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110
|
boat_1
|
bird:test.json:870
|
What are the ids of sailors who have not reserved a boat?
|
SELECT sid FROM Sailors EXCEPT SELECT sid FROM Reserves
|
[
"What",
"are",
"the",
"ids",
"of",
"sailors",
"who",
"have",
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"reserved",
"a",
"boat",
"?"
] |
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{
"id": 1,
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{
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"type": "table",
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{
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"value": "sid"
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"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
111
|
advertising_agencies
|
bird:test.json:2067
|
What is the agency id and details with most number of clients?
|
SELECT T1.agency_id , T1.agency_details FROM Agencies AS T1 JOIN Clients AS T2 ON T1.agency_id = T2.agency_id GROUP BY T1.agency_id ORDER BY count(*) DESC LIMIT 1
|
[
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"agency",
"i",
"d",
"and",
"details",
"with",
"most",
"number",
"of",
"clients",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "agency_details"
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{
"id": 0,
"type": "column",
"value": "agency_id"
},
{
"id": 2,
"type": "table",
"value": "agencies"
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{
"id": 3,
"type": "table",
"value": "clients"
}
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"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
112
|
donor
|
bird:train.json:3223
|
Is the donor who donated to school "d4af834b1d3fc8061e1ee1b3f1a77b85" a teacher?
|
SELECT T2.is_teacher_acct FROM projects AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T1.schoolid = 'd4af834b1d3fc8061e1ee1b3f1a77b85'
|
[
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"to",
"school",
"\"",
"d4af834b1d3fc8061e1ee1b3f1a77b85",
"\"",
"a",
"teacher",
"?"
] |
[
{
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"type": "value",
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},
{
"id": 0,
"type": "column",
"value": "is_teacher_acct"
},
{
"id": 2,
"type": "table",
"value": "donations"
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{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 1,
"type": "table",
"value": "projects"
},
{
"id": 3,
"type": "column",
"value": "schoolid"
}
] |
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[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
113
|
performance_attendance
|
spider:train_spider.json:1321
|
List the names of members who did not attend any performance.
|
SELECT Name FROM member WHERE Member_ID NOT IN (SELECT Member_ID FROM member_attendance)
|
[
"List",
"the",
"names",
"of",
"members",
"who",
"did",
"not",
"attend",
"any",
"performance",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "member_attendance"
},
{
"id": 2,
"type": "column",
"value": "member_id"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
114
|
book_review
|
bird:test.json:594
|
List the titles of books in ascending alphabetical order.
|
SELECT Title FROM book ORDER BY Title ASC
|
[
"List",
"the",
"titles",
"of",
"books",
"in",
"ascending",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "book"
}
] |
[
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] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
115
|
baseball_1
|
spider:train_spider.json:3678
|
What is the total salary expenses of team Boston Red Stockings in 2010?
|
SELECT sum(T1.salary) FROM salary AS T1 JOIN team AS T2 ON T1.team_id = T2.team_id_br WHERE T2.name = 'Boston Red Stockings' AND T1.year = 2010
|
[
"What",
"is",
"the",
"total",
"salary",
"expenses",
"of",
"team",
"Boston",
"Red",
"Stockings",
"in",
"2010",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Boston Red Stockings"
},
{
"id": 4,
"type": "column",
"value": "team_id_br"
},
{
"id": 3,
"type": "column",
"value": "team_id"
},
{
"id": 0,
"type": "table",
"value": "salary"
},
{
"id": 2,
"type": "column",
"value": "salary"
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{
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"value": "team"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2010"
}
] |
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[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
116
|
movies_4
|
bird:train.json:449
|
List the names of the production companies that made at least 200 movies.
|
SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id GROUP BY T1.company_id HAVING COUNT(T2.movie_id) > 200
|
[
"List",
"the",
"names",
"of",
"the",
"production",
"companies",
"that",
"made",
"at",
"least",
"200",
"movies",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "production_company"
},
{
"id": 3,
"type": "table",
"value": "movie_company"
},
{
"id": 1,
"type": "column",
"value": "company_name"
},
{
"id": 0,
"type": "column",
"value": "company_id"
},
{
"id": 5,
"type": "column",
"value": "movie_id"
},
{
"id": 4,
"type": "value",
"value": "200"
}
] |
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[
"O",
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"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
118
|
aircraft
|
spider:train_spider.json:4823
|
List the name of the aircraft that has been named winning aircraft the most number of times.
|
SELECT T1.Aircraft FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY COUNT(*) DESC LIMIT 1
|
[
"List",
"the",
"name",
"of",
"the",
"aircraft",
"that",
"has",
"been",
"named",
"winning",
"aircraft",
"the",
"most",
"number",
"of",
"times",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "winning_aircraft"
},
{
"id": 4,
"type": "column",
"value": "aircraft_id"
},
{
"id": 1,
"type": "column",
"value": "aircraft"
},
{
"id": 2,
"type": "table",
"value": "aircraft"
},
{
"id": 3,
"type": "table",
"value": "match"
}
] |
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{
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
119
|
store_1
|
spider:train_spider.json:582
|
In which country does Roberto Almeida?
|
SELECT country FROM customers WHERE first_name = "Roberto" AND last_name = "Almeida";
|
[
"In",
"which",
"country",
"does",
"Roberto",
"Almeida",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "Roberto"
},
{
"id": 5,
"type": "column",
"value": "Almeida"
}
] |
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{
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{
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},
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},
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},
{
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},
{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
120
|
theme_gallery
|
spider:train_spider.json:1672
|
What are the names of artists that have not had any exhibitions?
|
SELECT name FROM artist WHERE artist_id NOT IN (SELECT artist_id FROM exhibition)
|
[
"What",
"are",
"the",
"names",
"of",
"artists",
"that",
"have",
"not",
"had",
"any",
"exhibitions",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "exhibition"
},
{
"id": 2,
"type": "column",
"value": "artist_id"
},
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
121
|
works_cycles
|
bird:train.json:7304
|
Among the salable products from the mountain product line, how many of them have the most reviews?
|
SELECT SUM(CASE WHEN T2.ProductLine = 'M' THEN 1 ELSE 0 END) FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.FinishedGoodsFlag = 1 GROUP BY T1.ProductID ORDER BY COUNT(T1.ProductReviewID) DESC LIMIT 1
|
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"the",
"mountain",
"product",
"line",
",",
"how",
"many",
"of",
"them",
"have",
"the",
"most",
"reviews",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "finishedgoodsflag"
},
{
"id": 5,
"type": "column",
"value": "productreviewid"
},
{
"id": 1,
"type": "table",
"value": "productreview"
},
{
"id": 7,
"type": "column",
"value": "productline"
},
{
"id": 0,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "M"
}
] |
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"entity_id": 0,
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
122
|
thrombosis_prediction
|
bird:dev.json:1235
|
What are the patient's diagnosis for those who has lower red blood blood cell? State their ID and age.
|
SELECT DISTINCT T1.Diagnosis, T1.ID , STRFTIME('%Y', CURRENT_TIMESTAMP) -STRFTIME('%Y', T1.Birthday) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.RBC < 3.5
|
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"the",
"patient",
"'s",
"diagnosis",
"for",
"those",
"who",
"has",
"lower",
"red",
"blood",
"blood",
"cell",
"?",
"State",
"their",
"ID",
"and",
"age",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 7,
"type": "column",
"value": "birthday"
},
{
"id": 2,
"type": "table",
"value": "patient"
},
{
"id": 4,
"type": "column",
"value": "rbc"
},
{
"id": 5,
"type": "value",
"value": "3.5"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
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}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
123
|
books
|
bird:train.json:5952
|
What is the name of the first book written by J.K Rowling?
|
SELECT T1.title FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'J.K. Rowling' ORDER BY T1.publication_date ASC LIMIT 1
|
[
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"is",
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"name",
"of",
"the",
"first",
"book",
"written",
"by",
"J.K",
"Rowling",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "publication_date"
},
{
"id": 3,
"type": "value",
"value": "J.K. Rowling"
},
{
"id": 2,
"type": "column",
"value": "author_name"
},
{
"id": 6,
"type": "table",
"value": "book_author"
},
{
"id": 7,
"type": "column",
"value": "author_id"
},
{
"id": 8,
"type": "column",
"value": "book_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "table",
"value": "book"
}
] |
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3
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[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
124
|
movies_4
|
bird:train.json:535
|
What percentage of films are made in the US?
|
SELECT CAST(COUNT(CASE WHEN T3.COUNTry_iso_code = 'US' THEN T1.movie_id ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN production_COUNTry AS T2 ON T1.movie_id = T2.movie_id INNER JOIN COUNTry AS T3 ON T2.COUNTry_id = T3.COUNTry_id
|
[
"What",
"percentage",
"of",
"films",
"are",
"made",
"in",
"the",
"US",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "production_country"
},
{
"id": 6,
"type": "column",
"value": "country_iso_code"
},
{
"id": 3,
"type": "column",
"value": "country_id"
},
{
"id": 5,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "movie"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "US"
}
] |
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},
{
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},
{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
125
|
aan_1
|
bird:test.json:1023
|
What are the names of the top 3 affiliations that have the most papers in year 2009?
|
SELECT T3.name FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Affiliation AS T3 ON T2.affiliation_id = T3.affiliation_id WHERE T1.year = 2009 GROUP BY T2.affiliation_id ORDER BY count(*) DESC LIMIT 3
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"top",
"3",
"affiliations",
"that",
"have",
"the",
"most",
"papers",
"in",
"year",
"2009",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "affiliation_id"
},
{
"id": 2,
"type": "table",
"value": "affiliation"
},
{
"id": 6,
"type": "table",
"value": "author_list"
},
{
"id": 7,
"type": "column",
"value": "paper_id"
},
{
"id": 5,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2009"
}
] |
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{
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{
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[
"O",
"O",
"O",
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"O",
"O",
"B-TABLE",
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"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
126
|
financial
|
bird:dev.json:157
|
What is the number of committed crimes in 1995 in the district of the account with the id 532?
|
SELECT T1.A15 FROM district AS T1 INNER JOIN `account` AS T2 ON T1.district_id = T2.district_id WHERE T2.account_id = 532
|
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"in",
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"the",
"district",
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"with",
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"d",
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"?"
] |
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{
"id": 5,
"type": "column",
"value": "district_id"
},
{
"id": 3,
"type": "column",
"value": "account_id"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 2,
"type": "table",
"value": "account"
},
{
"id": 0,
"type": "column",
"value": "a15"
},
{
"id": 4,
"type": "value",
"value": "532"
}
] |
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{
"entity_id": 18,
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},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
127
|
soccer_2016
|
bird:train.json:1836
|
How many players with left-hand batting style are from India?
|
SELECT SUM(CASE WHEN T1.Batting_hand = 'Left-hand bat' THEN 1 ELSE 0 END) AS cnt FROM Batting_Style AS T1 INNER JOIN Player AS T2 ON T1.Batting_Id = T2.Batting_hand INNER JOIN Country AS T3 ON T2.Country_Name = T3.Country_Id WHERE T3.Country_Name = 'India'
|
[
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"players",
"with",
"left",
"-",
"hand",
"batting",
"style",
"are",
"from",
"India",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "batting_style"
},
{
"id": 10,
"type": "value",
"value": "Left-hand bat"
},
{
"id": 1,
"type": "column",
"value": "country_name"
},
{
"id": 8,
"type": "column",
"value": "batting_hand"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 7,
"type": "column",
"value": "batting_id"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "table",
"value": "player"
},
{
"id": 2,
"type": "value",
"value": "India"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
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"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"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": [
4,
5,
6
]
},
{
"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-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
129
|
car_road_race
|
bird:test.json:1343
|
How many drivers use each constructor?
|
SELECT CONSTRUCTOR , COUNT(*) FROM driver GROUP BY CONSTRUCTOR
|
[
"How",
"many",
"drivers",
"use",
"each",
"constructor",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "constructor"
},
{
"id": 0,
"type": "table",
"value": "driver"
}
] |
[
{
"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": []
},
{
"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"
] |
130
|
mondial_geo
|
bird:train.json:8242
|
Which country has the biggest percentage of the albanian ethnic group?
|
SELECT T1.Name FROM country AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Code = T2.Country WHERE T2.Name = 'Albanian' ORDER BY T2.Percentage DESC LIMIT 1
|
[
"Which",
"country",
"has",
"the",
"biggest",
"percentage",
"of",
"the",
"albanian",
"ethnic",
"group",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 4,
"type": "column",
"value": "percentage"
},
{
"id": 3,
"type": "value",
"value": "Albanian"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O"
] |
131
|
products_gen_characteristics
|
spider:train_spider.json:5581
|
What is the description of the product category with the code 'Spices'?
|
SELECT product_category_description FROM ref_product_categories WHERE product_category_code = "Spices"
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"product",
"category",
"with",
"the",
"code",
"'",
"Spices",
"'",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "product_category_description"
},
{
"id": 0,
"type": "table",
"value": "ref_product_categories"
},
{
"id": 2,
"type": "column",
"value": "product_category_code"
},
{
"id": 3,
"type": "column",
"value": "Spices"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
132
|
movie_2
|
bird:test.json:1831
|
Find the titles of all movies sorted by their ratings.
|
SELECT title FROM movies ORDER BY rating
|
[
"Find",
"the",
"titles",
"of",
"all",
"movies",
"sorted",
"by",
"their",
"ratings",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
133
|
soccer_2016
|
bird:train.json:1890
|
Give the player id of the player who was at the non-striker end for the most number of balls in the match 501219.
|
SELECT Ball_Id FROM Ball_by_Ball WHERE Non_Striker = Ball_Id ORDER BY Ball_Id DESC LIMIT 1
|
[
"Give",
"the",
"player",
"i",
"d",
"of",
"the",
"player",
"who",
"was",
"at",
"the",
"non",
"-",
"striker",
"end",
"for",
"the",
"most",
"number",
"of",
"balls",
"in",
"the",
"match",
"501219",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "ball_by_ball"
},
{
"id": 2,
"type": "column",
"value": "non_striker"
},
{
"id": 1,
"type": "column",
"value": "ball_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
21,
22
]
},
{
"entity_id": 2,
"token_idxs": [
12,
13,
14
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
134
|
warehouse_1
|
bird:test.json:1736
|
For each content, what is the total value and number of boxes?
|
SELECT sum(value) , count(*) , CONTENTS FROM boxes GROUP BY CONTENTS
|
[
"For",
"each",
"content",
",",
"what",
"is",
"the",
"total",
"value",
"and",
"number",
"of",
"boxes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "contents"
},
{
"id": 0,
"type": "table",
"value": "boxes"
},
{
"id": 2,
"type": "column",
"value": "value"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
135
|
allergy_1
|
spider:train_spider.json:504
|
How many students are affected by cat allergies?
|
SELECT count(*) FROM Has_allergy WHERE Allergy = "Cat"
|
[
"How",
"many",
"students",
"are",
"affected",
"by",
"cat",
"allergies",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "has_allergy"
},
{
"id": 1,
"type": "column",
"value": "allergy"
},
{
"id": 2,
"type": "column",
"value": "Cat"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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-COLUMN",
"B-COLUMN",
"O"
] |
136
|
restaurant
|
bird:train.json:1688
|
Identify all restaurants in Contra Costa County by id.
|
SELECT T1.id_restaurant FROM location AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T2.county = 'contra costa county'
|
[
"Identify",
"all",
"restaurants",
"in",
"Contra",
"Costa",
"County",
"by",
"i",
"d."
] |
[
{
"id": 4,
"type": "value",
"value": "contra costa county"
},
{
"id": 0,
"type": "column",
"value": "id_restaurant"
},
{
"id": 2,
"type": "table",
"value": "geographic"
},
{
"id": 1,
"type": "table",
"value": "location"
},
{
"id": 3,
"type": "column",
"value": "county"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"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": [
4,
5
]
},
{
"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": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
137
|
election
|
spider:train_spider.json:2777
|
For each party, return the name of the party and the number of delegates from that party.
|
SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party
|
[
"For",
"each",
"party",
",",
"return",
"the",
"name",
"of",
"the",
"party",
"and",
"the",
"number",
"of",
"delegates",
"from",
"that",
"party",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "election"
},
{
"id": 3,
"type": "column",
"value": "party_id"
},
{
"id": 0,
"type": "column",
"value": "party"
},
{
"id": 2,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
138
|
wedding
|
spider:train_spider.json:1634
|
Show all opening years and the number of churches that opened in that year.
|
SELECT open_date , count(*) FROM church GROUP BY open_date
|
[
"Show",
"all",
"opening",
"years",
"and",
"the",
"number",
"of",
"churches",
"that",
"opened",
"in",
"that",
"year",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "open_date"
},
{
"id": 0,
"type": "table",
"value": "church"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"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-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
139
|
flight_company
|
spider:train_spider.json:6382
|
how many airports are there in each country?
|
SELECT count(*) , country FROM airport GROUP BY country
|
[
"how",
"many",
"airports",
"are",
"there",
"in",
"each",
"country",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "airport"
},
{
"id": 1,
"type": "column",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": []
},
{
"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",
"B-COLUMN",
"O"
] |
140
|
game_1
|
spider:train_spider.json:5999
|
How many sports do we have?
|
SELECT count(DISTINCT sportname) FROM Sportsinfo
|
[
"How",
"many",
"sports",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sportsinfo"
},
{
"id": 1,
"type": "column",
"value": "sportname"
}
] |
[
{
"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"
] |
141
|
beer_factory
|
bird:train.json:5297
|
Among the customers not subscribed to the mailing list, what percentage has given three or more stars in a review?
|
SELECT CAST(COUNT(CASE WHEN T2.StarRating > 3 THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.CustomerID) FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.SubscribedToEmailList = 'FALSE'
|
[
"Among",
"the",
"customers",
"not",
"subscribed",
"to",
"the",
"mailing",
"list",
",",
"what",
"percentage",
"has",
"given",
"three",
"or",
"more",
"stars",
"in",
"a",
"review",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "subscribedtoemaillist"
},
{
"id": 1,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 4,
"type": "column",
"value": "customerid"
},
{
"id": 7,
"type": "column",
"value": "starrating"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "FALSE"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6,
7,
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": [
17,
18
]
},
{
"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",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O"
] |
142
|
hockey
|
bird:train.json:7782
|
What is the average winning rate of the Montreal Canadiens in the Stanley Cup finals?
|
SELECT SUM(T2.W / T2.G) / SUM(T2.G + T2.W) FROM Teams AS T1 INNER JOIN TeamsSC AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.name = 'Montreal Canadiens'
|
[
"What",
"is",
"the",
"average",
"winning",
"rate",
"of",
"the",
"Montreal",
"Canadiens",
"in",
"the",
"Stanley",
"Cup",
"finals",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Montreal Canadiens"
},
{
"id": 1,
"type": "table",
"value": "teamssc"
},
{
"id": 0,
"type": "table",
"value": "teams"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "tmid"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "column",
"value": "w"
},
{
"id": 7,
"type": "column",
"value": "g"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
143
|
icfp_1
|
spider:train_spider.json:2864
|
What are the titles of papers published by "Jeremy Gibbons"?
|
SELECT t3.title FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t1.fname = "Jeremy" AND t1.lname = "Gibbons"
|
[
"What",
"are",
"the",
"titles",
"of",
"papers",
"published",
"by",
"\"",
"Jeremy",
"Gibbons",
"\"",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "authorship"
},
{
"id": 2,
"type": "table",
"value": "authors"
},
{
"id": 4,
"type": "column",
"value": "paperid"
},
{
"id": 8,
"type": "column",
"value": "Gibbons"
},
{
"id": 1,
"type": "table",
"value": "papers"
},
{
"id": 6,
"type": "column",
"value": "Jeremy"
},
{
"id": 9,
"type": "column",
"value": "authid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "column",
"value": "fname"
},
{
"id": 7,
"type": "column",
"value": "lname"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
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},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O"
] |
144
|
movies_4
|
bird:train.json:454
|
How many horror movies are there?
|
SELECT COUNT(T1.movie_id) FROM movie_genres AS T1 INNER JOIN genre AS T2 ON T1.genre_id = T2.genre_id WHERE T2.genre_name = 'Horror'
|
[
"How",
"many",
"horror",
"movies",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "movie_genres"
},
{
"id": 2,
"type": "column",
"value": "genre_name"
},
{
"id": 4,
"type": "column",
"value": "movie_id"
},
{
"id": 5,
"type": "column",
"value": "genre_id"
},
{
"id": 3,
"type": "value",
"value": "Horror"
},
{
"id": 1,
"type": "table",
"value": "genre"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
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{
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},
{
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"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",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
145
|
architecture
|
spider:train_spider.json:6960
|
How many architects haven't built a mill before year 1850?
|
SELECT count(*) FROM architect WHERE id NOT IN ( SELECT architect_id FROM mill WHERE built_year < 1850 );
|
[
"How",
"many",
"architects",
"have",
"n't",
"built",
"a",
"mill",
"before",
"year",
"1850",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "architect_id"
},
{
"id": 4,
"type": "column",
"value": "built_year"
},
{
"id": 0,
"type": "table",
"value": "architect"
},
{
"id": 2,
"type": "table",
"value": "mill"
},
{
"id": 5,
"type": "value",
"value": "1850"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"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",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
146
|
government_shift
|
bird:test.json:355
|
List details of all the channel in alphabetical order .
|
select channel_details from channels order by channel_details
|
[
"List",
"details",
"of",
"all",
"the",
"channel",
"in",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "channel_details"
},
{
"id": 0,
"type": "table",
"value": "channels"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
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},
{
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},
{
"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",
"B-COLUMN",
"O",
"O",
"O"
] |
147
|
program_share
|
spider:train_spider.json:3766
|
Find the name of the program that is broadcast most frequently.
|
SELECT t1.name FROM program AS t1 JOIN broadcast AS t2 ON t1.program_id = t2.program_id GROUP BY t2.program_id ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"program",
"that",
"is",
"broadcast",
"most",
"frequently",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "program_id"
},
{
"id": 3,
"type": "table",
"value": "broadcast"
},
{
"id": 2,
"type": "table",
"value": "program"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
148
|
public_review_platform
|
bird:train.json:3852
|
Among the Yelp_Businesses in Arizona, how many of them do not provide alcohol?
|
SELECT COUNT(T2.business_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T1.attribute_name LIKE 'Alcohol' AND T2.attribute_value LIKE 'none' AND T3.state LIKE 'AZ'
|
[
"Among",
"the",
"Yelp_Businesses",
"in",
"Arizona",
",",
"how",
"many",
"of",
"them",
"do",
"not",
"provide",
"alcohol",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "business_attributes"
},
{
"id": 6,
"type": "column",
"value": "attribute_value"
},
{
"id": 4,
"type": "column",
"value": "attribute_name"
},
{
"id": 10,
"type": "column",
"value": "attribute_id"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "attributes"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "value",
"value": "Alcohol"
},
{
"id": 8,
"type": "column",
"value": "state"
},
{
"id": 7,
"type": "value",
"value": "none"
},
{
"id": 9,
"type": "value",
"value": "AZ"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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": []
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
149
|
book_publishing_company
|
bird:train.json:182
|
Which employee has the lowest job level. State the first name, last name and when he /she was hired.
|
SELECT fname, lname, hire_date FROM employee ORDER BY job_lvl LIMIT 1
|
[
"Which",
"employee",
"has",
"the",
"lowest",
"job",
"level",
".",
"State",
"the",
"first",
"name",
",",
"last",
"name",
"and",
"when",
"he",
"/she",
"was",
"hired",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "hire_date"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "column",
"value": "job_lvl"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 2,
"type": "column",
"value": "lname"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
20
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"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-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
150
|
student_loan
|
bird:train.json:4564
|
List the names of the disabled students who were absent from school for more than 5 months.
|
SELECT T1.name FROM longest_absense_from_school AS T1 INNER JOIN disabled AS T2 ON T1.name = T2.name WHERE T1.month > 5
|
[
"List",
"the",
"names",
"of",
"the",
"disabled",
"students",
"who",
"were",
"absent",
"from",
"school",
"for",
"more",
"than",
"5",
"months",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 2,
"type": "table",
"value": "disabled"
},
{
"id": 3,
"type": "column",
"value": "month"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
151
|
student_loan
|
bird:train.json:4519
|
State the number of male students who do not have payment due.
|
SELECT COUNT(T1.name) FROM no_payment_due AS T1 INNER JOIN male AS T2 ON T2.name = T1.name WHERE T1.bool = 'pos'
|
[
"State",
"the",
"number",
"of",
"male",
"students",
"who",
"do",
"not",
"have",
"payment",
"due",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "no_payment_due"
},
{
"id": 1,
"type": "table",
"value": "male"
},
{
"id": 2,
"type": "column",
"value": "bool"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "pos"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10,
11
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
153
|
thrombosis_prediction
|
bird:dev.json:1251
|
How many patients with an Ig G higher than normal?
|
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T3.ID = T2.ID WHERE T2.IGG >= 2000
|
[
"How",
"many",
"patients",
"with",
"an",
"Ig",
"G",
"higher",
"than",
"normal",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 5,
"type": "table",
"value": "laboratory"
},
{
"id": 4,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "value",
"value": "2000"
},
{
"id": 1,
"type": "column",
"value": "igg"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
154
|
bakery_1
|
bird:test.json:1588
|
What are the ids of customers who spend more than 5 on average for each good?
|
SELECT T3.CustomerId FROM goods AS T1 JOIN items AS T2 ON T1.id = T2.item JOIN receipts AS T3 ON T2.receipt = T3.ReceiptNumber GROUP BY T3.CustomerId HAVING avg(T1.price) > 5
|
[
"What",
"are",
"the",
"ids",
"of",
"customers",
"who",
"spend",
"more",
"than",
"5",
"on",
"average",
"for",
"each",
"good",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "receiptnumber"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "receipts"
},
{
"id": 5,
"type": "column",
"value": "receipt"
},
{
"id": 3,
"type": "table",
"value": "goods"
},
{
"id": 4,
"type": "table",
"value": "items"
},
{
"id": 7,
"type": "column",
"value": "price"
},
{
"id": 9,
"type": "column",
"value": "item"
},
{
"id": 8,
"type": "column",
"value": "id"
},
{
"id": 2,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"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": [
3
]
},
{
"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",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
155
|
movie_platform
|
bird:train.json:99
|
Please list the names of the movies that user 94978 scored as 5.
|
SELECT T2.movie_title FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T1.rating_score = 5 AND T1.user_id = 94978
|
[
"Please",
"list",
"the",
"names",
"of",
"the",
"movies",
"that",
"user",
"94978",
"scored",
"as",
"5",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "rating_score"
},
{
"id": 0,
"type": "column",
"value": "movie_title"
},
{
"id": 3,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 6,
"type": "column",
"value": "user_id"
},
{
"id": 2,
"type": "table",
"value": "movies"
},
{
"id": 7,
"type": "value",
"value": "94978"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
156
|
works_cycles
|
bird:train.json:7324
|
Among the employees in Adventure Works, calculate the percentage of them working as sales representatives.
|
SELECT CAST(SUM(CASE WHEN JobTitle = 'Sales Representative' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(BusinessEntityID) FROM Employee
|
[
"Among",
"the",
"employees",
"in",
"Adventure",
"Works",
",",
"calculate",
"the",
"percentage",
"of",
"them",
"working",
"as",
"sales",
"representatives",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Sales Representative"
},
{
"id": 2,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 5,
"type": "column",
"value": "jobtitle"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"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": [
14,
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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
157
|
world
|
bird:train.json:7895
|
How many countries have no GNP?
|
SELECT COUNT(*) FROM Country WHERE GNP = 0
|
[
"How",
"many",
"countries",
"have",
"no",
"GNP",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "gnp"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"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": []
},
{
"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"
] |
159
|
airline
|
bird:train.json:5849
|
Tell the number of flights that landed at Lake Charles Regional Airport on 2018/8/15.
|
SELECT COUNT(T1.Code) FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.DEST WHERE T2.FL_DATE = '2018/8/15' AND T1.Description = 'Lake Charles, LA: Lake Charles Regional'
|
[
"Tell",
"the",
"number",
"of",
"flights",
"that",
"landed",
"at",
"Lake",
"Charles",
"Regional",
"Airport",
"on",
"2018/8/15",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "Lake Charles, LA: Lake Charles Regional"
},
{
"id": 6,
"type": "column",
"value": "description"
},
{
"id": 5,
"type": "value",
"value": "2018/8/15"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 1,
"type": "table",
"value": "airlines"
},
{
"id": 4,
"type": "column",
"value": "fl_date"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 3,
"type": "column",
"value": "dest"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6,
7,
8,
10
]
},
{
"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-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"B-VALUE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
160
|
world
|
bird:train.json:7840
|
Among the countries that officially use the English language, what country has the highest capital?
|
SELECT T1.Code FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T2.Language = 'English' AND T2.IsOfficial = 'T' ORDER BY T1.Capital DESC LIMIT 1
|
[
"Among",
"the",
"countries",
"that",
"officially",
"use",
"the",
"English",
"language",
",",
"what",
"country",
"has",
"the",
"highest",
"capital",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "countrylanguage"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 7,
"type": "column",
"value": "isofficial"
},
{
"id": 5,
"type": "column",
"value": "language"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "capital"
},
{
"id": 6,
"type": "value",
"value": "English"
},
{
"id": 0,
"type": "column",
"value": "code"
},
{
"id": 8,
"type": "value",
"value": "T"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"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-VALUE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
161
|
music_platform_2
|
bird:train.json:7985
|
How many ratings of 5 have been given to the podcast "Please Excuse My Dead Aunt Sally"?
|
SELECT COUNT(T2.rating) FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id WHERE T1.title = 'Please Excuse My Dead Aunt Sally' AND T2.rating = 5
|
[
"How",
"many",
"ratings",
"of",
"5",
"have",
"been",
"given",
"to",
"the",
"podcast",
"\"",
"Please",
"Excuse",
"My",
"Dead",
"Aunt",
"Sally",
"\"",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Please Excuse My Dead Aunt Sally"
},
{
"id": 3,
"type": "column",
"value": "podcast_id"
},
{
"id": 0,
"type": "table",
"value": "podcasts"
},
{
"id": 1,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12,
13,
14,
15,
16,
17
]
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"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",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
162
|
restaurant
|
bird:train.json:1707
|
How many American food restaurants are unpopular in Carmel?
|
SELECT COUNT(id_restaurant) FROM generalinfo WHERE food_type = 'american' AND city = 'carmel' AND review = ( SELECT MIN(review) FROM generalinfo WHERE food_type = 'american' AND city = 'carmel' )
|
[
"How",
"many",
"American",
"food",
"restaurants",
"are",
"unpopular",
"in",
"Carmel",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "id_restaurant"
},
{
"id": 0,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "column",
"value": "food_type"
},
{
"id": 3,
"type": "value",
"value": "american"
},
{
"id": 5,
"type": "value",
"value": "carmel"
},
{
"id": 6,
"type": "column",
"value": "review"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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-VALUE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
163
|
retail_complains
|
bird:train.json:254
|
Which division is Diesel Galloway in?
|
SELECT T2.division FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.first = 'Diesel' AND T1.last = 'Galloway'
|
[
"Which",
"division",
"is",
"Diesel",
"Galloway",
"in",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "district_id"
},
{
"id": 0,
"type": "column",
"value": "division"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 7,
"type": "value",
"value": "Galloway"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 5,
"type": "value",
"value": "Diesel"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 6,
"type": "column",
"value": "last"
}
] |
[
{
"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": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"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",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
164
|
wedding
|
spider:train_spider.json:1648
|
How many churches have a wedding in year 2016?
|
SELECT COUNT (DISTINCT church_id) FROM wedding WHERE YEAR = 2016
|
[
"How",
"many",
"churches",
"have",
"a",
"wedding",
"in",
"year",
"2016",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "church_id"
},
{
"id": 0,
"type": "table",
"value": "wedding"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2016"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
165
|
card_games
|
bird:dev.json:495
|
What was the release date for the set which card "Evacuation" in it?
|
SELECT T2.releaseDate FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T1.name = 'Evacuation'
|
[
"What",
"was",
"the",
"release",
"date",
"for",
"the",
"set",
"which",
"card",
"\"",
"Evacuation",
"\"",
"in",
"it",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "releasedate"
},
{
"id": 4,
"type": "value",
"value": "Evacuation"
},
{
"id": 6,
"type": "column",
"value": "setcode"
},
{
"id": 1,
"type": "table",
"value": "cards"
},
{
"id": 2,
"type": "table",
"value": "sets"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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9
]
},
{
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7
]
},
{
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},
{
"entity_id": 4,
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11
]
},
{
"entity_id": 5,
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
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},
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},
{
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},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
166
|
law_episode
|
bird:train.json:1302
|
What is the name of the actors born in the USA?
|
SELECT name FROM Person WHERE birth_country = 'USA'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"actors",
"born",
"in",
"the",
"USA",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "birth_country"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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10
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
"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",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
167
|
csu_1
|
spider:train_spider.json:2355
|
What is the average fee for a CSU campus in the year of 2005?
|
SELECT avg(campusfee) FROM csu_fees WHERE YEAR = 2005
|
[
"What",
"is",
"the",
"average",
"fee",
"for",
"a",
"CSU",
"campus",
"in",
"the",
"year",
"of",
"2005",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "campusfee"
},
{
"id": 0,
"type": "table",
"value": "csu_fees"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2005"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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11
]
},
{
"entity_id": 2,
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13
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"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",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
168
|
codebase_community
|
bird:dev.json:691
|
Identify the number of adult users who have cast over 5000 upvotes.
|
SELECT COUNT(Id) FROM users WHERE Age BETWEEN 19 AND 65 AND UpVotes > 5000
|
[
"Identify",
"the",
"number",
"of",
"adult",
"users",
"who",
"have",
"cast",
"over",
"5000",
"upvotes",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "upvotes"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 6,
"type": "value",
"value": "5000"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 3,
"type": "value",
"value": "19"
},
{
"id": 4,
"type": "value",
"value": "65"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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11
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
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"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",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
169
|
student_loan
|
bird:train.json:4387
|
Which school is student829 enrolled in?
|
SELECT school FROM enrolled WHERE name = 'student829'
|
[
"Which",
"school",
"is",
"student829",
"enrolled",
"in",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "student829"
},
{
"id": 0,
"type": "table",
"value": "enrolled"
},
{
"id": 1,
"type": "column",
"value": "school"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"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",
"B-VALUE",
"B-TABLE",
"O",
"O"
] |
170
|
formula_1
|
bird:dev.json:924
|
Please list the exact dates on which a Formula_1 race took place on the Barcelona-Catalunya circuit.
|
SELECT T2.date FROM circuits AS T1 INNER JOIN races AS T2 ON T2.circuitID = T1.circuitId WHERE T1.name = 'Circuit de Barcelona-Catalunya'
|
[
"Please",
"list",
"the",
"exact",
"dates",
"on",
"which",
"a",
"Formula_1",
"race",
"took",
"place",
"on",
"the",
"Barcelona",
"-",
"Catalunya",
"circuit",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Circuit de Barcelona-Catalunya"
},
{
"id": 5,
"type": "column",
"value": "circuitid"
},
{
"id": 1,
"type": "table",
"value": "circuits"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 0,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
14,
15,
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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
171
|
public_review_platform
|
bird:train.json:3930
|
Find the location of businesses that has business hours from 9 am to 9 pm every Saturday.
|
SELECT T1.city FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T2.closing_time LIKE '9PM' AND T2.opening_time LIKE '9AM' AND T3.day_of_week LIKE 'Saturday' GROUP BY T1.city
|
[
"Find",
"the",
"location",
"of",
"businesses",
"that",
"has",
"business",
"hours",
"from",
"9",
"am",
"to",
"9",
"pm",
"every",
"Saturday",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "business_hours"
},
{
"id": 5,
"type": "column",
"value": "closing_time"
},
{
"id": 7,
"type": "column",
"value": "opening_time"
},
{
"id": 9,
"type": "column",
"value": "day_of_week"
},
{
"id": 11,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 10,
"type": "value",
"value": "Saturday"
},
{
"id": 4,
"type": "column",
"value": "day_id"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 1,
"type": "table",
"value": "days"
},
{
"id": 6,
"type": "value",
"value": "9PM"
},
{
"id": 8,
"type": "value",
"value": "9AM"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
13,
14
]
},
{
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},
{
"entity_id": 8,
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10,
11
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},
{
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},
{
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16
]
},
{
"entity_id": 11,
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},
{
"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-TABLE",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
173
|
cs_semester
|
bird:train.json:933
|
In students with a grade of B, how many of them have an intellegence level of 3?
|
SELECT COUNT(T1.student_id) FROM registration AS T1 INNER JOIN student AS T2 ON T1.student_id = T2.student_id WHERE T1.grade = 'B' AND T2.intelligence = 3
|
[
"In",
"students",
"with",
"a",
"grade",
"of",
"B",
",",
"how",
"many",
"of",
"them",
"have",
"an",
"intellegence",
"level",
"of",
"3",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "registration"
},
{
"id": 5,
"type": "column",
"value": "intelligence"
},
{
"id": 2,
"type": "column",
"value": "student_id"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 3,
"type": "column",
"value": "grade"
},
{
"id": 4,
"type": "value",
"value": "B"
},
{
"id": 6,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
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14
]
},
{
"entity_id": 6,
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17
]
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
174
|
airline
|
bird:train.json:5859
|
How many flights depart to Hartsfield-Jackson Atlanta International from Chicago O'Hare International?
|
SELECT COUNT(FL_DATE) FROM Airlines WHERE ORIGIN = ( SELECT T2.ORIGIN FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.ORIGIN WHERE T1.Description = 'Chicago, IL: Chicago O''Hare International' ) AND DEST = ( SELECT T4.DEST FROM Airports AS T3 INNER JOIN Airlines AS T4 ON T3.Code = T4.DEST WHERE T3.Description = 'Atlanta, GA: Hartsfield-Jackson Atlanta International' )
|
[
"How",
"many",
"flights",
"depart",
"to",
"Hartsfield",
"-",
"Jackson",
"Atlanta",
"International",
"from",
"Chicago",
"O'Hare",
"International",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Atlanta, GA: Hartsfield-Jackson Atlanta International"
},
{
"id": 6,
"type": "value",
"value": "Chicago, IL: Chicago O'Hare International"
},
{
"id": 5,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "airlines"
},
{
"id": 4,
"type": "table",
"value": "airports"
},
{
"id": 1,
"type": "column",
"value": "fl_date"
},
{
"id": 2,
"type": "column",
"value": "origin"
},
{
"id": 3,
"type": "column",
"value": "dest"
},
{
"id": 8,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10,
11,
12,
13
]
},
{
"entity_id": 7,
"token_idxs": [
4,
5,
6,
7,
8,
9
]
},
{
"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-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
175
|
car_road_race
|
bird:test.json:1344
|
List the most common type of engine used by drivers.
|
SELECT Engine FROM driver GROUP BY Engine ORDER BY COUNT(*) DESC LIMIT 1
|
[
"List",
"the",
"most",
"common",
"type",
"of",
"engine",
"used",
"by",
"drivers",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "engine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"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",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
176
|
retail_world
|
bird:train.json:6407
|
What territories is the Inside Sales Coordinator in charge of?
|
SELECT T3.TerritoryDescription FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID WHERE T1.Title = 'Inside Sales Coordinator'
|
[
"What",
"territories",
"is",
"the",
"Inside",
"Sales",
"Coordinator",
"in",
"charge",
"of",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Inside Sales Coordinator"
},
{
"id": 0,
"type": "column",
"value": "territorydescription"
},
{
"id": 5,
"type": "table",
"value": "employeeterritories"
},
{
"id": 1,
"type": "table",
"value": "territories"
},
{
"id": 6,
"type": "column",
"value": "territoryid"
},
{
"id": 7,
"type": "column",
"value": "employeeid"
},
{
"id": 4,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
"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",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O"
] |
177
|
soccer_2016
|
bird:train.json:2009
|
How many players are Indians?
|
SELECT COUNT(T1.Player_Id) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_ID WHERE T2.Country_Name = 'India'
|
[
"How",
"many",
"players",
"are",
"Indians",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 4,
"type": "column",
"value": "player_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "value",
"value": "India"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": []
},
{
"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-VALUE",
"O"
] |
178
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4232
|
Show the location name and code with the least documents.
|
SELECT T2.location_name , T1.location_code FROM Document_locations AS T1 JOIN Ref_locations AS T2 ON T1.location_code = T2.location_code GROUP BY T1.location_code ORDER BY count(*) ASC LIMIT 1
|
[
"Show",
"the",
"location",
"name",
"and",
"code",
"with",
"the",
"least",
"documents",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "document_locations"
},
{
"id": 0,
"type": "column",
"value": "location_code"
},
{
"id": 1,
"type": "column",
"value": "location_name"
},
{
"id": 3,
"type": "table",
"value": "ref_locations"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
179
|
movie_3
|
bird:train.json:9389
|
List at least 10 films that the customers can rent for more than 5 days.
|
SELECT T.title FROM ( SELECT T1.title, COUNT(T3.customer_id) AS num FROM film AS T1 INNER JOIN inventory AS T2 ON T1.film_id = T2.film_id INNER JOIN rental AS T3 ON T2.inventory_id = T3.inventory_id WHERE T1.rental_duration > 5 GROUP BY T1.title ) AS T WHERE T.num > 10
|
[
"List",
"at",
"least",
"10",
"films",
"that",
"the",
"customers",
"can",
"rent",
"for",
"more",
"than",
"5",
"days",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "rental_duration"
},
{
"id": 9,
"type": "column",
"value": "inventory_id"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 8,
"type": "table",
"value": "inventory"
},
{
"id": 10,
"type": "column",
"value": "film_id"
},
{
"id": 3,
"type": "table",
"value": "rental"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 7,
"type": "table",
"value": "film"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 2,
"type": "value",
"value": "10"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"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",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
180
|
professional_basketball
|
bird:train.json:2874
|
Among the Most improved Players awarded from 1985-1990, how many player whose country is USA?
|
SELECT COUNT(DISTINCT T2.playerID) FROM awards_players AS T1 INNER JOIN players AS T2 ON T1.playerID = T2.playerID WHERE T1.award = 'Most Improved Player' AND T2.birthCountry = 'USA' AND T1.year BETWEEN 1985 AND 1990
|
[
"Among",
"the",
"Most",
"improved",
"Players",
"awarded",
"from",
"1985",
"-",
"1990",
",",
"how",
"many",
"player",
"whose",
"country",
"is",
"USA",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Most Improved Player"
},
{
"id": 0,
"type": "table",
"value": "awards_players"
},
{
"id": 5,
"type": "column",
"value": "birthcountry"
},
{
"id": 2,
"type": "column",
"value": "playerid"
},
{
"id": 1,
"type": "table",
"value": "players"
},
{
"id": 3,
"type": "column",
"value": "award"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1985"
},
{
"id": 9,
"type": "value",
"value": "1990"
},
{
"id": 6,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
2,
3
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": [
9
]
},
{
"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",
"I-VALUE",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
181
|
aircraft
|
spider:train_spider.json:4798
|
What is the number of aircraft?
|
SELECT count(*) FROM aircraft
|
[
"What",
"is",
"the",
"number",
"of",
"aircraft",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"O"
] |
182
|
computer_student
|
bird:train.json:1037
|
Which courses were taught by a professor who is not a faculty member?
|
SELECT DISTINCT T2.course_id FROM person AS T1 INNER JOIN taughtBy AS T2 ON T1.p_id = T2.p_id WHERE T1.professor = 1 AND T1.hasPosition = 0
|
[
"Which",
"courses",
"were",
"taught",
"by",
"a",
"professor",
"who",
"is",
"not",
"a",
"faculty",
"member",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "hasposition"
},
{
"id": 0,
"type": "column",
"value": "course_id"
},
{
"id": 4,
"type": "column",
"value": "professor"
},
{
"id": 2,
"type": "table",
"value": "taughtby"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "p_id"
},
{
"id": 5,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
183
|
regional_sales
|
bird:train.json:2704
|
Which regions have online sales channels that have the most discounts?
|
SELECT T2.Region FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.`Sales Channel` = 'Online' ORDER BY T1.`Discount Applied` DESC LIMIT 1
|
[
"Which",
"regions",
"have",
"online",
"sales",
"channels",
"that",
"have",
"the",
"most",
"discounts",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Discount Applied"
},
{
"id": 3,
"type": "column",
"value": "Sales Channel"
},
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 7,
"type": "column",
"value": "_salesteamid"
},
{
"id": 6,
"type": "column",
"value": "salesteamid"
},
{
"id": 2,
"type": "table",
"value": "Sales Team"
},
{
"id": 0,
"type": "column",
"value": "region"
},
{
"id": 4,
"type": "value",
"value": "Online"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
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5
]
},
{
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4
]
},
{
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{
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3
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
184
|
works_cycles
|
bird:train.json:7157
|
For the document Control Assistant who was born on 1975/12/25, how many private documents did he/she have?
|
SELECT COUNT(T2.BusinessEntityID) FROM Document AS T1 INNER JOIN Employee AS T2 ON T1.Owner = T2.BusinessEntityID WHERE T2.JobTitle = 'Document Control Assistant' AND T2.BirthDate = '1975-12-25' AND T1.DocumentSummary IS NULL
|
[
"For",
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"Assistant",
"who",
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"born",
"on",
"1975/12/25",
",",
"how",
"many",
"private",
"documents",
"did",
"he",
"/",
"she",
"have",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Document Control Assistant"
},
{
"id": 2,
"type": "column",
"value": "businessentityid"
},
{
"id": 8,
"type": "column",
"value": "documentsummary"
},
{
"id": 7,
"type": "value",
"value": "1975-12-25"
},
{
"id": 6,
"type": "column",
"value": "birthdate"
},
{
"id": 0,
"type": "table",
"value": "document"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "column",
"value": "jobtitle"
},
{
"id": 3,
"type": "column",
"value": "owner"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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{
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},
{
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{
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{
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{
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"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
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"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
185
|
club_1
|
spider:train_spider.json:4280
|
What is the description of the club named "Tennis Club"?
|
SELECT clubdesc FROM club WHERE clubname = "Tennis Club"
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"club",
"named",
"\"",
"Tennis",
"Club",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Tennis Club"
},
{
"id": 1,
"type": "column",
"value": "clubdesc"
},
{
"id": 2,
"type": "column",
"value": "clubname"
},
{
"id": 0,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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{
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"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",
"I-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O"
] |
186
|
university_basketball
|
spider:train_spider.json:999
|
What is the total and minimum enrollment of all schools?
|
SELECT sum(enrollment) , min(enrollment) FROM university
|
[
"What",
"is",
"the",
"total",
"and",
"minimum",
"enrollment",
"of",
"all",
"schools",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 1,
"type": "column",
"value": "enrollment"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
187
|
retails
|
bird:train.json:6834
|
What are the top 5 nations of suppliers with the lowest account balance?
|
SELECT T2.n_name FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey ORDER BY T1.s_acctbal LIMIT 1
|
[
"What",
"are",
"the",
"top",
"5",
"nations",
"of",
"suppliers",
"with",
"the",
"lowest",
"account",
"balance",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "s_nationkey"
},
{
"id": 5,
"type": "column",
"value": "n_nationkey"
},
{
"id": 3,
"type": "column",
"value": "s_acctbal"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 0,
"type": "column",
"value": "n_name"
},
{
"id": 2,
"type": "table",
"value": "nation"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
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5
]
},
{
"entity_id": 3,
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11,
12
]
},
{
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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{
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{
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{
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{
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},
{
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},
{
"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-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
189
|
university_basketball
|
spider:train_spider.json:1012
|
What are the names of teams from universities that have a below average enrollment?
|
SELECT t2.team_name FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id WHERE enrollment < (SELECT avg(enrollment) FROM university)
|
[
"What",
"are",
"the",
"names",
"of",
"teams",
"from",
"universities",
"that",
"have",
"a",
"below",
"average",
"enrollment",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "basketball_match"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 3,
"type": "column",
"value": "enrollment"
},
{
"id": 0,
"type": "column",
"value": "team_name"
},
{
"id": 4,
"type": "column",
"value": "school_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
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},
{
"entity_id": 5,
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},
{
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},
{
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},
{
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{
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{
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},
{
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},
{
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},
{
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},
{
"entity_id": 14,
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},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
190
|
club_1
|
spider:train_spider.json:4297
|
Find the first name and last name for the "CTO" of the club "Hopkins Student Enterprises"?
|
SELECT t3.fname , t3.lname FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t1.clubname = "Hopkins Student Enterprises" AND t2.position = "CTO"
|
[
"Find",
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"name",
"and",
"last",
"name",
"for",
"the",
"\"",
"CTO",
"\"",
"of",
"the",
"club",
"\"",
"Hopkins",
"Student",
"Enterprises",
"\"",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "Hopkins Student Enterprises"
},
{
"id": 4,
"type": "table",
"value": "member_of_club"
},
{
"id": 6,
"type": "column",
"value": "clubname"
},
{
"id": 8,
"type": "column",
"value": "position"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 10,
"type": "column",
"value": "clubid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 5,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "table",
"value": "club"
},
{
"id": 9,
"type": "column",
"value": "CTO"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
16,
18
]
},
{
"entity_id": 8,
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},
{
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10
]
},
{
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},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"O"
] |
191
|
toxicology
|
bird:dev.json:339
|
List the atom ID of the carcinogenic molecule that contains oxygen?
|
SELECT T1.atom_id FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.element = 'o' AND T2.label = '+'
|
[
"List",
"the",
"atom",
"ID",
"of",
"the",
"carcinogenic",
"molecule",
"that",
"contains",
"oxygen",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 0,
"type": "column",
"value": "atom_id"
},
{
"id": 4,
"type": "column",
"value": "element"
},
{
"id": 6,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 5,
"type": "value",
"value": "o"
},
{
"id": 7,
"type": "value",
"value": "+"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
192
|
college_1
|
spider:train_spider.json:3277
|
What is the last name and office of the professor from the history department?
|
SELECT T1.emp_lname , T2.prof_office FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num JOIN department AS T3 ON T2.dept_code = T3.dept_code WHERE T3.dept_name = 'History'
|
[
"What",
"is",
"the",
"last",
"name",
"and",
"office",
"of",
"the",
"professor",
"from",
"the",
"history",
"department",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "prof_office"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "emp_lname"
},
{
"id": 3,
"type": "column",
"value": "dept_name"
},
{
"id": 6,
"type": "table",
"value": "professor"
},
{
"id": 7,
"type": "column",
"value": "dept_code"
},
{
"id": 5,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "value",
"value": "History"
},
{
"id": 8,
"type": "column",
"value": "emp_num"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
193
|
works_cycles
|
bird:train.json:7014
|
List down the product name, reviewer name, rating and comments for product under the road line.
|
SELECT T1.Name, T2.ReviewerName, T2.Rating, T2.Comments FROM Product AS T1 INNER JOIN ProductReview AS T2 USING (productID) WHERE T1.ProductLine = 'R'
|
[
"List",
"down",
"the",
"product",
"name",
",",
"reviewer",
"name",
",",
"rating",
"and",
"comments",
"for",
"product",
"under",
"the",
"road",
"line",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "productreview"
},
{
"id": 1,
"type": "column",
"value": "reviewername"
},
{
"id": 6,
"type": "column",
"value": "productline"
},
{
"id": 3,
"type": "column",
"value": "comments"
},
{
"id": 4,
"type": "table",
"value": "product"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "value",
"value": "R"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"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-TABLE",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
194
|
thrombosis_prediction
|
bird:dev.json:1304
|
Among the patients with a normal blood glucose, how many of them don't have thrombosis?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID INNER JOIN Examination AS T3 ON T1.ID = T3.ID WHERE T2.GLU < 180 AND T3.Thrombosis = 0
|
[
"Among",
"the",
"patients",
"with",
"a",
"normal",
"blood",
"glucose",
",",
"how",
"many",
"of",
"them",
"do",
"n't",
"have",
"thrombosis",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 3,
"type": "table",
"value": "laboratory"
},
{
"id": 6,
"type": "column",
"value": "thrombosis"
},
{
"id": 2,
"type": "table",
"value": "patient"
},
{
"id": 4,
"type": "column",
"value": "glu"
},
{
"id": 5,
"type": "value",
"value": "180"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
195
|
card_games
|
bird:dev.json:362
|
What is the description about the ruling of card "Condemn"?
|
SELECT T2.text FROM cards AS T1 INNER JOIN rulings AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Condemn'
|
[
"What",
"is",
"the",
"description",
"about",
"the",
"ruling",
"of",
"card",
"\"",
"Condemn",
"\"",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "rulings"
},
{
"id": 4,
"type": "value",
"value": "Condemn"
},
{
"id": 1,
"type": "table",
"value": "cards"
},
{
"id": 0,
"type": "column",
"value": "text"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "uuid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"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",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O"
] |
196
|
hr_1
|
spider:train_spider.json:3471
|
return the smallest salary for every departments.
|
SELECT MIN(salary) , department_id FROM employees GROUP BY department_id
|
[
"return",
"the",
"smallest",
"salary",
"for",
"every",
"departments",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "salary"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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-COLUMN",
"O"
] |
197
|
college_3
|
spider:train_spider.json:4669
|
Find the first names of faculties of rank Professor in alphabetic order.
|
SELECT Fname FROM FACULTY WHERE Rank = "Professor" ORDER BY Fname
|
[
"Find",
"the",
"first",
"names",
"of",
"faculties",
"of",
"rank",
"Professor",
"in",
"alphabetic",
"order",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "Professor"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 2,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
198
|
retail_world
|
bird:train.json:6664
|
When was the employee who handled order id 10281 hired?
|
SELECT T1.HireDate FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE T2.OrderID = 10281
|
[
"When",
"was",
"the",
"employee",
"who",
"handled",
"order",
"i",
"d",
"10281",
"hired",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 0,
"type": "column",
"value": "hiredate"
},
{
"id": 3,
"type": "column",
"value": "orderid"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 4,
"type": "value",
"value": "10281"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"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-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-COLUMN",
"O"
] |
199
|
synthea
|
bird:train.json:1540
|
Who is the patient with a body weight of 61.97 kg?
|
SELECT T2.first, T2.last FROM observations AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T1.DESCRIPTION = 'Body Weight' AND T1.UNITS = 'kg' AND T1.VALUE = 61.97
|
[
"Who",
"is",
"the",
"patient",
"with",
"a",
"body",
"weight",
"of",
"61.97",
"kg",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "observations"
},
{
"id": 5,
"type": "column",
"value": "description"
},
{
"id": 6,
"type": "value",
"value": "Body Weight"
},
{
"id": 3,
"type": "table",
"value": "patients"
},
{
"id": 4,
"type": "column",
"value": "patient"
},
{
"id": 0,
"type": "column",
"value": "first"
},
{
"id": 7,
"type": "column",
"value": "units"
},
{
"id": 9,
"type": "column",
"value": "value"
},
{
"id": 10,
"type": "value",
"value": "61.97"
},
{
"id": 1,
"type": "column",
"value": "last"
},
{
"id": 8,
"type": "value",
"value": "kg"
}
] |
[
{
"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": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6,
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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9
]
},
{
"entity_id": 11,
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},
{
"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-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
200
|
mountain_photos
|
spider:train_spider.json:3723
|
How many distinct kinds of camera lenses are used to take photos of mountains in the country 'Ethiopia'?
|
SELECT count(DISTINCT T2.camera_lens_id) FROM mountain AS T1 JOIN photos AS T2 ON T1.id = T2.mountain_id WHERE T1.country = 'Ethiopia'
|
[
"How",
"many",
"distinct",
"kinds",
"of",
"camera",
"lenses",
"are",
"used",
"to",
"take",
"photos",
"of",
"mountains",
"in",
"the",
"country",
"'",
"Ethiopia",
"'",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "camera_lens_id"
},
{
"id": 6,
"type": "column",
"value": "mountain_id"
},
{
"id": 0,
"type": "table",
"value": "mountain"
},
{
"id": 3,
"type": "value",
"value": "Ethiopia"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "photos"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
201
|
regional_sales
|
bird:train.json:2697
|
What percentage of sell orders on 04/04/2020 were for the state of New York?
|
SELECT CAST(SUM(CASE WHEN T2.State = 'New York' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.OrderDate = '4/4/20'
|
[
"What",
"percentage",
"of",
"sell",
"orders",
"on",
"04/04/2020",
"were",
"for",
"the",
"state",
"of",
"New",
"York",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "Store Locations"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 7,
"type": "column",
"value": "ordernumber"
},
{
"id": 2,
"type": "column",
"value": "orderdate"
},
{
"id": 5,
"type": "column",
"value": "_storeid"
},
{
"id": 11,
"type": "value",
"value": "New York"
},
{
"id": 4,
"type": "column",
"value": "storeid"
},
{
"id": 3,
"type": "value",
"value": "4/4/20"
},
{
"id": 10,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
10
]
},
{
"entity_id": 11,
"token_idxs": [
12,
13
]
},
{
"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",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
202
|
movielens
|
bird:train.json:2286
|
How many distinct movies in English stars a male actor who acts the best?
|
SELECT COUNT(DISTINCT T1.actorid) FROM actors AS T1 INNER JOIN movies2actors AS T2 ON T1.actorid = T2.actorid INNER JOIN movies AS T3 ON T2.movieid = T3.movieid WHERE T3.isEnglish = 'T' AND T1.a_gender = 'M' AND T1.a_quality = 5
|
[
"How",
"many",
"distinct",
"movies",
"in",
"English",
"stars",
"a",
"male",
"actor",
"who",
"acts",
"the",
"best",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "movies2actors"
},
{
"id": 5,
"type": "column",
"value": "isenglish"
},
{
"id": 9,
"type": "column",
"value": "a_quality"
},
{
"id": 7,
"type": "column",
"value": "a_gender"
},
{
"id": 1,
"type": "column",
"value": "actorid"
},
{
"id": 4,
"type": "column",
"value": "movieid"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 2,
"type": "table",
"value": "actors"
},
{
"id": 6,
"type": "value",
"value": "T"
},
{
"id": 8,
"type": "value",
"value": "M"
},
{
"id": 10,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"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-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
203
|
mondial_geo
|
bird:train.json:8460
|
What is the full name of ABEDA and when was it established?
|
SELECT Name, Established FROM organization WHERE Abbreviation = 'ABEDA'
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"ABEDA",
"and",
"when",
"was",
"it",
"established",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "organization"
},
{
"id": 3,
"type": "column",
"value": "abbreviation"
},
{
"id": 2,
"type": "column",
"value": "established"
},
{
"id": 4,
"type": "value",
"value": "ABEDA"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"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-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
204
|
movie_3
|
bird:train.json:9243
|
List the address in Texas in the ascending order of city id.
|
SELECT address FROM address WHERE district = 'Texas' AND city_id = ( SELECT MIN(city_id) FROM address WHERE district = 'Texas' )
|
[
"List",
"the",
"address",
"in",
"Texas",
"in",
"the",
"ascending",
"order",
"of",
"city",
"i",
"d."
] |
[
{
"id": 2,
"type": "column",
"value": "district"
},
{
"id": 0,
"type": "table",
"value": "address"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 4,
"type": "column",
"value": "city_id"
},
{
"id": 3,
"type": "value",
"value": "Texas"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12
]
},
{
"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",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
205
|
customers_card_transactions
|
spider:train_spider.json:739
|
Show the card type codes and the number of transactions.
|
SELECT T2.card_type_code , count(*) FROM Financial_transactions AS T1 JOIN Customers_cards AS T2 ON T1.card_id = T2.card_id GROUP BY T2.card_type_code
|
[
"Show",
"the",
"card",
"type",
"codes",
"and",
"the",
"number",
"of",
"transactions",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "financial_transactions"
},
{
"id": 2,
"type": "table",
"value": "customers_cards"
},
{
"id": 0,
"type": "column",
"value": "card_type_code"
},
{
"id": 3,
"type": "column",
"value": "card_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
206
|
icfp_1
|
spider:train_spider.json:2874
|
Who belong to the institution "University of Oxford"? Show the first names and last names.
|
SELECT DISTINCT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN inst AS t3 ON t2.instid = t3.instid WHERE t3.name = "University of Oxford"
|
[
"Who",
"belong",
"to",
"the",
"institution",
"\"",
"University",
"of",
"Oxford",
"\"",
"?",
"Show",
"the",
"first",
"names",
"and",
"last",
"names",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "University of Oxford"
},
{
"id": 6,
"type": "table",
"value": "authorship"
},
{
"id": 5,
"type": "table",
"value": "authors"
},
{
"id": 7,
"type": "column",
"value": "instid"
},
{
"id": 8,
"type": "column",
"value": "authid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 2,
"type": "table",
"value": "inst"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
207
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4242
|
Show the ids of all employees who have authorized destruction.
|
SELECT DISTINCT Destruction_Authorised_by_Employee_ID FROM Documents_to_be_destroyed
|
[
"Show",
"the",
"ids",
"of",
"all",
"employees",
"who",
"have",
"authorized",
"destruction",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "destruction_authorised_by_employee_id"
},
{
"id": 0,
"type": "table",
"value": "documents_to_be_destroyed"
}
] |
[
{
"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": []
},
{
"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",
"O"
] |
208
|
image_and_language
|
bird:train.json:7583
|
What is the image ID with a predicted class of "parked on"?
|
SELECT DISTINCT T1.IMG_ID FROM IMG_REL AS T1 INNER JOIN PRED_CLASSES AS T2 ON T1.PRED_CLASS_ID = T2.PRED_CLASS_ID WHERE T2.PRED_CLASS = 'parked on'
|
[
"What",
"is",
"the",
"image",
"ID",
"with",
"a",
"predicted",
"class",
"of",
"\"",
"parked",
"on",
"\"",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "pred_class_id"
},
{
"id": 2,
"type": "table",
"value": "pred_classes"
},
{
"id": 3,
"type": "column",
"value": "pred_class"
},
{
"id": 4,
"type": "value",
"value": "parked on"
},
{
"id": 1,
"type": "table",
"value": "img_rel"
},
{
"id": 0,
"type": "column",
"value": "img_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
209
|
cookbook
|
bird:train.json:8891
|
How many ingredients are there in Apricot Yogurt Parfaits?
|
SELECT COUNT(*) FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.title = 'Apricot Yogurt Parfaits'
|
[
"How",
"many",
"ingredients",
"are",
"there",
"in",
"Apricot",
"Yogurt",
"Parfaits",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Apricot Yogurt Parfaits"
},
{
"id": 4,
"type": "column",
"value": "recipe_id"
},
{
"id": 1,
"type": "table",
"value": "quantity"
},
{
"id": 0,
"type": "table",
"value": "recipe"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
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",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
210
|
game_1
|
spider:train_spider.json:6034
|
How many different students play games?
|
SELECT count(DISTINCT StuID) FROM Plays_games
|
[
"How",
"many",
"different",
"students",
"play",
"games",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "plays_games"
},
{
"id": 1,
"type": "column",
"value": "stuid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O"
] |
211
|
customer_complaints
|
spider:train_spider.json:5780
|
What is the phone number of the customer who has filed the most recent complaint?
|
SELECT t1.phone_number FROM customers AS t1 JOIN complaints AS t2 ON t1.customer_id = t2.customer_id ORDER BY t2.date_complaint_raised DESC LIMIT 1
|
[
"What",
"is",
"the",
"phone",
"number",
"of",
"the",
"customer",
"who",
"has",
"filed",
"the",
"most",
"recent",
"complaint",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "date_complaint_raised"
},
{
"id": 0,
"type": "column",
"value": "phone_number"
},
{
"id": 4,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "complaints"
},
{
"id": 1,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
212
|
retail_world
|
bird:train.json:6384
|
List the company names of customers from the city with the most customers.
|
SELECT CompanyName FROM `Customer and Suppliers by City` WHERE CITY = ( SELECT City FROM `Customer and Suppliers by City` GROUP BY City ORDER BY COUNT(Relationship) DESC LIMIT 1 )
|
[
"List",
"the",
"company",
"names",
"of",
"customers",
"from",
"the",
"city",
"with",
"the",
"most",
"customers",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "Customer and Suppliers by City"
},
{
"id": 3,
"type": "column",
"value": "relationship"
},
{
"id": 1,
"type": "column",
"value": "companyname"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"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-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
213
|
device
|
spider:train_spider.json:5079
|
What are the different software platforms for devices, ordered by frequency descending?
|
SELECT Software_Platform FROM device GROUP BY Software_Platform ORDER BY COUNT(*) DESC
|
[
"What",
"are",
"the",
"different",
"software",
"platforms",
"for",
"devices",
",",
"ordered",
"by",
"frequency",
"descending",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "software_platform"
},
{
"id": 0,
"type": "table",
"value": "device"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
214
|
works_cycles
|
bird:train.json:7182
|
What are the total per assembly quantity for unit measure code EA, IN and OZ respectively? What are the name of these 3 code?
|
SELECT SUM(T1.PerAssemblyQty), T2.Name FROM BillOfMaterials AS T1 INNER JOIN UnitMeasure AS T2 ON T1.UnitMeasureCode = T2.UnitMeasureCode WHERE T1.UnitMeasureCode IN ('EA', 'IN', 'OZ') GROUP BY T2.Name
|
[
"What",
"are",
"the",
"total",
"per",
"assembly",
"quantity",
"for",
"unit",
"measure",
"code",
"EA",
",",
"IN",
"and",
"OZ",
"respectively",
"?",
"What",
"are",
"the",
"name",
"of",
"these",
"3",
"code",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "billofmaterials"
},
{
"id": 3,
"type": "column",
"value": "unitmeasurecode"
},
{
"id": 7,
"type": "column",
"value": "perassemblyqty"
},
{
"id": 2,
"type": "table",
"value": "unitmeasure"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "EA"
},
{
"id": 5,
"type": "value",
"value": "IN"
},
{
"id": 6,
"type": "value",
"value": "OZ"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
21
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
4,
5
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
215
|
insurance_and_eClaims
|
spider:train_spider.json:1508
|
Sort the customer names in alphabetical order.
|
SELECT customer_details FROM customers ORDER BY customer_details
|
[
"Sort",
"the",
"customer",
"names",
"in",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customer_details"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"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",
"O",
"O"
] |
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