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2,571
|
simpson_episodes
|
bird:train.json:4256
|
Who is the recipient of the Primetime Emmy Award with the most votes?
|
SELECT T1.person FROM Award AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T1.award_category = 'Primetime Emmy' ORDER BY T2.votes DESC LIMIT 1;
|
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2,572
|
beer_factory
|
bird:train.json:5280
|
Between Sac State Union and Sac State American River Courtyard, which location sold the most Dog n Suds root beer?
|
SELECT T3.LocationName FROM rootbeer AS T1 INNER JOIN rootbeerbrand AS T2 ON T1.BrandID = T2.BrandID INNER JOIN location AS T3 ON T1.LocationID = T3.LocationID WHERE T2.BrandName = 'Dog n Suds' AND T3.LocationName IN ('Sac State American River Courtyard', 'Sac State Union') GROUP BY T1.LocationID ORDER BY COUNT(T1.BrandID) DESC LIMIT 1
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2,573
|
country_language
|
bird:test.json:1389
|
What are the names of the official languages, sorted descending by the average overall scores across the countries that correspond to each?
|
SELECT T3.name FROM countries AS T1 JOIN official_languages AS T2 ON T1.id = T2.country_id JOIN languages AS T3 ON T2.language_id = T3.id GROUP BY T3.id ORDER BY avg(T1.overall_score) DESC
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{
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"value": "name"
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"value": "id"
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"O",
"O",
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"O",
"O",
"O",
"O",
"O"
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2,574
|
party_people
|
spider:train_spider.json:2068
|
Which member names corresponding to members who are not in the Progress Party?
|
SELECT T1.member_name FROM Member AS T1 JOIN party AS T2 ON T1.party_id = T2.party_id WHERE T2.Party_name != "Progress Party"
|
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{
"id": 1,
"type": "table",
"value": "member"
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{
"id": 2,
"type": "table",
"value": "party"
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"B-TABLE",
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2,575
|
movie_3
|
bird:train.json:9195
|
Among the classic movies, how many movies have a rental rate of less than 1?
|
SELECT COUNT(T1.film_id) FROM film_category AS T1 INNER JOIN category AS T2 ON T1.category_id = T2.category_id INNER JOIN film AS T3 ON T1.film_id = T3.film_id WHERE T3.rental_rate < 1 AND T2.name = 'Classics'
|
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{
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"type": "column",
"value": "name"
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{
"id": 5,
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"value": "1"
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2,576
|
computer_student
|
bird:train.json:1024
|
How many professors teaches no more than two high-level or harder undergraduate courses?
|
SELECT COUNT(*) FROM ( SELECT COUNT(T2.p_id) FROM course AS T1 INNER JOIN taughtBy AS T2 ON T1.course_id = T2.course_id WHERE T1.courseLevel = 'Level_400' GROUP BY T2.p_id HAVING COUNT(DISTINCT T1.course_id) <= 2 )
|
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{
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{
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"value": "2"
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2,577
|
disney
|
bird:train.json:4718
|
Calculate the percentage of voice actors whose main character in the movie is in the Drama genre.
|
SELECT CAST(COUNT(CASE WHEN T1.genre = 'Drama' THEN T3.`voice-actor` ELSE NULL END) AS REAL) * 100 / COUNT(T3.`voice-actor`) FROM movies_total_gross AS T1 INNER JOIN characters AS T2 ON T1.movie_title = T2.movie_title INNER JOIN `voice-actors` AS T3 ON T3.movie = T1.movie_title
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{
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{
"id": 4,
"type": "column",
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"type": "column",
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{
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{
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{
"id": 8,
"type": "value",
"value": "Drama"
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{
"id": 5,
"type": "value",
"value": "100"
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"O",
"B-VALUE",
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"O"
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2,578
|
student_club
|
bird:dev.json:1362
|
How many cities are there in Orange County, Virginia?
|
SELECT COUNT(city) FROM zip_code WHERE county = 'Orange County' AND state = 'Virginia'
|
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"id": 5,
"type": "value",
"value": "Virginia"
},
{
"id": 2,
"type": "column",
"value": "county"
},
{
"id": 4,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
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6
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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9
]
},
{
"entity_id": 6,
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},
{
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},
{
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},
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"entity_id": 9,
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},
{
"entity_id": 11,
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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",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,580
|
professional_basketball
|
bird:train.json:2906
|
How many times between 1975 and 1980 did the player abdulka01 play for LAL?
|
SELECT COUNT(DISTINCT T2.year) FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE T2.tmID = 'LAL' AND T2.year BETWEEN 1975 AND 1980 AND T1.playerID = 'abdulka01'
|
[
"How",
"many",
"times",
"between",
"1975",
"and",
"1980",
"did",
"the",
"player",
"abdulka01",
"play",
"for",
"LAL",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "players_teams"
},
{
"id": 8,
"type": "value",
"value": "abdulka01"
},
{
"id": 3,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "players"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "column",
"value": "tmid"
},
{
"id": 6,
"type": "value",
"value": "1975"
},
{
"id": 7,
"type": "value",
"value": "1980"
},
{
"id": 5,
"type": "value",
"value": "LAL"
}
] |
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{
"entity_id": 0,
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},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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9
]
},
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{
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13
]
},
{
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4
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},
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6
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},
{
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]
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{
"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
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},
{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
2,581
|
match_season
|
spider:train_spider.json:1088
|
Show the players and years played for players from team "Columbus Crew".
|
SELECT T1.Player , T1.Years_Played FROM player AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id WHERE T2.Name = "Columbus Crew"
|
[
"Show",
"the",
"players",
"and",
"years",
"played",
"for",
"players",
"from",
"team",
"\"",
"Columbus",
"Crew",
"\"",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "Columbus Crew"
},
{
"id": 1,
"type": "column",
"value": "years_played"
},
{
"id": 7,
"type": "column",
"value": "team_id"
},
{
"id": 0,
"type": "column",
"value": "player"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "table",
"value": "team"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
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9
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
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"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
2,582
|
student_club
|
bird:dev.json:1414
|
State the name of major that Phillip Cullen has joined.
|
SELECT T1.major_name FROM major AS T1 INNER JOIN member AS T2 ON T1.major_id = T2.link_to_major WHERE T2.first_name = 'Phillip' AND T2.last_name = 'Cullen'
|
[
"State",
"the",
"name",
"of",
"major",
"that",
"Phillip",
"Cullen",
"has",
"joined",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_major"
},
{
"id": 0,
"type": "column",
"value": "major_name"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "major_id"
},
{
"id": 6,
"type": "value",
"value": "Phillip"
},
{
"id": 2,
"type": "table",
"value": "member"
},
{
"id": 8,
"type": "value",
"value": "Cullen"
},
{
"id": 1,
"type": "table",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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4
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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6
]
},
{
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"token_idxs": [
2
]
},
{
"entity_id": 8,
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7
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
"token_idxs": []
},
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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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O"
] |
2,583
|
debit_card_specializing
|
bird:dev.json:1480
|
What was the gas consumption peak month for SME customers in 2013?
|
SELECT SUBSTR(T2.Date, 5, 2) FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID WHERE SUBSTR(T2.Date, 1, 4) = '2013' AND T1.Segment = 'SME' GROUP BY SUBSTR(T2.Date, 5, 2) ORDER BY SUM(T2.Consumption) DESC LIMIT 1
|
[
"What",
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"the",
"gas",
"consumption",
"peak",
"month",
"for",
"SME",
"customers",
"in",
"2013",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "consumption"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "table",
"value": "yearmonth"
},
{
"id": 7,
"type": "column",
"value": "segment"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "2013"
},
{
"id": 8,
"type": "value",
"value": "SME"
},
{
"id": 3,
"type": "value",
"value": "5"
},
{
"id": 4,
"type": "value",
"value": "2"
},
{
"id": 10,
"type": "value",
"value": "1"
},
{
"id": 11,
"type": "value",
"value": "4"
}
] |
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5,
6
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},
{
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},
{
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},
{
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{
"entity_id": 6,
"token_idxs": [
11
]
},
{
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},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
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4
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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": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,585
|
works_cycles
|
bird:train.json:7466
|
Who owns the email address "regina7@adventure-works.com"?
|
SELECT T2.FirstName, T2.LastName FROM EmailAddress AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.EmailAddress = 'regina7@adventure-works.com'
|
[
"Who",
"owns",
"the",
"email",
"address",
"\"",
"regina7@adventure-works.com",
"\"",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "regina7@adventure-works.com"
},
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 2,
"type": "table",
"value": "emailaddress"
},
{
"id": 4,
"type": "column",
"value": "emailaddress"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
3,
4
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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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",
"B-VALUE",
"O",
"O"
] |
2,586
|
retail_world
|
bird:train.json:6348
|
Give the contact name of the supplier for the product "Gudbrandsdalsost".
|
SELECT T2.ContactName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ProductName = 'Gudbrandsdalsost'
|
[
"Give",
"the",
"contact",
"name",
"of",
"the",
"supplier",
"for",
"the",
"product",
"\"",
"Gudbrandsdalsost",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Gudbrandsdalsost"
},
{
"id": 0,
"type": "column",
"value": "contactname"
},
{
"id": 3,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
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9
]
},
{
"entity_id": 2,
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6
]
},
{
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"token_idxs": []
},
{
"entity_id": 4,
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11
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},
{
"entity_id": 5,
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 9,
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},
{
"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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O"
] |
2,587
|
college_completion
|
bird:train.json:3743
|
In year 2010 at schools located in Hawaii, what is the percentage of schools offers an associate's degree?
|
SELECT CAST(SUM(CASE WHEN T2.level = '2-year' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.level) FROM state_sector_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.stateid = T1.stateid WHERE T2.state = 'Hawaii' AND T2.year = 2010
|
[
"In",
"year",
"2010",
"at",
"schools",
"located",
"in",
"Hawaii",
",",
"what",
"is",
"the",
"percentage",
"of",
"schools",
"offers",
"an",
"associate",
"'s",
"degree",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "state_sector_details"
},
{
"id": 1,
"type": "table",
"value": "state_sector_grads"
},
{
"id": 2,
"type": "column",
"value": "stateid"
},
{
"id": 4,
"type": "value",
"value": "Hawaii"
},
{
"id": 11,
"type": "value",
"value": "2-year"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 8,
"type": "column",
"value": "level"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "value",
"value": "2010"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 9,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,588
|
world
|
bird:train.json:7873
|
Which country has the smallest surface area?
|
SELECT Name FROM Country ORDER BY SurfaceArea ASC LIMIT 1
|
[
"Which",
"country",
"has",
"the",
"smallest",
"surface",
"area",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "surfacearea"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,589
|
tracking_grants_for_research
|
spider:train_spider.json:4371
|
What is the type description of the organization whose detail is listed as 'quo'?
|
SELECT T1.organisation_type_description FROM organisation_Types AS T1 JOIN Organisations AS T2 ON T1.organisation_type = T2.organisation_type WHERE T2.organisation_details = 'quo'
|
[
"What",
"is",
"the",
"type",
"description",
"of",
"the",
"organization",
"whose",
"detail",
"is",
"listed",
"as",
"'",
"quo",
"'",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "organisation_type_description"
},
{
"id": 3,
"type": "column",
"value": "organisation_details"
},
{
"id": 1,
"type": "table",
"value": "organisation_types"
},
{
"id": 5,
"type": "column",
"value": "organisation_type"
},
{
"id": 2,
"type": "table",
"value": "organisations"
},
{
"id": 4,
"type": "value",
"value": "quo"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"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",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,590
|
aan_1
|
bird:test.json:974
|
What are the names and addresses for all affiliations?
|
SELECT DISTINCT name , address FROM Affiliation
|
[
"What",
"are",
"the",
"names",
"and",
"addresses",
"for",
"all",
"affiliations",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "affiliation"
},
{
"id": 2,
"type": "column",
"value": "address"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,592
|
bike_share_1
|
bird:train.json:9071
|
How many trips with a bike borrowed from the stations in San Francisco were made by a subscriber?
|
SELECT COUNT(T1.id) FROM trip AS T1 INNER JOIN station AS T2 ON T2.ID = T1.start_station_id WHERE T2.city = 'San Francisco' AND T1.subscription_type = 'Subscriber'
|
[
"How",
"many",
"trips",
"with",
"a",
"bike",
"borrowed",
"from",
"the",
"stations",
"in",
"San",
"Francisco",
"were",
"made",
"by",
"a",
"subscriber",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "subscription_type"
},
{
"id": 3,
"type": "column",
"value": "start_station_id"
},
{
"id": 5,
"type": "value",
"value": "San Francisco"
},
{
"id": 7,
"type": "value",
"value": "Subscriber"
},
{
"id": 1,
"type": "table",
"value": "station"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 4,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
17
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,593
|
simpson_episodes
|
bird:train.json:4203
|
What year did the Simpsons receive its first ever award for Favorite Animated Comedy in People's Choice Award?
|
SELECT year FROM Award WHERE result = 'Winner' AND award = 'Favorite Animated Comedy' ORDER BY year DESC LIMIT 1;
|
[
"What",
"year",
"did",
"the",
"Simpsons",
"receive",
"its",
"first",
"ever",
"award",
"for",
"Favorite",
"Animated",
"Comedy",
"in",
"People",
"'s",
"Choice",
"Award",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Favorite Animated Comedy"
},
{
"id": 2,
"type": "column",
"value": "result"
},
{
"id": 3,
"type": "value",
"value": "Winner"
},
{
"id": 0,
"type": "table",
"value": "award"
},
{
"id": 4,
"type": "column",
"value": "award"
},
{
"id": 1,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": [
11,
12,
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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,594
|
riding_club
|
spider:train_spider.json:1719
|
How many players are there?
|
SELECT count(*) FROM player
|
[
"How",
"many",
"players",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player"
}
] |
[
{
"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"
] |
2,595
|
workshop_paper
|
spider:train_spider.json:5842
|
List the authors who do not have submission to any workshop.
|
SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance)
|
[
"List",
"the",
"authors",
"who",
"do",
"not",
"have",
"submission",
"to",
"any",
"workshop",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "submission_id"
},
{
"id": 0,
"type": "table",
"value": "submission"
},
{
"id": 3,
"type": "table",
"value": "acceptance"
},
{
"id": 1,
"type": "column",
"value": "author"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
2,596
|
e_government
|
spider:train_spider.json:6337
|
What are the names of organizations that contain the word "Party"?
|
SELECT organization_name FROM organizations WHERE organization_name LIKE "%Party%"
|
[
"What",
"are",
"the",
"names",
"of",
"organizations",
"that",
"contain",
"the",
"word",
"\"",
"Party",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "organization_name"
},
{
"id": 0,
"type": "table",
"value": "organizations"
},
{
"id": 2,
"type": "column",
"value": "%Party%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,597
|
ice_hockey_draft
|
bird:train.json:6959
|
Who has the heaviest weight?
|
SELECT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN weight_info AS T2 ON T1.weight = T2.weight_id ORDER BY T2.weight_in_kg DESC LIMIT 1
|
[
"Who",
"has",
"the",
"heaviest",
"weight",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "weight_in_kg"
},
{
"id": 2,
"type": "table",
"value": "weight_info"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 1,
"type": "table",
"value": "playerinfo"
},
{
"id": 5,
"type": "column",
"value": "weight_id"
},
{
"id": 4,
"type": "column",
"value": "weight"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"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"
] |
2,598
|
chinook_1
|
spider:train_spider.json:840
|
What are the titles and ids for albums containing tracks with unit price greater than 1?
|
SELECT T1.Title , T2.AlbumID FROM ALBUM AS T1 JOIN TRACK AS T2 ON T1.AlbumId = T2.AlbumId WHERE T2.UnitPrice > 1 GROUP BY T2.AlbumID
|
[
"What",
"are",
"the",
"titles",
"and",
"ids",
"for",
"albums",
"containing",
"tracks",
"with",
"unit",
"price",
"greater",
"than",
"1",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "unitprice"
},
{
"id": 0,
"type": "column",
"value": "albumid"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "album"
},
{
"id": 3,
"type": "table",
"value": "track"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,599
|
movie_3
|
bird:train.json:9396
|
List at least 3 cities under the country of Philippines.
|
SELECT T1.city FROM city AS T1 INNER JOIN country AS T2 ON T2.country_id = T1.country_id WHERE country = 'Philippines'
|
[
"List",
"at",
"least",
"3",
"cities",
"under",
"the",
"country",
"of",
"Philippines",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Philippines"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,600
|
e_commerce
|
bird:test.json:100
|
How many items are shipped?
|
SELECT count(*) FROM Shipment_Items
|
[
"How",
"many",
"items",
"are",
"shipped",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "shipment_items"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
2,601
|
music_4
|
spider:train_spider.json:6179
|
What is the famous release date of the artist with the oldest age?
|
SELECT Famous_Release_date FROM artist ORDER BY Age DESC LIMIT 1
|
[
"What",
"is",
"the",
"famous",
"release",
"date",
"of",
"the",
"artist",
"with",
"the",
"oldest",
"age",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "famous_release_date"
},
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,603
|
boat_1
|
bird:test.json:905
|
Find the total number of boats.
|
SELECT count(*) FROM Boats
|
[
"Find",
"the",
"total",
"number",
"of",
"boats",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "boats"
}
] |
[
{
"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"
] |
2,604
|
mondial_geo
|
bird:train.json:8332
|
List all the mountains that are volcanic along with its longitude and latitude.
|
SELECT Name, Latitude, Longitude FROM mountain WHERE Type = 'volcano'
|
[
"List",
"all",
"the",
"mountains",
"that",
"are",
"volcanic",
"along",
"with",
"its",
"longitude",
"and",
"latitude",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "longitude"
},
{
"id": 0,
"type": "table",
"value": "mountain"
},
{
"id": 2,
"type": "column",
"value": "latitude"
},
{
"id": 5,
"type": "value",
"value": "volcano"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,605
|
retails
|
bird:train.json:6879
|
The part "hot spring dodger dim light" is ordered in how many orders?
|
SELECT COUNT(T1.p_partkey) FROM part AS T1 INNER JOIN lineitem AS T2 ON T1.p_partkey = T2.l_partkey WHERE T1.p_name = 'hot spring dodger dim light'
|
[
"The",
"part",
"\"",
"hot",
"spring",
"dodger",
"dim",
"light",
"\"",
"is",
"ordered",
"in",
"how",
"many",
"orders",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "hot spring dodger dim light"
},
{
"id": 4,
"type": "column",
"value": "p_partkey"
},
{
"id": 5,
"type": "column",
"value": "l_partkey"
},
{
"id": 1,
"type": "table",
"value": "lineitem"
},
{
"id": 2,
"type": "column",
"value": "p_name"
},
{
"id": 0,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3,
4,
5,
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,606
|
cre_Doc_and_collections
|
bird:test.json:729
|
List id of documents that in document subset Best for 2000 and collection named Best.
|
SELECT DISTINCT T1.Document_Object_ID FROM Document_Subset_Members AS T1 JOIN Document_Subsets AS T2 ON T1.Document_Subset_ID = T2.Document_Subset_ID JOIN Documents_in_Collections AS T3 ON T1.Document_Object_ID = T3.Document_Object_ID JOIN Collections AS T4 ON T3.Collection_ID = T4.Collection_ID WHERE T2.Document_Subset_Name = "Best for 2000" AND T4.Collection_Name = "Best";
|
[
"List",
"i",
"d",
"of",
"documents",
"that",
"in",
"document",
"subset",
"Best",
"for",
"2000",
"and",
"collection",
"named",
"Best",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "documents_in_collections"
},
{
"id": 8,
"type": "table",
"value": "document_subset_members"
},
{
"id": 4,
"type": "column",
"value": "document_subset_name"
},
{
"id": 0,
"type": "column",
"value": "document_object_id"
},
{
"id": 10,
"type": "column",
"value": "document_subset_id"
},
{
"id": 9,
"type": "table",
"value": "document_subsets"
},
{
"id": 6,
"type": "column",
"value": "collection_name"
},
{
"id": 3,
"type": "column",
"value": "collection_id"
},
{
"id": 5,
"type": "column",
"value": "Best for 2000"
},
{
"id": 1,
"type": "table",
"value": "collections"
},
{
"id": 7,
"type": "column",
"value": "Best"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
7,
8
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O"
] |
2,609
|
disney
|
bird:train.json:4664
|
Which director has made the most movies?
|
SELECT director, COUNT(name) FROM director GROUP BY director ORDER BY COUNT(name) DESC LIMIT 1
|
[
"Which",
"director",
"has",
"made",
"the",
"most",
"movies",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "director"
},
{
"id": 1,
"type": "column",
"value": "director"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,610
|
movie_3
|
bird:train.json:9167
|
State the name of the category which has the most number of films.
|
SELECT T.name FROM ( SELECT T2.name, COUNT(T1.film_id) AS num FROM film_category AS T1 INNER JOIN category AS T2 ON T1.category_id = T2.category_id GROUP BY T2.name ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"State",
"the",
"name",
"of",
"the",
"category",
"which",
"has",
"the",
"most",
"number",
"of",
"films",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "film_category"
},
{
"id": 5,
"type": "column",
"value": "category_id"
},
{
"id": 3,
"type": "table",
"value": "category"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
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2
]
},
{
"entity_id": 1,
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10
]
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},
{
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5
]
},
{
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12
]
},
{
"entity_id": 5,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,611
|
thrombosis_prediction
|
bird:dev.json:1210
|
What is the average index of the lactate dehydrogenase (LDH) for all patients with lactate dehydrogenase (LDH) within the normal range.
|
SELECT AVG(LDH) FROM Laboratory WHERE LDH < 500
|
[
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"is",
"the",
"average",
"index",
"of",
"the",
"lactate",
"dehydrogenase",
"(",
"LDH",
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"patients",
"with",
"lactate",
"dehydrogenase",
"(",
"LDH",
")",
"within",
"the",
"normal",
"range",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "laboratory"
},
{
"id": 1,
"type": "column",
"value": "ldh"
},
{
"id": 2,
"type": "value",
"value": "500"
}
] |
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{
"entity_id": 0,
"token_idxs": []
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{
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10
]
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{
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},
{
"entity_id": 7,
"token_idxs": []
},
{
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},
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},
{
"entity_id": 10,
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"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,612
|
cinema
|
spider:train_spider.json:1950
|
What is total number of show times per dat for each cinema?
|
SELECT T2.name , sum(T1.show_times_per_day) FROM schedule AS T1 JOIN cinema AS T2 ON T1.cinema_id = T2.cinema_id GROUP BY T1.cinema_id
|
[
"What",
"is",
"total",
"number",
"of",
"show",
"times",
"per",
"dat",
"for",
"each",
"cinema",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "show_times_per_day"
},
{
"id": 0,
"type": "column",
"value": "cinema_id"
},
{
"id": 2,
"type": "table",
"value": "schedule"
},
{
"id": 3,
"type": "table",
"value": "cinema"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6,
7,
8
]
},
{
"entity_id": 5,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,613
|
public_review_platform
|
bird:train.json:4127
|
List the active business ID and its stars of the businesses fall under the category of Food.
|
SELECT DISTINCT T1.business_id, T1.stars FROM Business AS T1 INNER JOIN Business_Categories AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T2.category_id = T3.category_id WHERE T3.category_name = 'Food' AND T1.active = 'true'
|
[
"List",
"the",
"active",
"business",
"ID",
"and",
"its",
"stars",
"of",
"the",
"businesses",
"fall",
"under",
"the",
"category",
"of",
"Food",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "business_categories"
},
{
"id": 6,
"type": "column",
"value": "category_name"
},
{
"id": 0,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "column",
"value": "category_id"
},
{
"id": 2,
"type": "table",
"value": "categories"
},
{
"id": 3,
"type": "table",
"value": "business"
},
{
"id": 8,
"type": "column",
"value": "active"
},
{
"id": 1,
"type": "column",
"value": "stars"
},
{
"id": 7,
"type": "value",
"value": "Food"
},
{
"id": 9,
"type": "value",
"value": "true"
}
] |
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{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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7
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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16
]
},
{
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2
]
},
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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-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,614
|
university_basketball
|
spider:train_spider.json:998
|
What are the enrollment and primary conference for the university which was founded the earliest?
|
SELECT enrollment , primary_conference FROM university ORDER BY founded LIMIT 1
|
[
"What",
"are",
"the",
"enrollment",
"and",
"primary",
"conference",
"for",
"the",
"university",
"which",
"was",
"founded",
"the",
"earliest",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "primary_conference"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 1,
"type": "column",
"value": "enrollment"
},
{
"id": 3,
"type": "column",
"value": "founded"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
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3
]
},
{
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5,
6
]
},
{
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12
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,616
|
customers_and_invoices
|
spider:train_spider.json:1551
|
Show the id, the date of account opened, the account name, and other account detail for all accounts.
|
SELECT account_id , date_account_opened , account_name , other_account_details FROM Accounts
|
[
"Show",
"the",
"i",
"d",
",",
"the",
"date",
"of",
"account",
"opened",
",",
"the",
"account",
"name",
",",
"and",
"other",
"account",
"detail",
"for",
"all",
"accounts",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "other_account_details"
},
{
"id": 2,
"type": "column",
"value": "date_account_opened"
},
{
"id": 3,
"type": "column",
"value": "account_name"
},
{
"id": 1,
"type": "column",
"value": "account_id"
},
{
"id": 0,
"type": "table",
"value": "accounts"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
21
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
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16,
17,
18
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"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",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,617
|
language_corpus
|
bird:train.json:5707
|
What is the title of corpus with most words?
|
SELECT title FROM pages WHERE words = ( SELECT MAX(words) FROM pages )
|
[
"What",
"is",
"the",
"title",
"of",
"corpus",
"with",
"most",
"words",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "words"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,618
|
student_assessment
|
spider:train_spider.json:81
|
How many registed students do each course have? List course name and the number of their registered students?
|
SELECT T3.course_name , count(*) FROM students AS T1 JOIN student_course_registrations AS T2 ON T1.student_id = T2.student_id JOIN courses AS T3 ON T2.course_id = T3.course_id GROUP BY T2.course_id
|
[
"How",
"many",
"registed",
"students",
"do",
"each",
"course",
"have",
"?",
"List",
"course",
"name",
"and",
"the",
"number",
"of",
"their",
"registered",
"students",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "student_course_registrations"
},
{
"id": 1,
"type": "column",
"value": "course_name"
},
{
"id": 5,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "column",
"value": "course_id"
},
{
"id": 3,
"type": "table",
"value": "students"
},
{
"id": 2,
"type": "table",
"value": "courses"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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]
},
{
"entity_id": 6,
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},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,619
|
california_schools
|
bird:dev.json:87
|
What are the valid e-mail addresses of the administrator of the school located in the San Bernardino county, City of San Bernardino City Unified that opened between 1/1/2009 to 12/31/2010 whose school types are public Intermediate/Middle Schools and Unified Schools?
|
SELECT T2.AdmEmail1, T2.AdmEmail2 FROM frpm AS T1 INNER JOIN schools AS T2 ON T1.CDSCode = T2.CDSCode WHERE T2.County = 'San Bernardino' AND T2.City = 'San Bernardino' AND T2.DOC = 54 AND strftime('%Y', T2.OpenDate) BETWEEN '2009' AND '2010' AND T2.SOC = 62
|
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"/",
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"?"
] |
[
{
"id": 6,
"type": "value",
"value": "San Bernardino"
},
{
"id": 0,
"type": "column",
"value": "admemail1"
},
{
"id": 1,
"type": "column",
"value": "admemail2"
},
{
"id": 15,
"type": "column",
"value": "opendate"
},
{
"id": 3,
"type": "table",
"value": "schools"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 5,
"type": "column",
"value": "county"
},
{
"id": 2,
"type": "table",
"value": "frpm"
},
{
"id": 7,
"type": "column",
"value": "city"
},
{
"id": 10,
"type": "value",
"value": "2009"
},
{
"id": 11,
"type": "value",
"value": "2010"
},
{
"id": 8,
"type": "column",
"value": "doc"
},
{
"id": 12,
"type": "column",
"value": "soc"
},
{
"id": 9,
"type": "value",
"value": "54"
},
{
"id": 13,
"type": "value",
"value": "62"
},
{
"id": 14,
"type": "value",
"value": "%Y"
}
] |
[
{
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},
{
"entity_id": 1,
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3,
4,
5,
6
]
},
{
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{
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28
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{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
2,620
|
epinions_1
|
spider:train_spider.json:1718
|
Find the number of items without any review.
|
SELECT count(*) FROM item WHERE i_id NOT IN (SELECT i_id FROM review)
|
[
"Find",
"the",
"number",
"of",
"items",
"without",
"any",
"review",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "review"
},
{
"id": 0,
"type": "table",
"value": "item"
},
{
"id": 1,
"type": "column",
"value": "i_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
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"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 7,
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},
{
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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",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
2,622
|
financial
|
bird:dev.json:114
|
For the first client who opened his/her account in Prague, what is his/her account ID?
|
SELECT T1.account_id FROM account AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.A3 = 'Prague' ORDER BY T1.date ASC LIMIT 1
|
[
"For",
"the",
"first",
"client",
"who",
"opened",
"his",
"/",
"her",
"account",
"in",
"Prague",
",",
"what",
"is",
"his",
"/",
"her",
"account",
"ID",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "district_id"
},
{
"id": 0,
"type": "column",
"value": "account_id"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 1,
"type": "table",
"value": "account"
},
{
"id": 4,
"type": "value",
"value": "Prague"
},
{
"id": 5,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "a3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18,
19
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"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",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,623
|
shipping
|
bird:train.json:5659
|
In which city did the heaviest shipment transported?
|
SELECT T2.city_name FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id ORDER BY T1.weight DESC LIMIT 1
|
[
"In",
"which",
"city",
"did",
"the",
"heaviest",
"shipment",
"transported",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "city_name"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 4,
"type": "column",
"value": "city_id"
},
{
"id": 3,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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3
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
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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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
2,624
|
hr_1
|
spider:train_spider.json:3450
|
What are the department ids for which more than 10 employees had a commission?
|
SELECT department_id FROM employees GROUP BY department_id HAVING COUNT(commission_pct) > 10
|
[
"What",
"are",
"the",
"department",
"ids",
"for",
"which",
"more",
"than",
"10",
"employees",
"had",
"a",
"commission",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "commission_pct"
},
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"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",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
2,625
|
public_review_platform
|
bird:train.json:3976
|
Among the review votes of funny and cool hit uber with long review length, describe the business ID, active status, user ID and user year of joining Yelp.
|
SELECT T1.business_id, T1.active, T3.user_id, T3.user_yelping_since_year FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id INNER JOIN Users AS T3 ON T2.user_id = T3.user_id WHERE T2.review_votes_cool = 'Uber' AND T2.review_votes_funny = 'Uber' AND T2.review_length = 'Long'
|
[
"Among",
"the",
"review",
"votes",
"of",
"funny",
"and",
"cool",
"hit",
"uber",
"with",
"long",
"review",
"length",
",",
"describe",
"the",
"business",
"ID",
",",
"active",
"status",
",",
"user",
"ID",
"and",
"user",
"year",
"of",
"joining",
"Yelp",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "user_yelping_since_year"
},
{
"id": 9,
"type": "column",
"value": "review_votes_funny"
},
{
"id": 7,
"type": "column",
"value": "review_votes_cool"
},
{
"id": 10,
"type": "column",
"value": "review_length"
},
{
"id": 0,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "table",
"value": "business"
},
{
"id": 2,
"type": "column",
"value": "user_id"
},
{
"id": 6,
"type": "table",
"value": "reviews"
},
{
"id": 1,
"type": "column",
"value": "active"
},
{
"id": 4,
"type": "table",
"value": "users"
},
{
"id": 8,
"type": "value",
"value": "Uber"
},
{
"id": 11,
"type": "value",
"value": "Long"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
24
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
23
]
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
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3
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},
{
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9
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{
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4,
5
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12,
13
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},
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11
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},
{
"entity_id": 12,
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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",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,626
|
movie
|
bird:train.json:732
|
Which actor played the role of Joker in the movie Batman?
|
SELECT T3.Name FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T1.Title = 'Batman' AND T2.`Character Name` = 'Joker'
|
[
"Which",
"actor",
"played",
"the",
"role",
"of",
"Joker",
"in",
"the",
"movie",
"Batman",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "Character Name"
},
{
"id": 3,
"type": "table",
"value": "characters"
},
{
"id": 4,
"type": "column",
"value": "actorid"
},
{
"id": 9,
"type": "column",
"value": "movieid"
},
{
"id": 6,
"type": "value",
"value": "Batman"
},
{
"id": 1,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 5,
"type": "column",
"value": "title"
},
{
"id": 8,
"type": "value",
"value": "Joker"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
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9
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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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6
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},
{
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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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
2,627
|
game_1
|
spider:train_spider.json:6027
|
Show all male student ids who don't play football.
|
SELECT StuID FROM Student WHERE sex = 'M' EXCEPT SELECT StuID FROM Sportsinfo WHERE sportname = "Football"
|
[
"Show",
"all",
"male",
"student",
"ids",
"who",
"do",
"n't",
"play",
"football",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "sportsinfo"
},
{
"id": 5,
"type": "column",
"value": "sportname"
},
{
"id": 6,
"type": "column",
"value": "Football"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 4,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
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},
{
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},
{
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"token_idxs": []
},
{
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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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,628
|
address
|
bird:train.json:5196
|
Which state has the most bad aliases?
|
SELECT T2.state FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.state ORDER BY COUNT(T1.bad_alias) DESC LIMIT 1
|
[
"Which",
"state",
"has",
"the",
"most",
"bad",
"aliases",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "bad_alias"
},
{
"id": 2,
"type": "table",
"value": "zip_data"
},
{
"id": 3,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "table",
"value": "avoid"
}
] |
[
{
"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": [
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-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,629
|
movie_1
|
spider:train_spider.json:2495
|
For each director, how many reviews have they received?
|
SELECT count(*) , T1.director FROM Movie AS T1 JOIN Rating AS T2 ON T1.mID = T2.mID GROUP BY T1.director
|
[
"For",
"each",
"director",
",",
"how",
"many",
"reviews",
"have",
"they",
"received",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "director"
},
{
"id": 2,
"type": "table",
"value": "rating"
},
{
"id": 1,
"type": "table",
"value": "movie"
},
{
"id": 3,
"type": "column",
"value": "mid"
}
] |
[
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,630
|
public_review_platform
|
bird:train.json:3763
|
What kind of "wi-fi" does Yelp business No."10172" have?
|
SELECT T2.attribute_value FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T2.business_id = 10172 AND T1.attribute_name LIKE 'wi-fi'
|
[
"What",
"kind",
"of",
"\"",
"wi",
"-",
"fi",
"\"",
"does",
"Yelp",
"business",
"No",
".",
"\"10172",
"\"",
"have",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "business_attributes"
},
{
"id": 0,
"type": "column",
"value": "attribute_value"
},
{
"id": 6,
"type": "column",
"value": "attribute_name"
},
{
"id": 3,
"type": "column",
"value": "attribute_id"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "attributes"
},
{
"id": 5,
"type": "value",
"value": "10172"
},
{
"id": 7,
"type": "value",
"value": "wi-fi"
}
] |
[
{
"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": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
4,
5,
6
]
},
{
"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-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
2,631
|
movie_platform
|
bird:train.json:79
|
What's of rating on the movie "Innocence Unprotected" by the user who created the movie list "250 Favourite Films"?
|
SELECT T1.rating_score FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id INNER JOIN lists AS T3 ON T3.user_id = T1.user_id WHERE T2.movie_title = 'Innocence Unprotected' AND T3.list_title = '250 Favourite Films'
|
[
"What",
"'s",
"of",
"rating",
"on",
"the",
"movie",
"\"",
"Innocence",
"Unprotected",
"\"",
"by",
"the",
"user",
"who",
"created",
"the",
"movie",
"list",
"\"",
"250",
"Favourite",
"Films",
"\"",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Innocence Unprotected"
},
{
"id": 8,
"type": "value",
"value": "250 Favourite Films"
},
{
"id": 0,
"type": "column",
"value": "rating_score"
},
{
"id": 5,
"type": "column",
"value": "movie_title"
},
{
"id": 7,
"type": "column",
"value": "list_title"
},
{
"id": 9,
"type": "column",
"value": "movie_id"
},
{
"id": 2,
"type": "table",
"value": "ratings"
},
{
"id": 4,
"type": "column",
"value": "user_id"
},
{
"id": 3,
"type": "table",
"value": "movies"
},
{
"id": 1,
"type": "table",
"value": "lists"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8,
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
20,
21,
22
]
},
{
"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",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,632
|
student_loan
|
bird:train.json:4561
|
Which organization has the least number of male students?
|
SELECT T.organ FROM ( SELECT T2.organ, COUNT(T1.name) AS num FROM male AS T1 INNER JOIN enlist AS T2 ON T1.name = T2.name GROUP BY T2.organ ) T ORDER BY T.num LIMIT 1
|
[
"Which",
"organization",
"has",
"the",
"least",
"number",
"of",
"male",
"students",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "enlist"
},
{
"id": 0,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "table",
"value": "male"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
2,633
|
movielens
|
bird:train.json:2331
|
Calculate the percentage of female actors and quality 2 who have appeared twice at the casting of the film 1672580.
|
SELECT CAST(SUM(IIF(T2.cast_num = 2 AND T1.a_quality = 2, 1, 0)) AS REAL) * 100 / COUNT(T1.actorid) FROM actors AS T1 INNER JOIN movies2actors AS T2 ON T1.actorid = T2.actorid WHERE T2.movieid = 1672580 AND T1.a_gender = 'F'
|
[
"Calculate",
"the",
"percentage",
"of",
"female",
"actors",
"and",
"quality",
"2",
"who",
"have",
"appeared",
"twice",
"at",
"the",
"casting",
"of",
"the",
"film",
"1672580",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "movies2actors"
},
{
"id": 12,
"type": "column",
"value": "a_quality"
},
{
"id": 5,
"type": "column",
"value": "a_gender"
},
{
"id": 10,
"type": "column",
"value": "cast_num"
},
{
"id": 2,
"type": "column",
"value": "actorid"
},
{
"id": 3,
"type": "column",
"value": "movieid"
},
{
"id": 4,
"type": "value",
"value": "1672580"
},
{
"id": 0,
"type": "table",
"value": "actors"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "F"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "0"
},
{
"id": 11,
"type": "value",
"value": "2"
}
] |
[
{
"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": [
19
]
},
{
"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": [
15
]
},
{
"entity_id": 11,
"token_idxs": [
8
]
},
{
"entity_id": 12,
"token_idxs": [
7
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
2,634
|
student_loan
|
bird:train.json:4506
|
List out student names that enrolled in two schools and two organizations?
|
SELECT T.name FROM ( SELECT T1.name, COUNT(T1.organ) AS num FROM enlist AS T1 INNER JOIN enrolled AS T2 ON T1.name = T2.name GROUP BY T1.name ) T WHERE T.num = 2
|
[
"List",
"out",
"student",
"names",
"that",
"enrolled",
"in",
"two",
"schools",
"and",
"two",
"organizations",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "enrolled"
},
{
"id": 3,
"type": "table",
"value": "enlist"
},
{
"id": 5,
"type": "column",
"value": "organ"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
0
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,635
|
wedding
|
spider:train_spider.json:1641
|
Show the name and age for all male people who don't have a wedding.
|
SELECT name , age FROM people WHERE is_male = 'T' AND people_id NOT IN (SELECT male_id FROM wedding)
|
[
"Show",
"the",
"name",
"and",
"age",
"for",
"all",
"male",
"people",
"who",
"do",
"n't",
"have",
"a",
"wedding",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "people_id"
},
{
"id": 3,
"type": "column",
"value": "is_male"
},
{
"id": 6,
"type": "table",
"value": "wedding"
},
{
"id": 7,
"type": "column",
"value": "male_id"
},
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "value",
"value": "T"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,636
|
retail_complains
|
bird:train.json:333
|
What is the address of the client who made a complaint via postal mail on March 14, 2012?
|
SELECT T1.address_1, T1.address_2 FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Date received` = '2012-03-14' AND T2.`Submitted via` = 'Postal mail'
|
[
"What",
"is",
"the",
"address",
"of",
"the",
"client",
"who",
"made",
"a",
"complaint",
"via",
"postal",
"mail",
"on",
"March",
"14",
",",
"2012",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Date received"
},
{
"id": 7,
"type": "column",
"value": "Submitted via"
},
{
"id": 8,
"type": "value",
"value": "Postal mail"
},
{
"id": 6,
"type": "value",
"value": "2012-03-14"
},
{
"id": 0,
"type": "column",
"value": "address_1"
},
{
"id": 1,
"type": "column",
"value": "address_2"
},
{
"id": 4,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "table",
"value": "client"
},
{
"id": 3,
"type": "table",
"value": "events"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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": [
12,
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,637
|
match_season
|
spider:train_spider.json:1102
|
Show the name of colleges that have at least two players in descending alphabetical order.
|
SELECT College FROM match_season GROUP BY College HAVING count(*) >= 2 ORDER BY College DESC
|
[
"Show",
"the",
"name",
"of",
"colleges",
"that",
"have",
"at",
"least",
"two",
"players",
"in",
"descending",
"alphabetical",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "match_season"
},
{
"id": 1,
"type": "column",
"value": "college"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,638
|
address
|
bird:train.json:5180
|
List all the locations of postal points with the area code "410".
|
SELECT T2.latitude, T2.longitude FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 410
|
[
"List",
"all",
"the",
"locations",
"of",
"postal",
"points",
"with",
"the",
"area",
"code",
"\"",
"410",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "longitude"
},
{
"id": 2,
"type": "table",
"value": "area_code"
},
{
"id": 4,
"type": "column",
"value": "area_code"
},
{
"id": 0,
"type": "column",
"value": "latitude"
},
{
"id": 3,
"type": "table",
"value": "zip_data"
},
{
"id": 6,
"type": "column",
"value": "zip_code"
},
{
"id": 5,
"type": "value",
"value": "410"
}
] |
[
{
"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": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
2,639
|
manufacturer
|
spider:train_spider.json:3401
|
Find the number of funiture types produced by each manufacturer as well as the company names.
|
SELECT count(*) , t1.name FROM manufacturer AS t1 JOIN furniture_manufacte AS t2 ON t1.manufacturer_id = t2.manufacturer_id GROUP BY t1.manufacturer_id
|
[
"Find",
"the",
"number",
"of",
"funiture",
"types",
"produced",
"by",
"each",
"manufacturer",
"as",
"well",
"as",
"the",
"company",
"names",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "furniture_manufacte"
},
{
"id": 0,
"type": "column",
"value": "manufacturer_id"
},
{
"id": 2,
"type": "table",
"value": "manufacturer"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,640
|
train_station
|
spider:train_spider.json:6608
|
Show the location with most number of train stations.
|
SELECT LOCATION FROM station GROUP BY LOCATION ORDER BY count(*) DESC LIMIT 1
|
[
"Show",
"the",
"location",
"with",
"most",
"number",
"of",
"train",
"stations",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "station"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"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",
"O",
"B-TABLE",
"O"
] |
2,641
|
bakery_1
|
bird:test.json:1537
|
Which good has "70" in its id? And what is its price?
|
SELECT id , price FROM goods WHERE id LIKE "%70%"
|
[
"Which",
"good",
"has",
"\"",
"70",
"\"",
"in",
"its",
"i",
"d",
"?",
"And",
"what",
"is",
"its",
"price",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "column",
"value": "%70%"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,642
|
mondial_geo
|
bird:train.json:8341
|
Name the river at Little Rock city. State the length of the river.
|
SELECT T3.Length FROM city AS T1 INNER JOIN located AS T2 ON T1.Name = T2.City INNER JOIN river AS T3 ON T3.Name = T2.River WHERE T1.Name = 'Little Rock'
|
[
"Name",
"the",
"river",
"at",
"Little",
"Rock",
"city",
".",
"State",
"the",
"length",
"of",
"the",
"river",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Little Rock"
},
{
"id": 5,
"type": "table",
"value": "located"
},
{
"id": 0,
"type": "column",
"value": "length"
},
{
"id": 1,
"type": "table",
"value": "river"
},
{
"id": 6,
"type": "column",
"value": "river"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "table",
"value": "city"
},
{
"id": 7,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,643
|
formula_1
|
bird:dev.json:955
|
What is the average time in seconds of champion for each year, before year 1975?
|
WITH time_in_seconds AS ( SELECT T2.year, T2.raceId, T1.positionOrder, CASE WHEN T1.positionOrder = 1 THEN (CAST(SUBSTR(T1.time, 1, 1) AS REAL) * 3600) + (CAST(SUBSTR(T1.time, 3, 2) AS REAL) * 60) + CAST(SUBSTR(T1.time, 6,2) AS REAL ) + CAST(SUBSTR(T1.time, 9) AS REAL)/1000 ELSE 0 END AS time_seconds FROM results AS T1 INNER JOIN races AS T2 ON T1.raceId = T2.raceId WHERE T1.time IS NOT NULL ), champion_time AS ( SELECT year, raceId, time_seconds FROM time_in_seconds WHERE positionOrder = 1 ) SELECT year, AVG(time_seconds) FROM champion_time WHERE year < 1975 GROUP BY year HAVING AVG(time_seconds) IS NOT NULL
|
[
"What",
"is",
"the",
"average",
"time",
"in",
"seconds",
"of",
"champion",
"for",
"each",
"year",
",",
"before",
"year",
"1975",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "time_in_seconds"
},
{
"id": 0,
"type": "table",
"value": "champion_time"
},
{
"id": 6,
"type": "column",
"value": "positionorder"
},
{
"id": 3,
"type": "column",
"value": "time_seconds"
},
{
"id": 7,
"type": "table",
"value": "results"
},
{
"id": 5,
"type": "column",
"value": "raceid"
},
{
"id": 8,
"type": "table",
"value": "races"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "1975"
},
{
"id": 9,
"type": "column",
"value": "time"
},
{
"id": 12,
"type": "value",
"value": "1000"
},
{
"id": 13,
"type": "value",
"value": "3600"
},
{
"id": 14,
"type": "value",
"value": "60"
},
{
"id": 10,
"type": "value",
"value": "1"
},
{
"id": 11,
"type": "value",
"value": "0"
},
{
"id": 15,
"type": "value",
"value": "6"
},
{
"id": 16,
"type": "value",
"value": "2"
},
{
"id": 17,
"type": "value",
"value": "9"
},
{
"id": 18,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"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": [
4
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,644
|
chinook_1
|
spider:train_spider.json:870
|
What are the first names and support rep ids for employees serving 10 or more customers?
|
SELECT T1.FirstName , T1.SupportRepId FROM CUSTOMER AS T1 JOIN EMPLOYEE AS T2 ON T1.SupportRepId = T2.EmployeeId GROUP BY T1.SupportRepId HAVING COUNT(*) >= 10
|
[
"What",
"are",
"the",
"first",
"names",
"and",
"support",
"rep",
"ids",
"for",
"employees",
"serving",
"10",
"or",
"more",
"customers",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "supportrepid"
},
{
"id": 5,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
2,645
|
world_development_indicators
|
bird:train.json:2188
|
What country have its data estimated based on regression?
|
SELECT DISTINCT T1.ShortName FROM Country AS T1 INNER JOIN CountryNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T2.Description = 'Estimates are based on regression.'
|
[
"What",
"country",
"have",
"its",
"data",
"estimated",
"based",
"on",
"regression",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Estimates are based on regression."
},
{
"id": 2,
"type": "table",
"value": "countrynotes"
},
{
"id": 3,
"type": "column",
"value": "description"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 0,
"type": "column",
"value": "shortname"
},
{
"id": 1,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6,
7,
8
]
},
{
"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-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,648
|
flight_4
|
spider:train_spider.json:6830
|
What is the name, city, and country of the airport with the lowest altitude?
|
SELECT name , city , country FROM airports ORDER BY elevation LIMIT 1
|
[
"What",
"is",
"the",
"name",
",",
"city",
",",
"and",
"country",
"of",
"the",
"airport",
"with",
"the",
"lowest",
"altitude",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "elevation"
},
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,649
|
food_inspection_2
|
bird:train.json:6177
|
List the point IDs and fines of the inspections done on 7th August 2010.
|
SELECT T2.point_id, T2.fine FROM inspection AS T1 INNER JOIN violation AS T2 ON T1.inspection_id = T2.inspection_id WHERE T1.inspection_date = '2010-08-07'
|
[
"List",
"the",
"point",
"IDs",
"and",
"fines",
"of",
"the",
"inspections",
"done",
"on",
"7th",
"August",
"2010",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "inspection_date"
},
{
"id": 6,
"type": "column",
"value": "inspection_id"
},
{
"id": 2,
"type": "table",
"value": "inspection"
},
{
"id": 5,
"type": "value",
"value": "2010-08-07"
},
{
"id": 3,
"type": "table",
"value": "violation"
},
{
"id": 0,
"type": "column",
"value": "point_id"
},
{
"id": 1,
"type": "column",
"value": "fine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
2,650
|
image_and_language
|
bird:train.json:7558
|
Name number of samples of "bed" object are there in the image No.1098?
|
SELECT SUM(CASE WHEN T2.OBJ_CLASS = 'bed' THEN 1 ELSE 0 END) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 1098
|
[
"Name",
"number",
"of",
"samples",
"of",
"\"",
"bed",
"\"",
"object",
"are",
"there",
"in",
"the",
"image",
"No.1098",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "obj_class_id"
},
{
"id": 1,
"type": "table",
"value": "obj_classes"
},
{
"id": 7,
"type": "column",
"value": "obj_class"
},
{
"id": 0,
"type": "table",
"value": "img_obj"
},
{
"id": 2,
"type": "column",
"value": "img_id"
},
{
"id": 3,
"type": "value",
"value": "1098"
},
{
"id": 8,
"type": "value",
"value": "bed"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"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": [
6
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,651
|
club_1
|
spider:train_spider.json:4268
|
Find the number of clubs where "Tracy Kim" is a member.
|
SELECT count(*) 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 t3.fname = "Tracy" AND t3.lname = "Kim"
|
[
"Find",
"the",
"number",
"of",
"clubs",
"where",
"\"",
"Tracy",
"Kim",
"\"",
"is",
"a",
"member",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "member_of_club"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "column",
"value": "clubid"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 4,
"type": "column",
"value": "fname"
},
{
"id": 5,
"type": "column",
"value": "Tracy"
},
{
"id": 6,
"type": "column",
"value": "lname"
},
{
"id": 1,
"type": "table",
"value": "club"
},
{
"id": 7,
"type": "column",
"value": "Kim"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
2,
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"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",
"I-TABLE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
2,652
|
movie_3
|
bird:train.json:9352
|
List down all of the customers' first name who were attended by staff with ID 1.
|
SELECT DISTINCT T1.first_name, T1.last_name FROM customer AS T1 INNER JOIN rental AS T2 ON T1.customer_id = T2.customer_id WHERE T2.staff_id = 1
|
[
"List",
"down",
"all",
"of",
"the",
"customers",
"'",
"first",
"name",
"who",
"were",
"attended",
"by",
"staff",
"with",
"ID",
"1",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 4,
"type": "column",
"value": "staff_id"
},
{
"id": 3,
"type": "table",
"value": "rental"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,653
|
simpson_episodes
|
bird:train.json:4289
|
How many 1 star ratings are there in the worst rated episode of the season?
|
SELECT COUNT(*) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T2.stars = 1 ORDER BY T1.rating LIMIT 1;
|
[
"How",
"many",
"1",
"star",
"ratings",
"are",
"there",
"in",
"the",
"worst",
"rated",
"episode",
"of",
"the",
"season",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "table",
"value": "episode"
},
{
"id": 4,
"type": "column",
"value": "rating"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 1,
"type": "table",
"value": "vote"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
12,
13
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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{
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},
{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
2,654
|
hr_1
|
spider:train_spider.json:3473
|
Find the first name and last name and department id for those employees who earn such amount of salary which is the smallest salary of any of the departments.
|
SELECT first_name , last_name , department_id FROM employees WHERE salary IN (SELECT MIN(salary) FROM employees GROUP BY department_id)
|
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"salary",
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"the",
"departments",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "department_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "column",
"value": "salary"
}
] |
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[
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"O",
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"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,655
|
bike_share_1
|
bird:train.json:9060
|
What is the difference between the hottest temperature and the coldest temperature in in Fahrenheit on 8/29/2013 for the area where the zip code is 94107?
|
SELECT SUM(IIF(zip_code = 94107 AND date = '8/29/2013', max_temperature_f - min_temperature_f, 0)) FROM weather
|
[
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"for",
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"area",
"where",
"the",
"zip",
"code",
"is",
"94107",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "max_temperature_f"
},
{
"id": 3,
"type": "column",
"value": "min_temperature_f"
},
{
"id": 7,
"type": "value",
"value": "8/29/2013"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 5,
"type": "value",
"value": "94107"
},
{
"id": 6,
"type": "column",
"value": "date"
},
{
"id": 1,
"type": "value",
"value": "0"
}
] |
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[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
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"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,656
|
swimming
|
spider:train_spider.json:5613
|
Which countries do not have a stadium that was opened after 2006?
|
SELECT country FROM stadium EXCEPT SELECT country FROM stadium WHERE opening_year > 2006
|
[
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"do",
"not",
"have",
"a",
"stadium",
"that",
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"opened",
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"2006",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "opening_year"
},
{
"id": 0,
"type": "table",
"value": "stadium"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "value",
"value": "2006"
}
] |
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"token_idxs": []
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
2,657
|
soccer_1
|
spider:train_spider.json:1305
|
Who are the top 3 players in terms of overall rating?
|
SELECT DISTINCT T1.player_name FROM Player AS T1 JOIN Player_Attributes AS T2 ON T1.player_api_id = T2.player_api_id ORDER BY overall_rating DESC LIMIT 3
|
[
"Who",
"are",
"the",
"top",
"3",
"players",
"in",
"terms",
"of",
"overall",
"rating",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "player_attributes"
},
{
"id": 3,
"type": "column",
"value": "overall_rating"
},
{
"id": 4,
"type": "column",
"value": "player_api_id"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 1,
"type": "table",
"value": "player"
}
] |
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,658
|
sales
|
bird:train.json:5400
|
What is the average number of customers per sales person?
|
SELECT CAST(COUNT(T1.CustomerID) AS REAL) / COUNT(T3.EmployeeID) FROM Customers AS T1 INNER JOIN Sales AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN Employees AS T3 ON T2.SalesPersonID = T3.EmployeeID
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"customers",
"per",
"sales",
"person",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "salespersonid"
},
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "sales"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
2,659
|
book_publishing_company
|
bird:train.json:214
|
Which type of book had the most pre-paid amount?
|
SELECT type FROM titles ORDER BY advance DESC LIMIT 1
|
[
"Which",
"type",
"of",
"book",
"had",
"the",
"most",
"pre",
"-",
"paid",
"amount",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "advance"
},
{
"id": 0,
"type": "table",
"value": "titles"
},
{
"id": 1,
"type": "column",
"value": "type"
}
] |
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},
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1
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{
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{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,660
|
party_people
|
spider:train_spider.json:2073
|
Show all member names who are not in charge of any event.
|
SELECT member_name FROM member EXCEPT SELECT T1.member_name FROM member AS T1 JOIN party_events AS T2 ON T1.member_id = T2.member_in_charge_id
|
[
"Show",
"all",
"member",
"names",
"who",
"are",
"not",
"in",
"charge",
"of",
"any",
"event",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "member_in_charge_id"
},
{
"id": 2,
"type": "table",
"value": "party_events"
},
{
"id": 1,
"type": "column",
"value": "member_name"
},
{
"id": 3,
"type": "column",
"value": "member_id"
},
{
"id": 0,
"type": "table",
"value": "member"
}
] |
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3
]
},
{
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10,
11
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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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"token_idxs": []
},
{
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},
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"token_idxs": []
},
{
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"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,661
|
soccer_2
|
spider:train_spider.json:5010
|
Find the average and maximum hours for the students whose tryout decision is yes.
|
SELECT avg(T1.HS) , max(T1.HS) FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes'
|
[
"Find",
"the",
"average",
"and",
"maximum",
"hours",
"for",
"the",
"students",
"whose",
"tryout",
"decision",
"is",
"yes",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "decision"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "table",
"value": "tryout"
},
{
"id": 3,
"type": "value",
"value": "yes"
},
{
"id": 5,
"type": "column",
"value": "pid"
},
{
"id": 4,
"type": "column",
"value": "hs"
}
] |
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10
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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": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,663
|
movie_3
|
bird:train.json:9194
|
List the names of the customers from India.
|
SELECT T4.first_name, T4.last_name FROM country AS T1 INNER JOIN city AS T2 ON T1.country_id = T2.country_id INNER JOIN address AS T3 ON T2.city_id = T3.city_id INNER JOIN customer AS T4 ON T3.address_id = T4.address_id WHERE T1.country = 'India'
|
[
"List",
"the",
"names",
"of",
"the",
"customers",
"from",
"India",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "address_id"
},
{
"id": 10,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "table",
"value": "address"
},
{
"id": 7,
"type": "table",
"value": "country"
},
{
"id": 9,
"type": "column",
"value": "city_id"
},
{
"id": 4,
"type": "value",
"value": "India"
},
{
"id": 8,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0,
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,665
|
car_racing
|
bird:test.json:1594
|
How many drivers receive points greater than 150 for each make? Show the make and the count.
|
SELECT make , count(*) FROM driver WHERE points > 150 GROUP BY make
|
[
"How",
"many",
"drivers",
"receive",
"points",
"greater",
"than",
"150",
"for",
"each",
"make",
"?",
"Show",
"the",
"make",
"and",
"the",
"count",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 2,
"type": "column",
"value": "points"
},
{
"id": 1,
"type": "column",
"value": "make"
},
{
"id": 3,
"type": "value",
"value": "150"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,666
|
donor
|
bird:train.json:3154
|
Name the project titles created by teacher who acquired a doctor degree.
|
SELECT T1.title FROM essays AS T1 INNER JOIN donations AS T2 ON T1.projectid = T2.projectid WHERE T2.donation_message LIKE 'Donation on behalf of Matt Carpenter because I''m a strong believer in education.'
|
[
"Name",
"the",
"project",
"titles",
"created",
"by",
"teacher",
"who",
"acquired",
"a",
"doctor",
"degree",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Donation on behalf of Matt Carpenter because I'm a strong believer in education."
},
{
"id": 3,
"type": "column",
"value": "donation_message"
},
{
"id": 2,
"type": "table",
"value": "donations"
},
{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 1,
"type": "table",
"value": "essays"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"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": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,667
|
mondial_geo
|
bird:train.json:8294
|
How many more people speak English than speak Scottish in United Kingdom?
|
SELECT T3.Population * (T2.Percentage - T1.Percentage) FROM ethnicGroup AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Country = T2.Country INNER JOIN country AS T3 ON T1.Country = T3.Code WHERE T1.Name = 'Scottish' AND T2.Name = 'English' AND T3.Name = 'United Kingdom'
|
[
"How",
"many",
"more",
"people",
"speak",
"English",
"than",
"speak",
"Scottish",
"in",
"United",
"Kingdom",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "United Kingdom"
},
{
"id": 2,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 1,
"type": "column",
"value": "population"
},
{
"id": 9,
"type": "column",
"value": "percentage"
},
{
"id": 6,
"type": "value",
"value": "Scottish"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 7,
"type": "value",
"value": "English"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
[
{
"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": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": [
10,
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,668
|
cookbook
|
bird:train.json:8866
|
Which recipe is more beneficial in wound healing, "Raspberry Chiffon Pie" or "Fresh Apricot Bavarian"?
|
SELECT DISTINCT CASE WHEN CASE WHEN T2.title = 'Raspberry Chiffon Pie' THEN T1.vitamin_c END > CASE WHEN T2.title = 'Fresh Apricot Bavarian' THEN T1.vitamin_c END THEN 'Raspberry Chiffon Pie' ELSE 'Fresh Apricot Bavarian' END AS "vitamin_c is higher" FROM Nutrition T1 INNER JOIN Recipe T2 ON T2.recipe_id = T1.recipe_id
|
[
"Which",
"recipe",
"is",
"more",
"beneficial",
"in",
"wound",
"healing",
",",
"\"",
"Raspberry",
"Chiffon",
"Pie",
"\"",
"or",
"\"",
"Fresh",
"Apricot",
"Bavarian",
"\"",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Fresh Apricot Bavarian"
},
{
"id": 4,
"type": "value",
"value": "Raspberry Chiffon Pie"
},
{
"id": 0,
"type": "table",
"value": "nutrition"
},
{
"id": 3,
"type": "column",
"value": "recipe_id"
},
{
"id": 5,
"type": "column",
"value": "vitamin_c"
},
{
"id": 1,
"type": "table",
"value": "recipe"
},
{
"id": 6,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
16,
17,
18
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,669
|
olympics
|
bird:train.json:5049
|
What is the name of the oldest competitor?
|
SELECT T1.full_name FROM person AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.person_id ORDER BY T2.age DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"oldest",
"competitor",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "games_competitor"
},
{
"id": 0,
"type": "column",
"value": "full_name"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,670
|
movie_platform
|
bird:train.json:106
|
What is the average score for the movie Versailles Rive-Gauche?
|
SELECT AVG(T1.rating_score) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title LIKE 'Versailles Rive-Gauche'
|
[
"What",
"is",
"the",
"average",
"score",
"for",
"the",
"movie",
"Versailles",
"Rive",
"-",
"Gauche",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Versailles Rive-Gauche"
},
{
"id": 4,
"type": "column",
"value": "rating_score"
},
{
"id": 2,
"type": "column",
"value": "movie_title"
},
{
"id": 5,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "ratings"
},
{
"id": 1,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
3,
4
]
},
{
"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",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,671
|
software_company
|
bird:train.json:8538
|
What is the geographic identifier and income of the oldest customer?
|
SELECT T1.GEOID, T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T1.age DESC LIMIT 1
|
[
"What",
"is",
"the",
"geographic",
"identifier",
"and",
"income",
"of",
"the",
"oldest",
"customer",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "income_k"
},
{
"id": 0,
"type": "column",
"value": "geoid"
},
{
"id": 3,
"type": "table",
"value": "demog"
},
{
"id": 4,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"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",
"B-TABLE",
"O"
] |
2,672
|
election
|
spider:train_spider.json:2789
|
Which party has two or more records?
|
SELECT Party FROM party GROUP BY Party HAVING COUNT(*) >= 2
|
[
"Which",
"party",
"has",
"two",
"or",
"more",
"records",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "party"
},
{
"id": 1,
"type": "column",
"value": "party"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
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},
{
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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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},
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},
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},
{
"entity_id": 10,
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},
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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,
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,673
|
video_games
|
bird:train.json:3404
|
What is the genre of the game "Mario vs. Donkey Kong"?
|
SELECT T1.genre_name FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id WHERE T2.game_name = 'Mario vs. Donkey Kong'
|
[
"What",
"is",
"the",
"genre",
"of",
"the",
"game",
"\"",
"Mario",
"vs.",
"Donkey",
"Kong",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Mario vs. Donkey Kong"
},
{
"id": 0,
"type": "column",
"value": "genre_name"
},
{
"id": 3,
"type": "column",
"value": "game_name"
},
{
"id": 6,
"type": "column",
"value": "genre_id"
},
{
"id": 1,
"type": "table",
"value": "genre"
},
{
"id": 2,
"type": "table",
"value": "game"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
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{
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{
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{
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"token_idxs": []
},
{
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},
{
"entity_id": 15,
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},
{
"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",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,674
|
shipping
|
bird:train.json:5639
|
What is the average annual revenue of customers who have shipment weight of less than 65000 pounds?
|
SELECT AVG(T1.annual_revenue) FROM customer AS T1 INNER JOIN shipment AS T2 ON T1.cust_id = T2.cust_id WHERE T2.weight < 65000
|
[
"What",
"is",
"the",
"average",
"annual",
"revenue",
"of",
"customers",
"who",
"have",
"shipment",
"weight",
"of",
"less",
"than",
"65000",
"pounds",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "annual_revenue"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 5,
"type": "column",
"value": "cust_id"
},
{
"id": 2,
"type": "column",
"value": "weight"
},
{
"id": 3,
"type": "value",
"value": "65000"
}
] |
[
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"entity_id": 0,
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]
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]
},
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]
},
{
"entity_id": 4,
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4,
5
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},
{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
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"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,675
|
tracking_grants_for_research
|
spider:train_spider.json:4357
|
What are the details and id of the project with the most outcomes?
|
SELECT T1.project_details , T1.project_id FROM Projects AS T1 JOIN Project_outcomes AS T2 ON T1.project_id = T2.project_id GROUP BY T1.project_id ORDER BY count(*) DESC LIMIT 1
|
[
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"are",
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"details",
"and",
"i",
"d",
"of",
"the",
"project",
"with",
"the",
"most",
"outcomes",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "project_outcomes"
},
{
"id": 1,
"type": "column",
"value": "project_details"
},
{
"id": 0,
"type": "column",
"value": "project_id"
},
{
"id": 2,
"type": "table",
"value": "projects"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2,
3
]
},
{
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]
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{
"entity_id": 3,
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12,
13
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{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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{
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},
{
"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-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,676
|
mondial_geo
|
bird:train.json:8382
|
How much sea is around the island where Kerinci Mountain is located?
|
SELECT COUNT(T4.Sea) FROM mountain AS T1 INNER JOIN mountainOnIsland AS T2 ON T1.Name = T2.Mountain INNER JOIN island AS T3 ON T3.Name = T2.Island INNER JOIN islandIn AS T4 ON T4.Island = T3.Name WHERE T1.Name = 'Kerinci'
|
[
"How",
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"sea",
"is",
"around",
"the",
"island",
"where",
"Kerinci",
"Mountain",
"is",
"located",
"?"
] |
[
{
"id": 7,
"type": "table",
"value": "mountainonisland"
},
{
"id": 0,
"type": "table",
"value": "islandin"
},
{
"id": 6,
"type": "table",
"value": "mountain"
},
{
"id": 8,
"type": "column",
"value": "mountain"
},
{
"id": 2,
"type": "value",
"value": "Kerinci"
},
{
"id": 4,
"type": "table",
"value": "island"
},
{
"id": 5,
"type": "column",
"value": "island"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "sea"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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8
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{
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2
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{
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{
"entity_id": 5,
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6
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{
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{
"entity_id": 7,
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10
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},
{
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9
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{
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},
{
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},
{
"entity_id": 11,
"token_idxs": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O"
] |
2,678
|
retails
|
bird:train.json:6757
|
Provide the nation and region of the customer with the address of wH55UnX7 VI?
|
SELECT T1.n_name, T3.r_name FROM nation AS T1 INNER JOIN customer AS T2 ON T1.n_nationkey = T2.c_nationkey INNER JOIN region AS T3 ON T1.n_regionkey = T3.r_regionkey WHERE T2.c_address = 'wH55UnX7 VI'
|
[
"Provide",
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"nation",
"and",
"region",
"of",
"the",
"customer",
"with",
"the",
"address",
"of",
"wH55UnX7",
"VI",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "wH55UnX7 VI"
},
{
"id": 7,
"type": "column",
"value": "n_regionkey"
},
{
"id": 8,
"type": "column",
"value": "r_regionkey"
},
{
"id": 9,
"type": "column",
"value": "n_nationkey"
},
{
"id": 10,
"type": "column",
"value": "c_nationkey"
},
{
"id": 3,
"type": "column",
"value": "c_address"
},
{
"id": 6,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "n_name"
},
{
"id": 1,
"type": "column",
"value": "r_name"
},
{
"id": 2,
"type": "table",
"value": "region"
},
{
"id": 5,
"type": "table",
"value": "nation"
}
] |
[
{
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"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
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7
]
},
{
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},
{
"entity_id": 8,
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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",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,679
|
retail_world
|
bird:train.json:6525
|
How many territories are there in the region with the highest number of territories?
|
SELECT COUNT(T2.RegionDescription), T1.TerritoryDescription, COUNT(*) AS num FROM Territories AS T1 INNER JOIN Region AS T2 ON T1.RegionID = T2.RegionID GROUP BY T1.TerritoryDescription ORDER BY num DESC LIMIT 1
|
[
"How",
"many",
"territories",
"are",
"there",
"in",
"the",
"region",
"with",
"the",
"highest",
"number",
"of",
"territories",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "territorydescription"
},
{
"id": 4,
"type": "column",
"value": "regiondescription"
},
{
"id": 1,
"type": "table",
"value": "territories"
},
{
"id": 5,
"type": "column",
"value": "regionid"
},
{
"id": 2,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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13
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
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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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"token_idxs": []
},
{
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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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
2,680
|
works_cycles
|
bird:train.json:7241
|
List all the sales people in the Northwest US.
|
SELECT T2.BusinessEntityID FROM SalesTerritory AS T1 INNER JOIN SalesPerson AS T2 ON T1.TerritoryID = T2.TerritoryID WHERE T1.Name = 'Northwest' AND T1.CountryRegionCode = 'US'
|
[
"List",
"all",
"the",
"sales",
"people",
"in",
"the",
"Northwest",
"US",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "countryregioncode"
},
{
"id": 0,
"type": "column",
"value": "businessentityid"
},
{
"id": 1,
"type": "table",
"value": "salesterritory"
},
{
"id": 2,
"type": "table",
"value": "salesperson"
},
{
"id": 3,
"type": "column",
"value": "territoryid"
},
{
"id": 5,
"type": "value",
"value": "Northwest"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "value",
"value": "US"
}
] |
[
{
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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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8
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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,
"token_idxs": []
},
{
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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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
2,681
|
retail_world
|
bird:train.json:6387
|
Calculate the average price of products shipped to the UK.
|
SELECT AVG(UnitPrice) AS avg FROM Invoices WHERE Country = 'UK'
|
[
"Calculate",
"the",
"average",
"price",
"of",
"products",
"shipped",
"to",
"the",
"UK",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "unitprice"
},
{
"id": 0,
"type": "table",
"value": "invoices"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "UK"
}
] |
[
{
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},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,682
|
match_season
|
spider:train_spider.json:1085
|
Return the positions of players on the team Ryley Goldner.
|
SELECT T1.Position FROM match_season AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id WHERE T2.Name = "Ryley Goldner"
|
[
"Return",
"the",
"positions",
"of",
"players",
"on",
"the",
"team",
"Ryley",
"Goldner",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "Ryley Goldner"
},
{
"id": 1,
"type": "table",
"value": "match_season"
},
{
"id": 0,
"type": "column",
"value": "position"
},
{
"id": 6,
"type": "column",
"value": "team_id"
},
{
"id": 2,
"type": "table",
"value": "team"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "team"
}
] |
[
{
"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": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,683
|
address
|
bird:train.json:5096
|
What is the area code of the city with the female median age over 32 years old?
|
SELECT T1.area_code FROM area_code AS T1 INNER JOIN ZIP_Data AS T2 ON T1.zip_code = T2.zip_code WHERE T2.female_median_age > 32 GROUP BY T1.area_code
|
[
"What",
"is",
"the",
"area",
"code",
"of",
"the",
"city",
"with",
"the",
"female",
"median",
"age",
"over",
"32",
"years",
"old",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "female_median_age"
},
{
"id": 0,
"type": "column",
"value": "area_code"
},
{
"id": 1,
"type": "table",
"value": "area_code"
},
{
"id": 2,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "zip_code"
},
{
"id": 4,
"type": "value",
"value": "32"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
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