name ORDER BY SUM(t1.home_team_goal + t1.away_team_goal) DESC LIMIT 1
[ "Give", "the", "name", "of", "the", "league", "had", "the", "most", "goals", "in", "the", "2016", "season", "?" ]
[ { "id": 7, "type": "column", "value": "home_team_goal" }, { "id": 8, "type": "column", "value": "away_team_goal" }, { "id": 4, "type": "value", "value": "2015/2016" }, { "id": 5, "type": "column", "value": "league_id" }, { "id": 2, "type": "table", "value": "league" }, { "id": 3, "type": "column", "value": "season" }, { "id": 1, "type": "table", "value": "match" }, { "id": 0, "type": "column", "value": "name" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,367
beer_factory
bird:train.json:5240
Among the users that permit the company to send regular emails to them, how many of them had made a transaction with a Visa card in July, 2014?
SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.SubscribedToEmailList = 'TRUE' AND T2.CreditCardType = 'Visa' AND STRFTIME('%Y-%m', T2.TransactionDate) = '2014-07'
[ "Among", "the", "users", "that", "permit", "the", "company", "to", "send", "regular", "emails", "to", "them", ",", "how", "many", "of", "them", "had", "made", "a", "transaction", "with", "a", "Visa", "card", "in", "July", ",", "2014", "?" ]
[ { "id": 3, "type": "column", "value": "subscribedtoemaillist" }, { "id": 9, "type": "column", "value": "transactiondate" }, { "id": 5, "type": "column", "value": "creditcardtype" }, { "id": 1, "type": "table", "value": "transaction" }, { "id": 2, "type": "column", "value": "customerid" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 7, "type": "value", "value": "2014-07" }, { "id": 8, "type": "value", "value": "%Y-%m" }, { "id": 4, "type": "value", "value": "TRUE" }, { "id": 6, "type": "value", "value": "Visa" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 21 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 24 ] }, { "entity_id": 7, "token_idxs": [ 29 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O" ]
15,368
european_football_2
bird:dev.json:1060
How many players were born after 1990?
SELECT COUNT(id) FROM Player WHERE STRFTIME('%Y', birthday) > '1990'
[ "How", "many", "players", "were", "born", "after", "1990", "?" ]
[ { "id": 4, "type": "column", "value": "birthday" }, { "id": 0, "type": "table", "value": "player" }, { "id": 1, "type": "value", "value": "1990" }, { "id": 2, "type": "column", "value": "id" }, { "id": 3, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
15,369
manufactory_1
spider:train_spider.json:5320
Find the number of products for each manufacturer, showing the name of each company.
SELECT count(*) , T2.name FROM products AS T1 JOIN manufacturers AS T2 ON T1.Manufacturer = T2.code GROUP BY T2.name
[ "Find", "the", "number", "of", "products", "for", "each", "manufacturer", ",", "showing", "the", "name", "of", "each", "company", "." ]
[ { "id": 2, "type": "table", "value": "manufacturers" }, { "id": 3, "type": "column", "value": "manufacturer" }, { "id": 1, "type": "table", "value": "products" }, { "id": 0, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
15,370
station_weather
spider:train_spider.json:3162
Find the number of trains starting from each origin.
SELECT origin , count(*) FROM train GROUP BY origin
[ "Find", "the", "number", "of", "trains", "starting", "from", "each", "origin", "." ]
[ { "id": 1, "type": "column", "value": "origin" }, { "id": 0, "type": "table", "value": "train" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O" ]
15,371
superhero
bird:dev.json:732
Which publisher published the slowest superhero?
SELECT T2.publisher_name FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id INNER JOIN hero_attribute AS T3 ON T1.id = T3.hero_id INNER JOIN attribute AS T4 ON T3.attribute_id = T4.id WHERE T4.attribute_name = 'Speed' ORDER BY T3.attribute_value LIMIT 1
[ "Which", "publisher", "published", "the", "slowest", "superhero", "?" ]
[ { "id": 4, "type": "column", "value": "attribute_value" }, { "id": 0, "type": "column", "value": "publisher_name" }, { "id": 2, "type": "column", "value": "attribute_name" }, { "id": 5, "type": "table", "value": "hero_attribute" }, { "id": 6, "type": "column", "value": "attribute_id" }, { "id": 11, "type": "column", "value": "publisher_id" }, { "id": 1, "type": "table", "value": "attribute" }, { "id": 8, "type": "table", "value": "superhero" }, { "id": 9, "type": "table", "value": "publisher" }, { "id": 10, "type": "column", "value": "hero_id" }, { "id": 3, "type": "value", "value": "Speed" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 5 ] }, { "entity_id": 9, "token_idxs": [ 1 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "O", "O", "O", "B-TABLE", "O" ]
15,372
aan_1
bird:test.json:1015
Find the name and number of citations of the author who has most citations among all authors?
SELECT T3.name , count(*) FROM Citation AS T1 JOIN Author_list AS T2 ON T1.cited_paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id GROUP BY T2.author_id ORDER BY count(*) DESC LIMIT 1
[ "Find", "the", "name", "and", "number", "of", "citations", "of", "the", "author", "who", "has", "most", "citations", "among", "all", "authors", "?" ]
[ { "id": 5, "type": "column", "value": "cited_paper_id" }, { "id": 4, "type": "table", "value": "author_list" }, { "id": 0, "type": "column", "value": "author_id" }, { "id": 3, "type": "table", "value": "citation" }, { "id": 6, "type": "column", "value": "paper_id" }, { "id": 2, "type": "table", "value": "author" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 16 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,373
address_1
bird:test.json:815
What is the average, minimum, maximum distance between two cities?
SELECT avg(distance) , min(distance) , max(distance) FROM Direct_distance
[ "What", "is", "the", "average", ",", "minimum", ",", "maximum", "distance", "between", "two", "cities", "?" ]
[ { "id": 0, "type": "table", "value": "direct_distance" }, { "id": 1, "type": "column", "value": "distance" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
15,374
cre_Theme_park
spider:train_spider.json:5945
Show the transportation method most people choose to get to tourist attractions.
SELECT How_to_Get_There FROM Tourist_Attractions GROUP BY How_to_Get_There ORDER BY COUNT(*) DESC LIMIT 1
[ "Show", "the", "transportation", "method", "most", "people", "choose", "to", "get", "to", "tourist", "attractions", "." ]
[ { "id": 0, "type": "table", "value": "tourist_attractions" }, { "id": 1, "type": "column", "value": "how_to_get_there" } ]
[ { "entity_id": 0, "token_idxs": [ 10, 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,375
retail_world
bird:train.json:6376
What are the territory descriptions of territories in the Eastern region?
SELECT DISTINCT T1.TerritoryDescription FROM Territories AS T1 INNER JOIN Region AS T2 ON T1.RegionID = T2.RegionID WHERE T2.RegionDescription = 'Eastern' ORDER BY T1.TerritoryDescription
[ "What", "are", "the", "territory", "descriptions", "of", "territories", "in", "the", "Eastern", "region", "?" ]
[ { "id": 0, "type": "column", "value": "territorydescription" }, { "id": 3, "type": "column", "value": "regiondescription" }, { "id": 1, "type": "table", "value": "territories" }, { "id": 5, "type": "column", "value": "regionid" }, { "id": 4, "type": "value", "value": "Eastern" }, { "id": 2, "type": "table", "value": "region" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 10 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-TABLE", "O", "O", "B-VALUE", "B-TABLE", "O" ]
15,376
ice_hockey_draft
bird:train.json:6981
Among the players who played in OHL league during the regular season in 2007-2008, who is the player that attained the most number of assist?
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2007-2008' AND T1.LEAGUE = 'OHL' AND T1.GAMETYPE = 'Regular Season' ORDER BY T1.A DESC LIMIT 1
[ "Among", "the", "players", "who", "played", "in", "OHL", "league", "during", "the", "regular", "season", "in", "2007", "-", "2008", ",", "who", "is", "the", "player", "that", "attained", "the", "most", "number", "of", "assist", "?" ]
[ { "id": 10, "type": "value", "value": "Regular Season" }, { "id": 1, "type": "table", "value": "seasonstatus" }, { "id": 0, "type": "column", "value": "playername" }, { "id": 2, "type": "table", "value": "playerinfo" }, { "id": 6, "type": "value", "value": "2007-2008" }, { "id": 9, "type": "column", "value": "gametype" }, { "id": 4, "type": "column", "value": "eliteid" }, { "id": 5, "type": "column", "value": "season" }, { "id": 7, "type": "column", "value": "league" }, { "id": 8, "type": "value", "value": "OHL" }, { "id": 3, "type": "column", "value": "a" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 20 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 11 ] }, { "entity_id": 6, "token_idxs": [ 13, 14, 15 ] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [ 6 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [ 10 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "B-VALUE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,377
election
spider:train_spider.json:2754
In which distinct years was the governor "Eliot Spitzer"?
SELECT DISTINCT YEAR FROM party WHERE Governor = "Eliot Spitzer"
[ "In", "which", "distinct", "years", "was", "the", "governor", "\"", "Eliot", "Spitzer", "\"", "?" ]
[ { "id": 3, "type": "column", "value": "Eliot Spitzer" }, { "id": 2, "type": "column", "value": "governor" }, { "id": 0, "type": "table", "value": "party" }, { "id": 1, "type": "column", "value": "year" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 8, 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O" ]
15,378
public_review_platform
bird:train.json:3900
How many businesses ID sell beer and wine?
SELECT COUNT(business_id) FROM Business_Attributes WHERE attribute_id = 1 AND attribute_value = 'beer_and_wine'
[ "How", "many", "businesses", "ID", "sell", "beer", "and", "wine", "?" ]
[ { "id": 0, "type": "table", "value": "business_attributes" }, { "id": 4, "type": "column", "value": "attribute_value" }, { "id": 5, "type": "value", "value": "beer_and_wine" }, { "id": 2, "type": "column", "value": "attribute_id" }, { "id": 1, "type": "column", "value": "business_id" }, { "id": 3, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2, 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5, 6, 7 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,379
university_rank
bird:test.json:1798
What is the total number of students enrolled in an university with a rank of 5 or below?
SELECT sum(enrollment) FROM University AS T1 JOIN Overall_ranking AS T2 ON T1.university_id = T2.university_id WHERE T2.rank >= 5
[ "What", "is", "the", "total", "number", "of", "students", "enrolled", "in", "an", "university", "with", "a", "rank", "of", "5", "or", "below", "?" ]
[ { "id": 1, "type": "table", "value": "overall_ranking" }, { "id": 5, "type": "column", "value": "university_id" }, { "id": 0, "type": "table", "value": "university" }, { "id": 4, "type": "column", "value": "enrollment" }, { "id": 2, "type": "column", "value": "rank" }, { "id": 3, "type": "value", "value": "5" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 15 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "O" ]
15,380
protein_institute
spider:train_spider.json:1929
How many institutions do not have an associated protein in our record?
SELECT count(*) FROM institution WHERE institution_id NOT IN (SELECT institution_id FROM protein)
[ "How", "many", "institutions", "do", "not", "have", "an", "associated", "protein", "in", "our", "record", "?" ]
[ { "id": 1, "type": "column", "value": "institution_id" }, { "id": 0, "type": "table", "value": "institution" }, { "id": 2, "type": "table", "value": "protein" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,381
flight_1
spider:train_spider.json:352
What is the name and distance for the aircraft that has an id of 12?
SELECT name , distance FROM Aircraft WHERE aid = 12
[ "What", "is", "the", "name", "and", "distance", "for", "the", "aircraft", "that", "has", "an", "i", "d", "of", "12", "?" ]
[ { "id": 0, "type": "table", "value": "aircraft" }, { "id": 2, "type": "column", "value": "distance" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "column", "value": "aid" }, { "id": 4, "type": "value", "value": "12" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 12, 13 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
15,382
superhero
bird:dev.json:733
How many gold-eyed superheroes did Marvel Comics publish?
SELECT COUNT(T1.id) FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id INNER JOIN colour AS T3 ON T1.eye_colour_id = T3.id WHERE T2.publisher_name = 'Marvel Comics' AND T3.colour = 'Gold'
[ "How", "many", "gold", "-", "eyed", "superheroes", "did", "Marvel", "Comics", "publish", "?" ]
[ { "id": 5, "type": "column", "value": "publisher_name" }, { "id": 4, "type": "column", "value": "eye_colour_id" }, { "id": 6, "type": "value", "value": "Marvel Comics" }, { "id": 9, "type": "column", "value": "publisher_id" }, { "id": 2, "type": "table", "value": "superhero" }, { "id": 3, "type": "table", "value": "publisher" }, { "id": 0, "type": "table", "value": "colour" }, { "id": 7, "type": "column", "value": "colour" }, { "id": 8, "type": "value", "value": "Gold" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 7, 8 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 2 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-VALUE", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "I-VALUE", "B-TABLE", "O" ]
15,384
simpson_episodes
bird:train.json:4188
List the name character awarded for the Outstanding Voice-Over Performance award in 2009.
SELECT T2.character FROM Award AS T1 INNER JOIN Character_Award AS T2 ON T1.award_id = T2.award_id WHERE T1.year = 2009 AND T1.award = 'Outstanding Voice-Over Performance';
[ "List", "the", "name", "character", "awarded", "for", "the", "Outstanding", "Voice", "-", "Over", "Performance", "award", "in", "2009", "." ]
[ { "id": 7, "type": "value", "value": "Outstanding Voice-Over Performance" }, { "id": 2, "type": "table", "value": "character_award" }, { "id": 0, "type": "column", "value": "character" }, { "id": 3, "type": "column", "value": "award_id" }, { "id": 1, "type": "table", "value": "award" }, { "id": 6, "type": "column", "value": "award" }, { "id": 4, "type": "column", "value": "year" }, { "id": 5, "type": "value", "value": "2009" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [ 12 ] }, { "entity_id": 7, "token_idxs": [ 7, 8, 9, 10, 11 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
15,385
codebase_comments
bird:train.json:666
What is the task of the method that is in the Czech language?
SELECT DISTINCT SUBSTR(SUBSTR(Name, INSTR(Name, '.') + 1), 1, INSTR(SUBSTR(Name, INSTR(Name, '.') + 1), '.') - 1) task FROM Method WHERE Lang = 'cs'
[ "What", "is", "the", "task", "of", "the", "method", "that", "is", "in", "the", "Czech", "language", "?" ]
[ { "id": 0, "type": "table", "value": "method" }, { "id": 1, "type": "column", "value": "lang" }, { "id": 4, "type": "column", "value": "name" }, { "id": 2, "type": "value", "value": "cs" }, { "id": 3, "type": "value", "value": "1" }, { "id": 5, "type": "value", "value": "." } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,386
donor
bird:train.json:3266
How many donors who donated to the city of Pocatello are not teachers?
SELECT COUNT(donationid) FROM donations WHERE donor_city = 'Pocatello' AND is_teacher_acct = 'f'
[ "How", "many", "donors", "who", "donated", "to", "the", "city", "of", "Pocatello", "are", "not", "teachers", "?" ]
[ { "id": 4, "type": "column", "value": "is_teacher_acct" }, { "id": 1, "type": "column", "value": "donationid" }, { "id": 2, "type": "column", "value": "donor_city" }, { "id": 0, "type": "table", "value": "donations" }, { "id": 3, "type": "value", "value": "Pocatello" }, { "id": 5, "type": "value", "value": "f" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 8 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "B-VALUE", "O", "O", "B-COLUMN", "O" ]
15,387
customers_and_orders
bird:test.json:309
How many customers have an order?
SELECT count(DISTINCT customer_id) FROM Customer_orders
[ "How", "many", "customers", "have", "an", "order", "?" ]
[ { "id": 0, "type": "table", "value": "customer_orders" }, { "id": 1, "type": "column", "value": "customer_id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
15,389
card_games
bird:dev.json:483
Please list the Italian text ruling of all the cards in the set Coldsnap.
SELECT DISTINCT T1.text FROM foreign_data AS T1 INNER JOIN cards AS T2 ON T2.uuid = T1.uuid INNER JOIN sets AS T3 ON T3.code = T2.setCode WHERE T3.name = 'Coldsnap' AND T1.language = 'Italian'
[ "Please", "list", "the", "Italian", "text", "ruling", "of", "all", "the", "cards", "in", "the", "set", "Coldsnap", "." ]
[ { "id": 2, "type": "table", "value": "foreign_data" }, { "id": 7, "type": "value", "value": "Coldsnap" }, { "id": 8, "type": "column", "value": "language" }, { "id": 5, "type": "column", "value": "setcode" }, { "id": 9, "type": "value", "value": "Italian" }, { "id": 3, "type": "table", "value": "cards" }, { "id": 0, "type": "column", "value": "text" }, { "id": 1, "type": "table", "value": "sets" }, { "id": 4, "type": "column", "value": "code" }, { "id": 6, "type": "column", "value": "name" }, { "id": 10, "type": "column", "value": "uuid" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 3 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,390
theme_gallery
spider:train_spider.json:1685
How many exhibitions have a attendance more than 100 or have a ticket price below 10?
SELECT count(*) FROM exhibition_record AS T1 JOIN exhibition AS T2 ON T1.exhibition_id = T2.exhibition_id WHERE T1.attendance > 100 OR T2.ticket_price < 10
[ "How", "many", "exhibitions", "have", "a", "attendance", "more", "than", "100", "or", "have", "a", "ticket", "price", "below", "10", "?" ]
[ { "id": 0, "type": "table", "value": "exhibition_record" }, { "id": 2, "type": "column", "value": "exhibition_id" }, { "id": 5, "type": "column", "value": "ticket_price" }, { "id": 1, "type": "table", "value": "exhibition" }, { "id": 3, "type": "column", "value": "attendance" }, { "id": 4, "type": "value", "value": "100" }, { "id": 6, "type": "value", "value": "10" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [ 12, 13 ] }, { "entity_id": 6, "token_idxs": [ 15 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-VALUE", "O" ]
15,391
customers_card_transactions
spider:train_spider.json:675
How many accounts does the customer with first name Art and last name Turcotte have?
SELECT count(*) FROM Accounts AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T2.customer_first_name = "Art" AND T2.customer_last_name = "Turcotte"
[ "How", "many", "accounts", "does", "the", "customer", "with", "first", "name", "Art", "and", "last", "name", "Turcotte", "have", "?" ]
[ { "id": 3, "type": "column", "value": "customer_first_name" }, { "id": 5, "type": "column", "value": "customer_last_name" }, { "id": 2, "type": "column", "value": "customer_id" }, { "id": 1, "type": "table", "value": "customers" }, { "id": 0, "type": "table", "value": "accounts" }, { "id": 6, "type": "column", "value": "Turcotte" }, { "id": 4, "type": "column", "value": "Art" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [ 6, 7, 8 ] }, { "entity_id": 6, "token_idxs": [ 13 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O" ]
15,392
books
bird:train.json:6090
Who ordered the book with the cheapest price?
SELECT T3.first_name, T3.last_name FROM order_line AS T1 INNER JOIN cust_order AS T2 ON T2.order_id = T1.order_id INNER JOIN customer AS T3 ON T3.customer_id = T2.customer_id ORDER BY T1.price ASC LIMIT 1
[ "Who", "ordered", "the", "book", "with", "the", "cheapest", "price", "?" ]
[ { "id": 6, "type": "column", "value": "customer_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 4, "type": "table", "value": "order_line" }, { "id": 5, "type": "table", "value": "cust_order" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 2, "type": "table", "value": "customer" }, { "id": 7, "type": "column", "value": "order_id" }, { "id": 3, "type": "column", "value": "price" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 1 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,393
food_inspection_2
bird:train.json:6238
What is the inspection ID where the employee named "David Hodges" is currently employed in the "Kamayan Express" establishment?
SELECT T2.inspection_id FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN employee AS T3 ON T2.employee_id = T3.employee_id WHERE T3.first_name = 'David' AND T3.last_name = 'Hodges' AND T1.dba_name = 'KAMAYAN EXPRESS'
[ "What", "is", "the", "inspection", "ID", "where", "the", "employee", "named", "\"", "David", "Hodges", "\"", "is", "currently", "employed", "in", "the", "\"", "Kamayan", "Express", "\"", "establishment", "?" ]
[ { "id": 10, "type": "value", "value": "KAMAYAN EXPRESS" }, { "id": 0, "type": "column", "value": "inspection_id" }, { "id": 2, "type": "table", "value": "establishment" }, { "id": 4, "type": "column", "value": "employee_id" }, { "id": 3, "type": "table", "value": "inspection" }, { "id": 5, "type": "column", "value": "first_name" }, { "id": 11, "type": "column", "value": "license_no" }, { "id": 7, "type": "column", "value": "last_name" }, { "id": 1, "type": "table", "value": "employee" }, { "id": 9, "type": "column", "value": "dba_name" }, { "id": 8, "type": "value", "value": "Hodges" }, { "id": 6, "type": "value", "value": "David" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 7 ] }, { "entity_id": 2, "token_idxs": [ 22 ] }, { "entity_id": 3, "token_idxs": [ 3 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 11 ] }, { "entity_id": 9, "token_idxs": [ 8 ] }, { "entity_id": 10, "token_idxs": [ 19, 20 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
15,394
cre_Doc_Tracking_DB
spider:train_spider.json:4221
What is the location name of the document "Robin CV"?
SELECT T3.location_name FROM All_documents AS T1 JOIN Document_locations AS T2 ON T1.document_id = T2.document_id JOIN Ref_locations AS T3 ON T2.location_code = T3.location_code WHERE T1.document_name = "Robin CV"
[ "What", "is", "the", "location", "name", "of", "the", "document", "\"", "Robin", "CV", "\"", "?" ]
[ { "id": 5, "type": "table", "value": "document_locations" }, { "id": 0, "type": "column", "value": "location_name" }, { "id": 1, "type": "table", "value": "ref_locations" }, { "id": 2, "type": "column", "value": "document_name" }, { "id": 4, "type": "table", "value": "all_documents" }, { "id": 6, "type": "column", "value": "location_code" }, { "id": 7, "type": "column", "value": "document_id" }, { "id": 3, "type": "column", "value": "Robin CV" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 8 ] }, { "entity_id": 6, "token_idxs": [ 3 ] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "B-COLUMN", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O" ]
15,395
works_cycles
bird:train.json:7350
How many employees who began working in 2009 or later had night shifts?
SELECT COUNT(T1.BusinessEntityID) FROM EmployeeDepartmentHistory AS T1 INNER JOIN Shift AS T2 ON T1.ShiftId = T2.ShiftId WHERE T2.ShiftId = 3 AND STRFTIME('%Y', T2.StartTime) >= '2009'
[ "How", "many", "employees", "who", "began", "working", "in", "2009", "or", "later", "had", "night", "shifts", "?" ]
[ { "id": 0, "type": "table", "value": "employeedepartmenthistory" }, { "id": 2, "type": "column", "value": "businessentityid" }, { "id": 7, "type": "column", "value": "starttime" }, { "id": 3, "type": "column", "value": "shiftid" }, { "id": 1, "type": "table", "value": "shift" }, { "id": 5, "type": "value", "value": "2009" }, { "id": 6, "type": "value", "value": "%Y" }, { "id": 4, "type": "value", "value": "3" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 12 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 7 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-TABLE", "O" ]
15,396
music_4
spider:train_spider.json:6182
Return the number of music festivals of each category.
SELECT Category , COUNT(*) FROM music_festival GROUP BY Category
[ "Return", "the", "number", "of", "music", "festivals", "of", "each", "category", "." ]
[ { "id": 0, "type": "table", "value": "music_festival" }, { "id": 1, "type": "column", "value": "category" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 8 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "O" ]
15,397
coinmarketcap
bird:train.json:6254
Name the coin with the highest percentage price changed in 24 hours. State the transaction date and price.
SELECT T1.name, T2.DATE, T2.price FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.percent_change_24h = ( SELECT MAX(percent_change_24h) FROM historical )
[ "Name", "the", "coin", "with", "the", "highest", "percentage", "price", "changed", "in", "24", "hours", ".", "State", "the", "transaction", "date", "and", "price", "." ]
[ { "id": 5, "type": "column", "value": "percent_change_24h" }, { "id": 4, "type": "table", "value": "historical" }, { "id": 7, "type": "column", "value": "coin_id" }, { "id": 2, "type": "column", "value": "price" }, { "id": 3, "type": "table", "value": "coins" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "date" }, { "id": 6, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 0 ] }, { "entity_id": 1, "token_idxs": [ 16 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 2 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 6 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O" ]
15,398
region_building
bird:test.json:328
Give me the capitals of the regions whose area is larger than 10000.
SELECT Capital FROM region WHERE Area > 10000
[ "Give", "me", "the", "capitals", "of", "the", "regions", "whose", "area", "is", "larger", "than", "10000", "." ]
[ { "id": 1, "type": "column", "value": "capital" }, { "id": 0, "type": "table", "value": "region" }, { "id": 3, "type": "value", "value": "10000" }, { "id": 2, "type": "column", "value": "area" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,399
apartment_rentals
spider:train_spider.json:1272
Show the apartment numbers of apartments with unit status availability of both 0 and 1.
SELECT T1.apt_number FROM Apartments AS T1 JOIN View_Unit_Status AS T2 ON T1.apt_id = T2.apt_id WHERE T2.available_yn = 0 INTERSECT SELECT T1.apt_number FROM Apartments AS T1 JOIN View_Unit_Status AS T2 ON T1.apt_id = T2.apt_id WHERE T2.available_yn = 1
[ "Show", "the", "apartment", "numbers", "of", "apartments", "with", "unit", "status", "availability", "of", "both", "0", "and", "1", "." ]
[ { "id": 2, "type": "table", "value": "view_unit_status" }, { "id": 3, "type": "column", "value": "available_yn" }, { "id": 0, "type": "column", "value": "apt_number" }, { "id": 1, "type": "table", "value": "apartments" }, { "id": 6, "type": "column", "value": "apt_id" }, { "id": 4, "type": "value", "value": "0" }, { "id": 5, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 7, 8 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,400
match_season
spider:train_spider.json:1053
Count the number of countries.
SELECT count(*) FROM country
[ "Count", "the", "number", "of", "countries", "." ]
[ { "id": 0, "type": "table", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 0 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "B-TABLE", "O", "O", "O", "O", "O" ]
15,401
public_review_platform
bird:train.json:3818
Which city has the highest number of businesses in the food industry whose number of reviews is high?
SELECT T1.city FROM Business AS T1 INNER JOIN Business_Categories ON T1.business_id = Business_Categories.business_id INNER JOIN Categories AS T3 ON Business_Categories.category_id = T3.category_id WHERE T1.review_count LIKE 'High' AND T3.category_name LIKE 'Food' GROUP BY T1.city
[ "Which", "city", "has", "the", "highest", "number", "of", "businesses", "in", "the", "food", "industry", "whose", "number", "of", "reviews", "is", "high", "?" ]
[ { "id": 3, "type": "table", "value": "business_categories" }, { "id": 7, "type": "column", "value": "category_name" }, { "id": 5, "type": "column", "value": "review_count" }, { "id": 4, "type": "column", "value": "category_id" }, { "id": 9, "type": "column", "value": "business_id" }, { "id": 1, "type": "table", "value": "categories" }, { "id": 2, "type": "table", "value": "business" }, { "id": 0, "type": "column", "value": "city" }, { "id": 6, "type": "value", "value": "High" }, { "id": 8, "type": "value", "value": "Food" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [ 10 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "O" ]
15,402
coinmarketcap
bird:train.json:6269
What was the number of Bitcoins verifiably burned until 2013/4/28?
SELECT T2.max_supply - T2.total_supply FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2013-04-28' AND T1.name = 'Bitcoin'
[ "What", "was", "the", "number", "of", "Bitcoins", "verifiably", "burned", "until", "2013/4/28", "?" ]
[ { "id": 3, "type": "column", "value": "total_supply" }, { "id": 1, "type": "table", "value": "historical" }, { "id": 2, "type": "column", "value": "max_supply" }, { "id": 7, "type": "value", "value": "2013-04-28" }, { "id": 5, "type": "column", "value": "coin_id" }, { "id": 9, "type": "value", "value": "Bitcoin" }, { "id": 0, "type": "table", "value": "coins" }, { "id": 6, "type": "column", "value": "date" }, { "id": 8, "type": "column", "value": "name" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O" ]
15,403
simpson_episodes
bird:train.json:4300
What are the titles of the episodes that have received more 7-star votes than the season average?
SELECT DISTINCT T1.episode_id FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T2.stars = 7 AND T2.votes > 0.7 * ( SELECT CAST(COUNT(votes) AS REAL) / COUNT(CASE WHEN stars = 7 THEN 1 ELSE 0 END) FROM Vote );
[ "What", "are", "the", "titles", "of", "the", "episodes", "that", "have", "received", "more", "7", "-", "star", "votes", "than", "the", "season", "average", "?" ]
[ { "id": 0, "type": "column", "value": "episode_id" }, { "id": 1, "type": "table", "value": "episode" }, { "id": 3, "type": "column", "value": "stars" }, { "id": 5, "type": "column", "value": "votes" }, { "id": 2, "type": "table", "value": "vote" }, { "id": 6, "type": "value", "value": "0.7" }, { "id": 4, "type": "value", "value": "7" }, { "id": 7, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "O" ]
15,404
menu
bird:train.json:5569
How many dishes are there on page 1 of menu ID12882?
SELECT SUM(CASE WHEN T1.page_number = 1 THEN 1 ELSE 0 END) FROM MenuPage AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.menu_page_id WHERE T1.menu_id = 12882
[ "How", "many", "dishes", "are", "there", "on", "page", "1", "of", "menu", "ID12882", "?" ]
[ { "id": 5, "type": "column", "value": "menu_page_id" }, { "id": 8, "type": "column", "value": "page_number" }, { "id": 0, "type": "table", "value": "menupage" }, { "id": 1, "type": "table", "value": "menuitem" }, { "id": 2, "type": "column", "value": "menu_id" }, { "id": 3, "type": "value", "value": "12882" }, { "id": 4, "type": "column", "value": "id" }, { "id": 6, "type": "value", "value": "0" }, { "id": 7, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 7 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-VALUE", "O", "B-COLUMN", "B-VALUE", "O" ]
15,405
hr_1
spider:train_spider.json:3426
Return the full names and salaries of employees with null commissions.
SELECT first_name , last_name , salary FROM employees WHERE commission_pct = "null"
[ "Return", "the", "full", "names", "and", "salaries", "of", "employees", "with", "null", "commissions", "." ]
[ { "id": 4, "type": "column", "value": "commission_pct" }, { "id": 1, "type": "column", "value": "first_name" }, { "id": 0, "type": "table", "value": "employees" }, { "id": 2, "type": "column", "value": "last_name" }, { "id": 3, "type": "column", "value": "salary" }, { "id": 5, "type": "column", "value": "null" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [ 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "B-COLUMN", "O" ]
15,406
music_platform_2
bird:train.json:7941
The 'More Stupider: A 90-Day Fiance Podcast' belongs to which category and what is the average rating of the podcast?
SELECT AVG(T3.rating) FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id INNER JOIN reviews AS T3 ON T3.podcast_id = T2.podcast_id WHERE T2.title = 'More Stupider: A 90-Day Fiance Podcast'
[ "The", "'", "More", "Stupider", ":", "A", "90", "-", "Day", "Fiance", "Podcast", "'", "belongs", "to", "which", "category", "and", "what", "is", "the", "average", "rating", "of", "the", "podcast", "?" ]
[ { "id": 2, "type": "value", "value": "More Stupider: A 90-Day Fiance Podcast" }, { "id": 4, "type": "table", "value": "categories" }, { "id": 6, "type": "column", "value": "podcast_id" }, { "id": 5, "type": "table", "value": "podcasts" }, { "id": 0, "type": "table", "value": "reviews" }, { "id": 3, "type": "column", "value": "rating" }, { "id": 1, "type": "column", "value": "title" } ]
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[ "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
15,407
simpson_episodes
bird:train.json:4164
Which character won the Outstanding Voice-Over Performance award in 2009?
SELECT DISTINCT T1.character FROM Character_Award AS T1 INNER JOIN Award AS T2 ON T1.award_id = T2.award_id WHERE T2.award = 'Outstanding Voice-Over Performance' AND T2.year = 2009 AND T2.result = 'Winner';
[ "Which", "character", "won", "the", "Outstanding", "Voice", "-", "Over", "Performance", "award", "in", "2009", "?" ]
[ { "id": 5, "type": "value", "value": "Outstanding Voice-Over Performance" }, { "id": 1, "type": "table", "value": "character_award" }, { "id": 0, "type": "column", "value": "character" }, { "id": 3, "type": "column", "value": "award_id" }, { "id": 8, "type": "column", "value": "result" }, { "id": 9, "type": "value", "value": "Winner" }, { "id": 2, "type": "table", "value": "award" }, { "id": 4, "type": "column", "value": "award" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2009" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [ 4, 5, 6, 7, 8 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 11 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O", "B-VALUE", "O" ]
15,408
art_1
bird:test.json:1254
Find the distinct titles of all the paintings that have a longer height than some painting on canvas?
SELECT DISTINCT title FROM paintings WHERE height_mm > (SELECT min(height_mm) FROM paintings WHERE mediumOn = "canvas")
[ "Find", "the", "distinct", "titles", "of", "all", "the", "paintings", "that", "have", "a", "longer", "height", "than", "some", "painting", "on", "canvas", "?" ]
[ { "id": 0, "type": "table", "value": "paintings" }, { "id": 2, "type": "column", "value": "height_mm" }, { "id": 3, "type": "column", "value": "mediumon" }, { "id": 4, "type": "column", "value": "canvas" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 17 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,409
products_gen_characteristics
spider:train_spider.json:5559
Return the characteristic names of the 'sesame' product.
SELECT t3.characteristic_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id WHERE t1.product_name = "sesame"
[ "Return", "the", "characteristic", "names", "of", "the", "'", "sesame", "'", "product", "." ]
[ { "id": 5, "type": "table", "value": "product_characteristics" }, { "id": 0, "type": "column", "value": "characteristic_name" }, { "id": 6, "type": "column", "value": "characteristic_id" }, { "id": 1, "type": "table", "value": "characteristics" }, { "id": 2, "type": "column", "value": "product_name" }, { "id": 7, "type": "column", "value": "product_id" }, { "id": 4, "type": "table", "value": "products" }, { "id": 3, "type": "column", "value": "sesame" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,410
works_cycles
bird:train.json:7043
What is the profit of the product with the highest list price and of the product with the lowest list price other than 0? Indicates the depth the component is from its parent.
SELECT ( SELECT ListPrice - StandardCost FROM Product WHERE ListPrice != 0 ORDER BY ListPrice DESC LIMIT 1 ) , ( SELECT ListPrice - StandardCost FROM Product WHERE ListPrice != 0 ORDER BY ListPrice LIMIT 1 )
[ "What", "is", "the", "profit", "of", "the", "product", "with", "the", "highest", "list", "price", "and", "of", "the", "product", "with", "the", "lowest", "list", "price", "other", "than", "0", "?", "Indicates", "the", "depth", "the", "component", "is", "from", "its", "parent", "." ]
[ { "id": 3, "type": "column", "value": "standardcost" }, { "id": 1, "type": "column", "value": "listprice" }, { "id": 0, "type": "table", "value": "product" }, { "id": 2, "type": "value", "value": "0" } ]
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[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,411
legislator
bird:train.json:4892
For how many terms have the oldest current legislator served?
SELECT COUNT(T2.bioguide) FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.birthday_bio = ( SELECT MIN(birthday_bio) FROM current )
[ "For", "how", "many", "terms", "have", "the", "oldest", "current", "legislator", "served", "?" ]
[ { "id": 1, "type": "table", "value": "current-terms" }, { "id": 2, "type": "column", "value": "birthday_bio" }, { "id": 4, "type": "column", "value": "bioguide_id" }, { "id": 3, "type": "column", "value": "bioguide" }, { "id": 0, "type": "table", "value": "current" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
15,412
book_review
bird:test.json:602
What is the rank of the book with the smallest number of pages?
SELECT T2.Rank FROM book AS T1 JOIN review AS T2 ON T1.Book_ID = T2.Book_ID ORDER BY T1.Pages ASC LIMIT 1
[ "What", "is", "the", "rank", "of", "the", "book", "with", "the", "smallest", "number", "of", "pages", "?" ]
[ { "id": 4, "type": "column", "value": "book_id" }, { "id": 2, "type": "table", "value": "review" }, { "id": 3, "type": "column", "value": "pages" }, { "id": 0, "type": "column", "value": "rank" }, { "id": 1, "type": "table", "value": "book" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,413
formula_1
bird:dev.json:892
State the driver with the most points scored. Find his full name with that points.
SELECT T3.forename, T3.surname, T2.points FROM races AS T1 INNER JOIN driverStandings AS T2 ON T2.raceId = T1.raceId INNER JOIN drivers AS T3 ON T3.driverId = T2.driverId ORDER BY T2.points DESC LIMIT 1
[ "State", "the", "driver", "with", "the", "most", "points", "scored", ".", "Find", "his", "full", "name", "with", "that", "points", "." ]
[ { "id": 5, "type": "table", "value": "driverstandings" }, { "id": 0, "type": "column", "value": "forename" }, { "id": 6, "type": "column", "value": "driverid" }, { "id": 1, "type": "column", "value": "surname" }, { "id": 3, "type": "table", "value": "drivers" }, { "id": 2, "type": "column", "value": "points" }, { "id": 7, "type": "column", "value": "raceid" }, { "id": 4, "type": "table", "value": "races" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O" ]
15,414
legislator
bird:train.json:4854
List all the representatives in 1789 along with the districts and state.
SELECT T2.district, T2.state FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.start LIKE '1789%'
[ "List", "all", "the", "representatives", "in", "1789", "along", "with", "the", "districts", "and", "state", "." ]
[ { "id": 3, "type": "table", "value": "historical-terms" }, { "id": 6, "type": "column", "value": "bioguide_id" }, { "id": 2, "type": "table", "value": "historical" }, { "id": 0, "type": "column", "value": "district" }, { "id": 7, "type": "column", "value": "bioguide" }, { "id": 1, "type": "column", "value": "state" }, { "id": 4, "type": "column", "value": "start" }, { "id": 5, "type": "value", "value": "1789%" } ]
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[ "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
15,415
disney
bird:train.json:4637
Give the name of the movie which the song "I Thought I Lost You" is associated with.
SELECT movie_title FROM characters WHERE song = 'I Thought I Lost You'
[ "Give", "the", "name", "of", "the", "movie", "which", "the", "song", "\"", "I", "Thought", "I", "Lost", "You", "\"", "is", "associated", "with", "." ]
[ { "id": 3, "type": "value", "value": "I Thought I Lost You" }, { "id": 1, "type": "column", "value": "movie_title" }, { "id": 0, "type": "table", "value": "characters" }, { "id": 2, "type": "column", "value": "song" } ]
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[ "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "O", "O", "O", "O" ]
15,416
financial
bird:dev.json:122
State the district and region for loan ID '4990'.
SELECT T2.A2, T2.A3 FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN loan AS T3 ON T1.account_id = T3.account_id WHERE T3.loan_id = 4990
[ "State", "the", "district", "and", "region", "for", "loan", "ID", "'", "4990", "'", "." ]
[ { "id": 8, "type": "column", "value": "district_id" }, { "id": 7, "type": "column", "value": "account_id" }, { "id": 6, "type": "table", "value": "district" }, { "id": 3, "type": "column", "value": "loan_id" }, { "id": 5, "type": "table", "value": "account" }, { "id": 2, "type": "table", "value": "loan" }, { "id": 4, "type": "value", "value": "4990" }, { "id": 0, "type": "column", "value": "a2" }, { "id": 1, "type": "column", "value": "a3" } ]
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[ "O", "O", "B-TABLE", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
15,417
activity_1
spider:train_spider.json:6753
Show first name and last name for all the students advised by Michael Goodrich.
SELECT T2.fname , T2.lname FROM Faculty AS T1 JOIN Student AS T2 ON T1.FacID = T2.advisor WHERE T1.fname = "Michael" AND T1.lname = "Goodrich"
[ "Show", "first", "name", "and", "last", "name", "for", "all", "the", "students", "advised", "by", "Michael", "Goodrich", "." ]
[ { "id": 7, "type": "column", "value": "Goodrich" }, { "id": 2, "type": "table", "value": "faculty" }, { "id": 3, "type": "table", "value": "student" }, { "id": 5, "type": "column", "value": "advisor" }, { "id": 6, "type": "column", "value": "Michael" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 4, "type": "column", "value": "facid" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "B-COLUMN", "O" ]
15,418
superhero
bird:dev.json:781
Provide the heights of the heroes whose eye colours are amber.
SELECT T1.height_cm FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.eye_colour_id = T2.id WHERE T2.colour = 'Amber'
[ "Provide", "the", "heights", "of", "the", "heroes", "whose", "eye", "colours", "are", "amber", "." ]
[ { "id": 5, "type": "column", "value": "eye_colour_id" }, { "id": 0, "type": "column", "value": "height_cm" }, { "id": 1, "type": "table", "value": "superhero" }, { "id": 2, "type": "table", "value": "colour" }, { "id": 3, "type": "column", "value": "colour" }, { "id": 4, "type": "value", "value": "Amber" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O", "B-VALUE", "O" ]
15,419
ice_hockey_draft
bird:train.json:6941
What is the average weight in pounds of all the players with the highest prospects for the draft?
SELECT CAST(SUM(T2.weight_in_lbs) AS REAL) / COUNT(T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN weight_info AS T2 ON T1.weight = T2.weight_id WHERE T1.CSS_rank = ( SELECT MAX(CSS_rank) FROM PlayerInfo )
[ "What", "is", "the", "average", "weight", "in", "pounds", "of", "all", "the", "players", "with", "the", "highest", "prospects", "for", "the", "draft", "?" ]
[ { "id": 6, "type": "column", "value": "weight_in_lbs" }, { "id": 1, "type": "table", "value": "weight_info" }, { "id": 0, "type": "table", "value": "playerinfo" }, { "id": 4, "type": "column", "value": "weight_id" }, { "id": 2, "type": "column", "value": "css_rank" }, { "id": 5, "type": "column", "value": "eliteid" }, { "id": 3, "type": "column", "value": "weight" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,420
university
bird:train.json:8017
What is the ranking criteria ID of Brown University in 2014?
SELECT T1.ranking_criteria_id FROM university_ranking_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.university_name = 'Brown University' AND T1.year = 2014
[ "What", "is", "the", "ranking", "criteria", "ID", "of", "Brown", "University", "in", "2014", "?" ]
[ { "id": 1, "type": "table", "value": "university_ranking_year" }, { "id": 0, "type": "column", "value": "ranking_criteria_id" }, { "id": 6, "type": "value", "value": "Brown University" }, { "id": 5, "type": "column", "value": "university_name" }, { "id": 3, "type": "column", "value": "university_id" }, { "id": 2, "type": "table", "value": "university" }, { "id": 7, "type": "column", "value": "year" }, { "id": 8, "type": "value", "value": "2014" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "B-TABLE", "B-VALUE", "O" ]