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15,421
|
financial
|
bird:dev.json:93
|
How many male customers who are living in North Bohemia have average salary greater than 8000?
|
SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.gender = 'M' AND T2.A3 = 'north Bohemia' AND T2.A11 > 8000
|
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"value": "M"
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"O",
"B-VALUE",
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15,422
|
ice_hockey_draft
|
bird:train.json:6949
|
Among all players drafted by the Toronto Maple Leafs, identify the percentage who are from Eastern Europe.
|
SELECT CAST(COUNT(CASE WHEN nation IN ('Belarus', 'Czech Rep.', 'Slovakia', 'Ukraine') THEN ELITEID ELSE NULL END) AS REAL) * 100 / COUNT(ELITEID) FROM PlayerInfo WHERE overallby = 'Toronto Maple Leafs'
|
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"value": "nation"
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"O",
"O",
"O",
"O",
"O",
"O",
"O"
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15,423
|
retails
|
bird:train.json:6881
|
Please list the order keys of all the orders that have more than 2 parts with a jumbo case container.
|
SELECT T.l_orderkey FROM ( SELECT T2.l_orderkey, COUNT(T2.l_partkey) AS num FROM part AS T1 INNER JOIN lineitem AS T2 ON T1.p_partkey = T2.l_partkey WHERE T1.p_container = 'JUMBO CASE' GROUP BY T2.l_orderkey ) AS T WHERE T.num > 2
|
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"case",
"container",
"."
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{
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"type": "value",
"value": "JUMBO CASE"
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"value": "num"
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"id": 2,
"type": "value",
"value": "2"
}
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"O",
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"I-VALUE",
"B-COLUMN",
"O"
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15,424
|
pilot_record
|
spider:train_spider.json:2089
|
What are the different nationalities of pilots? Show each nationality and the number of pilots of each nationality.
|
SELECT Nationality , COUNT(*) FROM pilot GROUP BY Nationality
|
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"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
15,425
|
aircraft
|
spider:train_spider.json:4819
|
What is the average total number of passengers of airports that are associated with aircraft "Robinson R-22"?
|
SELECT avg(T3.Total_Passengers) FROM aircraft AS T1 JOIN airport_aircraft AS T2 ON T1.Aircraft_ID = T2.Aircraft_ID JOIN airport AS T3 ON T2.Airport_ID = T3.Airport_ID WHERE T1.Aircraft = "Robinson R-22"
|
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"?"
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{
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"value": "airport"
}
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"I-COLUMN",
"O",
"O"
] |
15,426
|
disney
|
bird:train.json:4673
|
Who directed the movie with the most voice actors?
|
SELECT T2.director, COUNT(DISTINCT T1.`voice-actor`) FROM `voice-actors` AS T1 INNER JOIN director AS T2 ON T1.movie = T2.name GROUP BY T2.director ORDER BY COUNT(DISTINCT T1.`voice-actor`) DESC LIMIT 1
|
[
"Who",
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"with",
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"most",
"voice",
"actors",
"?"
] |
[
{
"id": 1,
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{
"id": 3,
"type": "column",
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{
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"type": "column",
"value": "director"
},
{
"id": 2,
"type": "table",
"value": "director"
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{
"id": 4,
"type": "column",
"value": "movie"
},
{
"id": 5,
"type": "column",
"value": "name"
}
] |
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"B-COLUMN",
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"O",
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] |
15,428
|
ice_hockey_draft
|
bird:train.json:6996
|
Who is the tallest player in team USA U20?
|
SELECT T.PlayerName FROM ( SELECT T1.PlayerName, T3.height_in_cm FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID INNER JOIN height_info AS T3 ON T1.height = T3.height_id WHERE T2.TEAM = 'USA U20' ORDER BY T3.height_in_cm DESC ) AS T WHERE T.height_in_cm = ( SELECT MAX(T3.height_in_cm) FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID INNER JOIN height_info AS T3 ON T1.height = T3.height_id WHERE T2.TEAM = 'USA U20' )
|
[
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"USA",
"U20",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "height_in_cm"
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{
"id": 6,
"type": "table",
"value": "seasonstatus"
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{
"id": 2,
"type": "table",
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{
"id": 0,
"type": "column",
"value": "playername"
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{
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"type": "table",
"value": "playerinfo"
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{
"id": 8,
"type": "column",
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{
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{
"id": 9,
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{
"id": 7,
"type": "column",
"value": "height"
},
{
"id": 3,
"type": "column",
"value": "team"
}
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[
"O",
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"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
15,429
|
law_episode
|
bird:train.json:1252
|
Park Dietz was credited in which role in the episode titled "Cherished"?
|
SELECT T2.role FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T1.title = 'Cherished' AND T3.name = 'Park Dietz' AND T2.credited = 'true'
|
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"Cherished",
"\"",
"?"
] |
[
{
"id": 8,
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{
"id": 11,
"type": "column",
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{
"id": 4,
"type": "column",
"value": "person_id"
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{
"id": 6,
"type": "value",
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{
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"type": "column",
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},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "table",
"value": "credit"
},
{
"id": 5,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "role"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 10,
"type": "value",
"value": "true"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
0,
1
]
},
{
"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-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
15,430
|
allergy_1
|
spider:train_spider.json:508
|
Which students are unaffected by allergies?
|
SELECT StuID FROM Student EXCEPT SELECT StuID FROM Has_allergy
|
[
"Which",
"students",
"are",
"unaffected",
"by",
"allergies",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "has_allergy"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stuid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"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-TABLE",
"O"
] |
15,431
|
club_1
|
spider:train_spider.json:4292
|
How many clubs are located at "HHH"?
|
SELECT count(*) FROM club WHERE clublocation = "HHH"
|
[
"How",
"many",
"clubs",
"are",
"located",
"at",
"\"",
"HHH",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "clublocation"
},
{
"id": 0,
"type": "table",
"value": "club"
},
{
"id": 2,
"type": "column",
"value": "HHH"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,432
|
art_1
|
bird:test.json:1236
|
Find the first and last names of the artists who have both works of paintings and sculptures?
|
SELECT T1.lname , T1.fname FROM artists AS T1 JOIN sculptures AS T2 ON T1.artistID = T2.sculptorID INTERSECT SELECT T3.lname , T3.fname FROM artists AS T3 JOIN paintings AS T4 ON T3.artistID = T4.painterID
|
[
"Find",
"the",
"first",
"and",
"last",
"names",
"of",
"the",
"artists",
"who",
"have",
"both",
"works",
"of",
"paintings",
"and",
"sculptures",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "sculptures"
},
{
"id": 6,
"type": "column",
"value": "sculptorid"
},
{
"id": 4,
"type": "table",
"value": "paintings"
},
{
"id": 7,
"type": "column",
"value": "painterid"
},
{
"id": 5,
"type": "column",
"value": "artistid"
},
{
"id": 2,
"type": "table",
"value": "artists"
},
{
"id": 0,
"type": "column",
"value": "lname"
},
{
"id": 1,
"type": "column",
"value": "fname"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"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": [
16
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
15,433
|
codebase_community
|
bird:dev.json:612
|
What is the name of badge that the user whose display name is "Pierre" obtained?
|
SELECT T2.Name FROM users AS T1 INNER JOIN badges AS T2 ON T1.Id = T2.UserId WHERE T1.DisplayName = 'Pierre'
|
[
"What",
"is",
"the",
"name",
"of",
"badge",
"that",
"the",
"user",
"whose",
"display",
"name",
"is",
"\"",
"Pierre",
"\"",
"obtained",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "displayname"
},
{
"id": 2,
"type": "table",
"value": "badges"
},
{
"id": 4,
"type": "value",
"value": "Pierre"
},
{
"id": 6,
"type": "column",
"value": "userid"
},
{
"id": 1,
"type": "table",
"value": "users"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
15,434
|
legislator
|
bird:train.json:4858
|
How many female legislators become representatives for California in 2015?
|
SELECT COUNT(*) FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE STRFTIME('%Y', T2.start) = '2015' AND T2.state = 'CA' AND T1.gender_bio = 'F'
|
[
"How",
"many",
"female",
"legislators",
"become",
"representatives",
"for",
"California",
"in",
"2015",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "current-terms"
},
{
"id": 2,
"type": "column",
"value": "bioguide_id"
},
{
"id": 7,
"type": "column",
"value": "gender_bio"
},
{
"id": 3,
"type": "column",
"value": "bioguide"
},
{
"id": 0,
"type": "table",
"value": "current"
},
{
"id": 5,
"type": "column",
"value": "state"
},
{
"id": 10,
"type": "column",
"value": "start"
},
{
"id": 4,
"type": "value",
"value": "2015"
},
{
"id": 6,
"type": "value",
"value": "CA"
},
{
"id": 9,
"type": "value",
"value": "%Y"
},
{
"id": 8,
"type": "value",
"value": "F"
}
] |
[
{
"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": []
},
{
"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-VALUE",
"O"
] |
15,435
|
software_company
|
bird:train.json:8580
|
Find out the yearly income of geographic ID when the customer is female and occupation as sales.
|
SELECT T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.OCCUPATION = 'Sales'
|
[
"Find",
"out",
"the",
"yearly",
"income",
"of",
"geographic",
"ID",
"when",
"the",
"customer",
"is",
"female",
"and",
"occupation",
"as",
"sales",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "inhabitants_k"
},
{
"id": 6,
"type": "column",
"value": "occupation"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 9,
"type": "column",
"value": "income_k"
},
{
"id": 5,
"type": "value",
"value": "Female"
},
{
"id": 1,
"type": "table",
"value": "demog"
},
{
"id": 3,
"type": "column",
"value": "geoid"
},
{
"id": 7,
"type": "value",
"value": "Sales"
},
{
"id": 4,
"type": "column",
"value": "sex"
},
{
"id": 2,
"type": "value",
"value": "12"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"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": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,436
|
mondial_geo
|
bird:train.json:8427
|
On what date did the country have a gross domestic product 400% higher than Saint Kitts and Nevis become independent?
|
SELECT Independence FROM politics WHERE country = ( SELECT country FROM economy WHERE GDP = 1100 )
|
[
"On",
"what",
"date",
"did",
"the",
"country",
"have",
"a",
"gross",
"domestic",
"product",
"400",
"%",
"higher",
"than",
"Saint",
"Kitts",
"and",
"Nevis",
"become",
"independent",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "independence"
},
{
"id": 0,
"type": "table",
"value": "politics"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "economy"
},
{
"id": 5,
"type": "value",
"value": "1100"
},
{
"id": 4,
"type": "column",
"value": "gdp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,437
|
scientist_1
|
spider:train_spider.json:6499
|
Find the number of projects which each scientist is working on and scientist's name.
|
SELECT count(*) , T1.name FROM scientists AS T1 JOIN assignedto AS T2 ON T1.ssn = T2.scientist GROUP BY T1.name
|
[
"Find",
"the",
"number",
"of",
"projects",
"which",
"each",
"scientist",
"is",
"working",
"on",
"and",
"scientist",
"'s",
"name",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "scientists"
},
{
"id": 2,
"type": "table",
"value": "assignedto"
},
{
"id": 4,
"type": "column",
"value": "scientist"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,438
|
superhero
|
bird:dev.json:748
|
What is the eye colour of superhero with superhero ID 75?
|
SELECT T2.colour FROM superhero AS T1 INNER JOIN colour AS T2 ON T1.eye_colour_id = T2.id WHERE T1.id = 75
|
[
"What",
"is",
"the",
"eye",
"colour",
"of",
"superhero",
"with",
"superhero",
"ID",
"75",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "eye_colour_id"
},
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 0,
"type": "column",
"value": "colour"
},
{
"id": 2,
"type": "table",
"value": "colour"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "75"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
15,439
|
simpson_episodes
|
bird:train.json:4363
|
What is the title of episode with 5 stars and nominated for Prism Award which is aired on April 19, 2009?
|
SELECT T3.title FROM Award AS T1 INNER JOIN Vote AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Episode AS T3 ON T1.episode_id = T3.episode_id WHERE T3.air_date = '2009-04-19' AND T1.award_category = 'Prism Award' AND T2.stars = 5 AND T1.result = 'Nominee';
|
[
"What",
"is",
"the",
"title",
"of",
"episode",
"with",
"5",
"stars",
"and",
"nominated",
"for",
"Prism",
"Award",
"which",
"is",
"aired",
"on",
"April",
"19",
",",
"2009",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "award_category"
},
{
"id": 8,
"type": "value",
"value": "Prism Award"
},
{
"id": 4,
"type": "column",
"value": "episode_id"
},
{
"id": 6,
"type": "value",
"value": "2009-04-19"
},
{
"id": 5,
"type": "column",
"value": "air_date"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 12,
"type": "value",
"value": "Nominee"
},
{
"id": 11,
"type": "column",
"value": "result"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "award"
},
{
"id": 9,
"type": "column",
"value": "stars"
},
{
"id": 3,
"type": "table",
"value": "vote"
},
{
"id": 10,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": [
8
]
},
{
"entity_id": 10,
"token_idxs": [
7
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
10
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,441
|
formula_1
|
bird:dev.json:929
|
Please list the Formula_1 races that Lewis Hamilton participated.
|
SELECT T1.name FROM races AS T1 INNER JOIN results AS T2 ON T2.raceId = T1.raceId INNER JOIN drivers AS T3 ON T3.driverId = T2.driverId WHERE T3.forename = 'Lewis' AND T3.surname = 'Hamilton'
|
[
"Please",
"list",
"the",
"Formula_1",
"races",
"that",
"Lewis",
"Hamilton",
"participated",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "driverid"
},
{
"id": 5,
"type": "column",
"value": "forename"
},
{
"id": 8,
"type": "value",
"value": "Hamilton"
},
{
"id": 1,
"type": "table",
"value": "drivers"
},
{
"id": 3,
"type": "table",
"value": "results"
},
{
"id": 7,
"type": "column",
"value": "surname"
},
{
"id": 9,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 6,
"type": "value",
"value": "Lewis"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"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",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
15,442
|
dorm_1
|
spider:train_spider.json:5671
|
What are the names of all the dorms that can accomdate more than 300 students?
|
SELECT dorm_name FROM dorm WHERE student_capacity > 300
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"the",
"dorms",
"that",
"can",
"accomdate",
"more",
"than",
"300",
"students",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "student_capacity"
},
{
"id": 1,
"type": "column",
"value": "dorm_name"
},
{
"id": 0,
"type": "table",
"value": "dorm"
},
{
"id": 3,
"type": "value",
"value": "300"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"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",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,443
|
hr_1
|
spider:train_spider.json:3527
|
display the full name (first and last name), and salary of those employees who working in any department located in London.
|
SELECT first_name , last_name , salary FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id WHERE T3.city = 'London'
|
[
"display",
"the",
"full",
"name",
"(",
"first",
"and",
"last",
"name",
")",
",",
"and",
"salary",
"of",
"those",
"employees",
"who",
"working",
"in",
"any",
"department",
"located",
"in",
"London",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "department_id"
},
{
"id": 7,
"type": "table",
"value": "departments"
},
{
"id": 8,
"type": "column",
"value": "location_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "table",
"value": "locations"
},
{
"id": 6,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "salary"
},
{
"id": 5,
"type": "value",
"value": "London"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
21,
22
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
23
]
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
20
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"B-VALUE",
"O"
] |
15,444
|
works_cycles
|
bird:train.json:7239
|
What is the reason for sales order "51883"?
|
SELECT T2.Name FROM SalesOrderHeaderSalesReason AS T1 INNER JOIN SalesReason AS T2 ON T1.SalesReasonID = T2.SalesReasonID WHERE T1.SalesOrderID = 51883
|
[
"What",
"is",
"the",
"reason",
"for",
"sales",
"order",
"\"",
"51883",
"\"",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "salesorderheadersalesreason"
},
{
"id": 5,
"type": "column",
"value": "salesreasonid"
},
{
"id": 3,
"type": "column",
"value": "salesorderid"
},
{
"id": 2,
"type": "table",
"value": "salesreason"
},
{
"id": 4,
"type": "value",
"value": "51883"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
15,445
|
hr_1
|
spider:train_spider.json:3468
|
What is the average salary for each job title?
|
SELECT job_title , AVG(salary) FROM employees AS T1 JOIN jobs AS T2 ON T1.job_id = T2.job_id GROUP BY T2.job_title
|
[
"What",
"is",
"the",
"average",
"salary",
"for",
"each",
"job",
"title",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "job_title"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 4,
"type": "column",
"value": "job_id"
},
{
"id": 2,
"type": "table",
"value": "jobs"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,446
|
video_games
|
bird:train.json:3419
|
Which publisher has published the most number of Action games?
|
SELECT T.publisher_name FROM ( SELECT T4.publisher_name, COUNT(DISTINCT T2.id) FROM genre AS T1 INNER JOIN game AS T2 ON T1.id = T2.genre_id INNER JOIN game_publisher AS T3 ON T2.id = T3.game_id INNER JOIN publisher AS T4 ON T3.publisher_id = T4.id WHERE T1.genre_name = 'Action' GROUP BY T4.publisher_name ORDER BY COUNT(DISTINCT T2.id) DESC LIMIT 1 ) t
|
[
"Which",
"publisher",
"has",
"published",
"the",
"most",
"number",
"of",
"Action",
"games",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 6,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "column",
"value": "genre_name"
},
{
"id": 1,
"type": "table",
"value": "publisher"
},
{
"id": 10,
"type": "column",
"value": "genre_id"
},
{
"id": 9,
"type": "column",
"value": "game_id"
},
{
"id": 3,
"type": "value",
"value": "Action"
},
{
"id": 7,
"type": "table",
"value": "genre"
},
{
"id": 8,
"type": "table",
"value": "game"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,447
|
codebase_community
|
bird:dev.json:587
|
Calculate the average view count of each post tagged as 'humor' and list the title and the comment of each post.
|
SELECT AVG(T2.ViewCount), T2.Title, T1.Text FROM comments AS T1 INNER JOIN posts AS T2 ON T2.Id = T1.PostId WHERE T2.Tags = '<humor>' GROUP BY T2.Title, T1.Text
|
[
"Calculate",
"the",
"average",
"view",
"count",
"of",
"each",
"post",
"tagged",
"as",
"'",
"humor",
"'",
"and",
"list",
"the",
"title",
"and",
"the",
"comment",
"of",
"each",
"post",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "viewcount"
},
{
"id": 2,
"type": "table",
"value": "comments"
},
{
"id": 5,
"type": "value",
"value": "<humor>"
},
{
"id": 8,
"type": "column",
"value": "postid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "posts"
},
{
"id": 1,
"type": "column",
"value": "text"
},
{
"id": 4,
"type": "column",
"value": "tags"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": [
22
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
3,
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
15,449
|
olympics
|
bird:train.json:4976
|
How many gold medals were given to the winners in the Ice Hockey Men's Ice Hockey event?
|
SELECT COUNT(T2.competitor_id) FROM event AS T1 INNER JOIN competitor_event AS T2 ON T1.id = T2.event_id WHERE T1.event_name LIKE 'Ice Hockey Men%s Ice Hockey' AND T2.medal_id = 1
|
[
"How",
"many",
"gold",
"medals",
"were",
"given",
"to",
"the",
"winners",
"in",
"the",
"Ice",
"Hockey",
"Men",
"'s",
"Ice",
"Hockey",
"event",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Ice Hockey Men%s Ice Hockey"
},
{
"id": 1,
"type": "table",
"value": "competitor_event"
},
{
"id": 2,
"type": "column",
"value": "competitor_id"
},
{
"id": 5,
"type": "column",
"value": "event_name"
},
{
"id": 4,
"type": "column",
"value": "event_id"
},
{
"id": 7,
"type": "column",
"value": "medal_id"
},
{
"id": 0,
"type": "table",
"value": "event"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"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": [
11,
12,
13,
14,
15,
16
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"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",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
15,450
|
student_loan
|
bird:train.json:4544
|
What is the employment and payment status of student110?
|
SELECT T1.bool FROM no_payment_due AS T1 INNER JOIN unemployed AS T2 ON T1.name = T2.name WHERE T1.name = 'student110'
|
[
"What",
"is",
"the",
"employment",
"and",
"payment",
"status",
"of",
"student110",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "no_payment_due"
},
{
"id": 2,
"type": "table",
"value": "unemployed"
},
{
"id": 4,
"type": "value",
"value": "student110"
},
{
"id": 0,
"type": "column",
"value": "bool"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,451
|
customers_and_addresses
|
spider:train_spider.json:6138
|
What are names of customers who never ordered product Latte.
|
SELECT customer_name FROM customers EXCEPT SELECT t1.customer_name FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id JOIN products AS t4 ON t3.product_id = t4.product_id WHERE t4.product_details = 'Latte'
|
[
"What",
"are",
"names",
"of",
"customers",
"who",
"never",
"ordered",
"product",
"Latte",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "product_details"
},
{
"id": 7,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 5,
"type": "table",
"value": "order_items"
},
{
"id": 9,
"type": "column",
"value": "customer_id"
},
{
"id": 6,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 8,
"type": "column",
"value": "order_id"
},
{
"id": 4,
"type": "value",
"value": "Latte"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": [
7
]
},
{
"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",
"B-TABLE",
"B-VALUE",
"O"
] |
15,452
|
college_2
|
spider:train_spider.json:1376
|
Which department has the lowest budget?
|
SELECT dept_name FROM department ORDER BY budget LIMIT 1
|
[
"Which",
"department",
"has",
"the",
"lowest",
"budget",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "department"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 2,
"type": "column",
"value": "budget"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,453
|
music_tracker
|
bird:train.json:2048
|
What are the top 5 tags with the highest amount of downloads?
|
SELECT T2.tag FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T1.releaseType = 'album' ORDER BY T1.totalSnatched DESC LIMIT 5
|
[
"What",
"are",
"the",
"top",
"5",
"tags",
"with",
"the",
"highest",
"amount",
"of",
"downloads",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "totalsnatched"
},
{
"id": 3,
"type": "column",
"value": "releasetype"
},
{
"id": 1,
"type": "table",
"value": "torrents"
},
{
"id": 4,
"type": "value",
"value": "album"
},
{
"id": 2,
"type": "table",
"value": "tags"
},
{
"id": 0,
"type": "column",
"value": "tag"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,454
|
books
|
bird:train.json:5997
|
How many addresses are from the Philippines?
|
SELECT COUNT(T2.country_id) FROM address AS T1 INNER JOIN country AS T2 ON T2.country_id = T1.country_id WHERE T2.country_name = 'Philippines'
|
[
"How",
"many",
"addresses",
"are",
"from",
"the",
"Philippines",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 3,
"type": "value",
"value": "Philippines"
},
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "table",
"value": "address"
},
{
"id": 1,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,455
|
network_2
|
spider:train_spider.json:4482
|
Find Alice's friends of friends.
|
SELECT DISTINCT T4.name FROM PersonFriend AS T1 JOIN Person AS T2 ON T1.name = T2.name JOIN PersonFriend AS T3 ON T1.friend = T3.name JOIN PersonFriend AS T4 ON T3.friend = T4.name WHERE T2.name = 'Alice' AND T4.name != 'Alice'
|
[
"Find",
"Alice",
"'s",
"friends",
"of",
"friends",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "personfriend"
},
{
"id": 2,
"type": "column",
"value": "friend"
},
{
"id": 4,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "value",
"value": "Alice"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"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-VALUE",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O"
] |
15,456
|
movie_1
|
spider:train_spider.json:2494
|
How many movie reviews does each director get?
|
SELECT count(*) , T1.director FROM Movie AS T1 JOIN Rating AS T2 ON T1.mID = T2.mID GROUP BY T1.director
|
[
"How",
"many",
"movie",
"reviews",
"does",
"each",
"director",
"get",
"?"
] |
[
{
"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": [
6
]
},
{
"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-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,457
|
legislator
|
bird:train.json:4809
|
What is the middle name of the legislator whose birthday was on 8/24/1956?
|
SELECT middle_name FROM current WHERE birthday_bio = '1956-08-24'
|
[
"What",
"is",
"the",
"middle",
"name",
"of",
"the",
"legislator",
"whose",
"birthday",
"was",
"on",
"8/24/1956",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "birthday_bio"
},
{
"id": 1,
"type": "column",
"value": "middle_name"
},
{
"id": 3,
"type": "value",
"value": "1956-08-24"
},
{
"id": 0,
"type": "table",
"value": "current"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,458
|
debit_card_specializing
|
bird:dev.json:1488
|
Who among KAM's customers consumed the most? How much did it consume?
|
SELECT T2.CustomerID, SUM(T2.Consumption) FROM customers AS T1 INNER JOIN yearmonth AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.Segment = 'KAM' GROUP BY T2.CustomerID ORDER BY SUM(T2.Consumption) DESC LIMIT 1
|
[
"Who",
"among",
"KAM",
"'s",
"customers",
"consumed",
"the",
"most",
"?",
"How",
"much",
"did",
"it",
"consume",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "consumption"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "yearmonth"
},
{
"id": 3,
"type": "column",
"value": "segment"
},
{
"id": 4,
"type": "value",
"value": "KAM"
}
] |
[
{
"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": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,459
|
authors
|
bird:train.json:3636
|
What is the percentage of preprints of John Van Reenen's papers?
|
SELECT CAST(SUM(CASE WHEN T1.ConferenceId = 0 AND T1.JournalId = 0 THEN 1 ELSE 0 END) AS REAL) / COUNT(T1.Id) FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name = 'John Van Reenen'
|
[
"What",
"is",
"the",
"percentage",
"of",
"preprints",
"of",
"John",
"Van",
"Reenen",
"'s",
"papers",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "John Van Reenen"
},
{
"id": 8,
"type": "column",
"value": "conferenceid"
},
{
"id": 1,
"type": "table",
"value": "paperauthor"
},
{
"id": 9,
"type": "column",
"value": "journalid"
},
{
"id": 5,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
15,460
|
flight_4
|
spider:train_spider.json:6882
|
What is the name of the airport with the most number of routes that start in China?
|
SELECT T1.name FROM airports AS T1 JOIN routes AS T2 ON T1.apid = T2.src_apid WHERE T1.country = 'China' GROUP BY T1.name ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"airport",
"with",
"the",
"most",
"number",
"of",
"routes",
"that",
"start",
"in",
"China",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "airports"
},
{
"id": 6,
"type": "column",
"value": "src_apid"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "routes"
},
{
"id": 4,
"type": "value",
"value": "China"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "apid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,461
|
film_rank
|
spider:train_spider.json:4144
|
List the names of studios that have at least two films.
|
SELECT Studio FROM film GROUP BY Studio HAVING COUNT(*) >= 2
|
[
"List",
"the",
"names",
"of",
"studios",
"that",
"have",
"at",
"least",
"two",
"films",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "studio"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"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",
"B-TABLE",
"O"
] |
15,462
|
books
|
bird:train.json:5989
|
List all the authors named "George".
|
SELECT author_name FROM author WHERE author_name LIKE 'George%'
|
[
"List",
"all",
"the",
"authors",
"named",
"\"",
"George",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "author_name"
},
{
"id": 2,
"type": "value",
"value": "George%"
},
{
"id": 0,
"type": "table",
"value": "author"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
15,463
|
card_games
|
bird:dev.json:432
|
Which Russian set of cards contains the most cards overall?
|
SELECT T1.id FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.code = T2.setCode WHERE T2.language = 'Russian' GROUP BY T1.baseSetSize ORDER BY T1.baseSetSize DESC LIMIT 1
|
[
"Which",
"Russian",
"set",
"of",
"cards",
"contains",
"the",
"most",
"cards",
"overall",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "set_translations"
},
{
"id": 0,
"type": "column",
"value": "basesetsize"
},
{
"id": 4,
"type": "column",
"value": "language"
},
{
"id": 5,
"type": "value",
"value": "Russian"
},
{
"id": 7,
"type": "column",
"value": "setcode"
},
{
"id": 2,
"type": "table",
"value": "sets"
},
{
"id": 6,
"type": "column",
"value": "code"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"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-VALUE",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,464
|
vehicle_rent
|
bird:test.json:422
|
Return all information about discounts.
|
SELECT * FROM discount
|
[
"Return",
"all",
"information",
"about",
"discounts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "discount"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,465
|
small_bank_1
|
spider:train_spider.json:1801
|
What are the names and sum of checking and savings balances for accounts with savings balances higher than the average savings balance?
|
SELECT T1.name , T2.balance + T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T3.balance > (SELECT avg(balance) FROM savings)
|
[
"What",
"are",
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"names",
"and",
"sum",
"of",
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"savings",
"balances",
"for",
"accounts",
"with",
"savings",
"balances",
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"than",
"the",
"average",
"savings",
"balance",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "accounts"
},
{
"id": 4,
"type": "table",
"value": "checking"
},
{
"id": 1,
"type": "table",
"value": "savings"
},
{
"id": 2,
"type": "column",
"value": "balance"
},
{
"id": 5,
"type": "column",
"value": "custid"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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"token_idxs": [
20
]
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21
]
},
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12
]
},
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]
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,466
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4196
|
How many employees do we have?
|
SELECT count(*) FROM Employees
|
[
"How",
"many",
"employees",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employees"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
15,467
|
sales_in_weather
|
bird:train.json:8175
|
What percentage was the total unit sales of store no.10 to the total sales of its weather station on 2014/10/31?
|
SELECT CAST(SUM(CASE WHEN T2.store_nbr = 10 THEN units * 1 ELSE 0 END) AS REAL) * 100 / SUM(units) FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr WHERE T1.`date` = '2014-10-31'
|
[
"What",
"percentage",
"was",
"the",
"total",
"unit",
"sales",
"of",
"store",
"no.10",
"to",
"the",
"total",
"sales",
"of",
"its",
"weather",
"station",
"on",
"2014/10/31",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "sales_in_weather"
},
{
"id": 3,
"type": "value",
"value": "2014-10-31"
},
{
"id": 4,
"type": "column",
"value": "store_nbr"
},
{
"id": 1,
"type": "table",
"value": "relation"
},
{
"id": 6,
"type": "column",
"value": "units"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "10"
},
{
"id": 7,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13,
14,
15,
16
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,470
|
chicago_crime
|
bird:train.json:8702
|
What phone number does alderman Emma Mitts have to call if she wants to speak to the commander in charge of the investigation of the crimes that have occurred in her ward?
|
SELECT T3.phone FROM Ward AS T1 INNER JOIN Crime AS T2 ON T2.ward_no = T1.ward_no INNER JOIN District AS T3 ON T3.district_no = T2.district_no WHERE T1.alderman_first_name = 'Emma' AND T1.alderman_last_name = 'Mitts'
|
[
"What",
"phone",
"number",
"does",
"alderman",
"Emma",
"Mitts",
"have",
"to",
"call",
"if",
"she",
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"to",
"speak",
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"the",
"commander",
"in",
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"the",
"investigation",
"of",
"the",
"crimes",
"that",
"have",
"occurred",
"in",
"her",
"ward",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "alderman_first_name"
},
{
"id": 7,
"type": "column",
"value": "alderman_last_name"
},
{
"id": 4,
"type": "column",
"value": "district_no"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 9,
"type": "column",
"value": "ward_no"
},
{
"id": 0,
"type": "column",
"value": "phone"
},
{
"id": 3,
"type": "table",
"value": "crime"
},
{
"id": 8,
"type": "value",
"value": "Mitts"
},
{
"id": 2,
"type": "table",
"value": "ward"
},
{
"id": 6,
"type": "value",
"value": "Emma"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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31
]
},
{
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25
]
},
{
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},
{
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},
{
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5
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4
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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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"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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,471
|
works_cycles
|
bird:train.json:7266
|
How much is the average salary of female employees in comparison to male employees?
|
SELECT AVG(T2.Rate) FROM Employee AS T1 INNER JOIN EmployeePayHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.Gender = 'F'
|
[
"How",
"much",
"is",
"the",
"average",
"salary",
"of",
"female",
"employees",
"in",
"comparison",
"to",
"male",
"employees",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "employeepayhistory"
},
{
"id": 5,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "rate"
},
{
"id": 3,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,472
|
formula_1
|
bird:dev.json:916
|
Please list the surnames of all the Italian drivers.
|
SELECT surname FROM drivers WHERE nationality = 'Italian'
|
[
"Please",
"list",
"the",
"surnames",
"of",
"all",
"the",
"Italian",
"drivers",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "drivers"
},
{
"id": 1,
"type": "column",
"value": "surname"
},
{
"id": 3,
"type": "value",
"value": "Italian"
}
] |
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{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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{
"entity_id": 3,
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7
]
},
{
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{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,473
|
e_commerce
|
bird:test.json:55
|
What is the order that total cost the least , and how much is the total cost ?
|
select t1.order_id , sum(t2.product_price) from order_items as t1 join products as t2 on t1.product_id = t2.product_id group by t1.order_id order by sum(t2.product_price) asc limit 1
|
[
"What",
"is",
"the",
"order",
"that",
"total",
"cost",
"the",
"least",
",",
"and",
"how",
"much",
"is",
"the",
"total",
"cost",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "product_price"
},
{
"id": 1,
"type": "table",
"value": "order_items"
},
{
"id": 4,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "column",
"value": "order_id"
},
{
"id": 2,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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{
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{
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{
"entity_id": 5,
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},
{
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},
{
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{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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{
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"token_idxs": []
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{
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},
{
"entity_id": 14,
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,474
|
news_report
|
spider:train_spider.json:2810
|
Show the nations that have both journalists with more than 10 years of working and journalists with less than 3 years of working.
|
SELECT Nationality FROM journalist WHERE Years_working > 10 INTERSECT SELECT Nationality FROM journalist WHERE Years_working < 3
|
[
"Show",
"the",
"nations",
"that",
"have",
"both",
"journalists",
"with",
"more",
"than",
"10",
"years",
"of",
"working",
"and",
"journalists",
"with",
"less",
"than",
"3",
"years",
"of",
"working",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "years_working"
},
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "journalist"
},
{
"id": 3,
"type": "value",
"value": "10"
},
{
"id": 4,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
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11,
12,
13
]
},
{
"entity_id": 3,
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10
]
},
{
"entity_id": 4,
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19
]
},
{
"entity_id": 5,
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},
{
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},
{
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},
{
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},
{
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},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
15,475
|
ice_hockey_draft
|
bird:train.json:6938
|
Who is the youngest player to have played during the 1997-1998 season for OHL League?
|
SELECT DISTINCT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '1997-1998' AND T1.LEAGUE = 'OHL' ORDER BY T2.birthdate DESC LIMIT 1
|
[
"Who",
"is",
"the",
"youngest",
"player",
"to",
"have",
"played",
"during",
"the",
"1997",
"-",
"1998",
"season",
"for",
"OHL",
"League",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "seasonstatus"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 2,
"type": "table",
"value": "playerinfo"
},
{
"id": 3,
"type": "column",
"value": "birthdate"
},
{
"id": 6,
"type": "value",
"value": "1997-1998"
},
{
"id": 4,
"type": "column",
"value": "eliteid"
},
{
"id": 5,
"type": "column",
"value": "season"
},
{
"id": 7,
"type": "column",
"value": "league"
},
{
"id": 8,
"type": "value",
"value": "OHL"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
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15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,476
|
ice_hockey_draft
|
bird:train.json:6970
|
Among the USA players, who has the lightest weight?
|
SELECT T2.PlayerName FROM weight_info AS T1 INNER JOIN PlayerInfo AS T2 ON T1.weight_id = T2.weight WHERE T2.nation = 'USA' ORDER BY T1.weight_in_lbs ASC LIMIT 1
|
[
"Among",
"the",
"USA",
"players",
",",
"who",
"has",
"the",
"lightest",
"weight",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "weight_in_lbs"
},
{
"id": 1,
"type": "table",
"value": "weight_info"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 2,
"type": "table",
"value": "playerinfo"
},
{
"id": 6,
"type": "column",
"value": "weight_id"
},
{
"id": 3,
"type": "column",
"value": "nation"
},
{
"id": 7,
"type": "column",
"value": "weight"
},
{
"id": 4,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,477
|
simpson_episodes
|
bird:train.json:4158
|
Which crew member of the simpson 20s is the oldest?
|
SELECT name FROM Person WHERE birthdate IS NOT NULL ORDER BY birthdate ASC LIMIT 1;
|
[
"Which",
"crew",
"member",
"of",
"the",
"simpson",
"20s",
"is",
"the",
"oldest",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "birthdate"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"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",
"O",
"O",
"O",
"O"
] |
15,478
|
institution_sports
|
bird:test.json:1661
|
List the names of institutions in descending order of the number of championships.
|
SELECT T2.Name FROM championship AS T1 JOIN institution AS T2 ON T1.Institution_ID = T2.Institution_ID ORDER BY T1.Number_of_Championships DESC
|
[
"List",
"the",
"names",
"of",
"institutions",
"in",
"descending",
"order",
"of",
"the",
"number",
"of",
"championships",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "number_of_championships"
},
{
"id": 4,
"type": "column",
"value": "institution_id"
},
{
"id": 1,
"type": "table",
"value": "championship"
},
{
"id": 2,
"type": "table",
"value": "institution"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
15,479
|
inn_1
|
spider:train_spider.json:2588
|
How many king beds are there?
|
SELECT sum(beds) FROM Rooms WHERE bedtype = 'King';
|
[
"How",
"many",
"king",
"beds",
"are",
"there",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "bedtype"
},
{
"id": 0,
"type": "table",
"value": "rooms"
},
{
"id": 2,
"type": "value",
"value": "King"
},
{
"id": 3,
"type": "column",
"value": "beds"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"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",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
15,480
|
mondial_geo
|
bird:train.json:8415
|
Which country with a city with a population between 50,000 and 300,000 inhabitants and which is a member of an organization established between 03/01/1991 and 04/30/1991 is also a member of the EBRD?
|
SELECT T2.Country FROM country AS T1 INNER JOIN isMember AS T2 ON T1.Code = T2.Country INNER JOIN organization AS T3 ON T3.Country = T2.Country INNER JOIN city AS T4 ON T4.Country = T3.Country WHERE T3.Abbreviation = 'EBRD' AND T4.Population BETWEEN 50000 AND 300000 AND T3.Established BETWEEN '1991-01-31' AND '1991-04-30'
|
[
"Which",
"country",
"with",
"a",
"city",
"with",
"a",
"population",
"between",
"50,000",
"and",
"300,000",
"inhabitants",
"and",
"which",
"is",
"a",
"member",
"of",
"an",
"organization",
"established",
"between",
"03/01/1991",
"and",
"04/30/1991",
"is",
"also",
"a",
"member",
"of",
"the",
"EBRD",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "organization"
},
{
"id": 3,
"type": "column",
"value": "abbreviation"
},
{
"id": 8,
"type": "column",
"value": "established"
},
{
"id": 5,
"type": "column",
"value": "population"
},
{
"id": 9,
"type": "value",
"value": "1991-01-31"
},
{
"id": 10,
"type": "value",
"value": "1991-04-30"
},
{
"id": 12,
"type": "table",
"value": "ismember"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 11,
"type": "table",
"value": "country"
},
{
"id": 7,
"type": "value",
"value": "300000"
},
{
"id": 6,
"type": "value",
"value": "50000"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "EBRD"
},
{
"id": 13,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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19,
20
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},
{
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},
{
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7
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},
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},
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},
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"token_idxs": [
1
]
},
{
"entity_id": 12,
"token_idxs": [
29
]
},
{
"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-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,481
|
world_development_indicators
|
bird:train.json:2193
|
Name the country in which the topic is about Poverty: Shared Prosperity. Indicate the long name of the country.
|
SELECT DISTINCT T1.LongName FROM Country AS T1 INNER JOIN footnotes AS T2 ON T1.CountryCode = T2.Countrycode INNER JOIN Series AS T3 ON T2.Seriescode = T3.SeriesCode WHERE T3.Topic = 'Poverty: Shared prosperity'
|
[
"Name",
"the",
"country",
"in",
"which",
"the",
"topic",
"is",
"about",
"Poverty",
":",
"Shared",
"Prosperity",
".",
"Indicate",
"the",
"long",
"name",
"of",
"the",
"country",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Poverty: Shared prosperity"
},
{
"id": 7,
"type": "column",
"value": "countrycode"
},
{
"id": 6,
"type": "column",
"value": "seriescode"
},
{
"id": 5,
"type": "table",
"value": "footnotes"
},
{
"id": 0,
"type": "column",
"value": "longname"
},
{
"id": 4,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "series"
},
{
"id": 2,
"type": "column",
"value": "topic"
}
] |
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{
"entity_id": 0,
"token_idxs": [
16,
17
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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6
]
},
{
"entity_id": 3,
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9,
10,
11,
12
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},
{
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20
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,482
|
computer_student
|
bird:train.json:1015
|
How many students are under advisor 415?
|
SELECT COUNT(*) FROM advisedBy WHERE p_id_dummy = 415
|
[
"How",
"many",
"students",
"are",
"under",
"advisor",
"415",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "p_id_dummy"
},
{
"id": 0,
"type": "table",
"value": "advisedby"
},
{
"id": 2,
"type": "value",
"value": "415"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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",
"B-VALUE",
"O"
] |
15,484
|
art_1
|
bird:test.json:1293
|
What are the first names of all artists who have at least two paintings, and how many works did each create?
|
SELECT T1.fname , count(*) FROM artists AS T1 JOIN paintings AS T2 ON T1.artistID = T2.painterID GROUP BY T2.painterID HAVING count(*) >= 2
|
[
"What",
"are",
"the",
"first",
"names",
"of",
"all",
"artists",
"who",
"have",
"at",
"least",
"two",
"paintings",
",",
"and",
"how",
"many",
"works",
"did",
"each",
"create",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "painterid"
},
{
"id": 3,
"type": "table",
"value": "paintings"
},
{
"id": 5,
"type": "column",
"value": "artistid"
},
{
"id": 2,
"type": "table",
"value": "artists"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,485
|
movie_platform
|
bird:train.json:9
|
List ther users who gave the worst rating for movie 'Love Will Tear Us Apart'.
|
SELECT T1.user_id FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id WHERE T2.movie_title = 'Love Will Tear Us Apart' AND T1.rating_score = 1
|
[
"List",
"ther",
"users",
"who",
"gave",
"the",
"worst",
"rating",
"for",
"movie",
"'",
"Love",
"Will",
"Tear",
"Us",
"Apart",
"'",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Love Will Tear Us Apart"
},
{
"id": 6,
"type": "column",
"value": "rating_score"
},
{
"id": 4,
"type": "column",
"value": "movie_title"
},
{
"id": 3,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 2,
"type": "table",
"value": "movies"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10,
11
]
},
{
"entity_id": 5,
"token_idxs": [
12,
13,
14,
15
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"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",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
15,486
|
codebase_community
|
bird:dev.json:708
|
List the creation date and age of the user that commented with webiste.
|
SELECT T2.CreationDate, T2.Age FROM comments AS T1 INNER JOIN users AS T2 ON T1.UserId = T2.Id WHERE T1.text LIKE '%http://%'
|
[
"List",
"the",
"creation",
"date",
"and",
"age",
"of",
"the",
"user",
"that",
"commented",
"with",
"webiste",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "creationdate"
},
{
"id": 5,
"type": "value",
"value": "%http://%"
},
{
"id": 2,
"type": "table",
"value": "comments"
},
{
"id": 6,
"type": "column",
"value": "userid"
},
{
"id": 3,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "column",
"value": "text"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
15,487
|
customers_and_orders
|
bird:test.json:260
|
What are the names of all Hardware products, sorted by price ascending?
|
SELECT product_name FROM Products WHERE product_type_code = "Hardware" ORDER BY product_price ASC
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"Hardware",
"products",
",",
"sorted",
"by",
"price",
"ascending",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_type_code"
},
{
"id": 4,
"type": "column",
"value": "product_price"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "column",
"value": "Hardware"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
15,488
|
legislator
|
bird:train.json:4804
|
Provide the start date, end date, and party of Pearl Peden Oldfield.
|
SELECT T2.start, T2.`end`, T2.party FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.first_name = 'Pearl' AND T1.middle_name = 'Peden' AND T1.last_name = 'Oldfield'
|
[
"Provide",
"the",
"start",
"date",
",",
"end",
"date",
",",
"and",
"party",
"of",
"Pearl",
"Peden",
"Oldfield",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "historical-terms"
},
{
"id": 5,
"type": "column",
"value": "bioguide_id"
},
{
"id": 9,
"type": "column",
"value": "middle_name"
},
{
"id": 3,
"type": "table",
"value": "historical"
},
{
"id": 7,
"type": "column",
"value": "first_name"
},
{
"id": 11,
"type": "column",
"value": "last_name"
},
{
"id": 6,
"type": "column",
"value": "bioguide"
},
{
"id": 12,
"type": "value",
"value": "Oldfield"
},
{
"id": 0,
"type": "column",
"value": "start"
},
{
"id": 2,
"type": "column",
"value": "party"
},
{
"id": 8,
"type": "value",
"value": "Pearl"
},
{
"id": 10,
"type": "value",
"value": "Peden"
},
{
"id": 1,
"type": "column",
"value": "end"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
12
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
13
]
},
{
"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-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"B-VALUE",
"O"
] |
15,489
|
dorm_1
|
spider:train_spider.json:5677
|
What is the first name of the students who are in age 20 to 25 and living in PHL city?
|
SELECT fname FROM student WHERE city_code = 'PHL' AND age BETWEEN 20 AND 25
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"the",
"students",
"who",
"are",
"in",
"age",
"20",
"to",
"25",
"and",
"living",
"in",
"PHL",
"city",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "city_code"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 3,
"type": "value",
"value": "PHL"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "value",
"value": "20"
},
{
"id": 6,
"type": "value",
"value": "25"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,490
|
language_corpus
|
bird:train.json:5713
|
Is word id "88" the word id for title "Animals"?
|
SELECT CASE WHEN COUNT(T1.pid) > 0 THEN 'YES' ELSE 'NO' END AS YORN FROM pages AS T1 INNER JOIN pages_words AS T2 ON T1.pid = T2.pid WHERE T2.wid = 88 AND T1.title = 'Animals'
|
[
"Is",
"word",
"i",
"d",
"\"",
"88",
"\"",
"the",
"word",
"i",
"d",
"for",
"title",
"\"",
"Animals",
"\"",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "pages_words"
},
{
"id": 7,
"type": "value",
"value": "Animals"
},
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 6,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "column",
"value": "pid"
},
{
"id": 4,
"type": "column",
"value": "wid"
},
{
"id": 8,
"type": "value",
"value": "YES"
},
{
"id": 2,
"type": "value",
"value": "NO"
},
{
"id": 5,
"type": "value",
"value": "88"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"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": [
2,
3
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
15,491
|
epinions_1
|
spider:train_spider.json:1715
|
Find the names of the items that did not receive any review.
|
SELECT title FROM item WHERE i_id NOT IN (SELECT i_id FROM review)
|
[
"Find",
"the",
"names",
"of",
"the",
"items",
"that",
"did",
"not",
"receive",
"any",
"review",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "review"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "item"
},
{
"id": 2,
"type": "column",
"value": "i_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"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-TABLE",
"O"
] |
15,492
|
car_retails
|
bird:train.json:1581
|
List out full name of employees who are working in Boston?
|
SELECT T1.firstName, T1.lastName FROM employees AS T1 INNER JOIN offices AS T2 ON T1.officeCode = T2.officeCode WHERE T2.city = 'Boston'
|
[
"List",
"out",
"full",
"name",
"of",
"employees",
"who",
"are",
"working",
"in",
"Boston",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "officecode"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "offices"
},
{
"id": 5,
"type": "value",
"value": "Boston"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,493
|
e_government
|
spider:train_spider.json:6346
|
Find the last name of the individuals that have been contact individuals of an organization.
|
SELECT DISTINCT t1.individual_last_name FROM individuals AS t1 JOIN organization_contact_individuals AS t2 ON t1.individual_id = t2.individual_id
|
[
"Find",
"the",
"last",
"name",
"of",
"the",
"individuals",
"that",
"have",
"been",
"contact",
"individuals",
"of",
"an",
"organization",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "organization_contact_individuals"
},
{
"id": 0,
"type": "column",
"value": "individual_last_name"
},
{
"id": 3,
"type": "column",
"value": "individual_id"
},
{
"id": 1,
"type": "table",
"value": "individuals"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,494
|
european_football_1
|
bird:train.json:2779
|
Which country did Bradford Team belongs to?
|
SELECT DISTINCT T2.country FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.HomeTeam = 'Bradford' OR T1.AwayTeam = 'Bradford'
|
[
"Which",
"country",
"did",
"Bradford",
"Team",
"belongs",
"to",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "divisions"
},
{
"id": 4,
"type": "column",
"value": "division"
},
{
"id": 5,
"type": "column",
"value": "hometeam"
},
{
"id": 6,
"type": "value",
"value": "Bradford"
},
{
"id": 7,
"type": "column",
"value": "awayteam"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "matchs"
},
{
"id": 3,
"type": "column",
"value": "div"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
15,495
|
machine_repair
|
spider:train_spider.json:2254
|
What are the names of the technicians by ascending order of quality rank for the machine they are assigned?
|
SELECT T3.Name FROM repair_assignment AS T1 JOIN machine AS T2 ON T1.machine_id = T2.machine_id JOIN technician AS T3 ON T1.technician_ID = T3.technician_ID ORDER BY T2.quality_rank
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"technicians",
"by",
"ascending",
"order",
"of",
"quality",
"rank",
"for",
"the",
"machine",
"they",
"are",
"assigned",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "repair_assignment"
},
{
"id": 5,
"type": "column",
"value": "technician_id"
},
{
"id": 2,
"type": "column",
"value": "quality_rank"
},
{
"id": 1,
"type": "table",
"value": "technician"
},
{
"id": 6,
"type": "column",
"value": "machine_id"
},
{
"id": 4,
"type": "table",
"value": "machine"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
17,
18
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
15,496
|
beer_factory
|
bird:train.json:5320
|
How many brands of bottle root beer were purchased between 4/3/2015 and 10/26/2015?
|
SELECT COUNT(BrandID) FROM rootbeer WHERE ContainerType = 'Bottle' AND PurchaseDate BETWEEN '2015-04-03' AND '2015-10-26'
|
[
"How",
"many",
"brands",
"of",
"bottle",
"root",
"beer",
"were",
"purchased",
"between",
"4/3/2015",
"and",
"10/26/2015",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "containertype"
},
{
"id": 4,
"type": "column",
"value": "purchasedate"
},
{
"id": 5,
"type": "value",
"value": "2015-04-03"
},
{
"id": 6,
"type": "value",
"value": "2015-10-26"
},
{
"id": 0,
"type": "table",
"value": "rootbeer"
},
{
"id": 1,
"type": "column",
"value": "brandid"
},
{
"id": 3,
"type": "value",
"value": "Bottle"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,497
|
works_cycles
|
bird:train.json:7312
|
List the name of married employees with less than 20 vacation hours.
|
SELECT T1.FirstName, T1.LastName FROM Person AS T1 INNER JOIN Employee AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T2.MaritalStatus = 'M' AND T2.VacationHours < 20
|
[
"List",
"the",
"name",
"of",
"married",
"employees",
"with",
"less",
"than",
"20",
"vacation",
"hours",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "businessentityid"
},
{
"id": 5,
"type": "column",
"value": "maritalstatus"
},
{
"id": 7,
"type": "column",
"value": "vacationhours"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 8,
"type": "value",
"value": "20"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0,
1
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10,
11
]
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,498
|
insurance_policies
|
spider:train_spider.json:3875
|
Find the the customer details and id for the customers who had more than one policy.
|
SELECT T1.customer_details , T1.customer_id FROM Customers AS T1 JOIN Customer_Policies AS T2 ON T1.Customer_id = T2.Customer_id GROUP BY T1.customer_id HAVING count(*) > 1
|
[
"Find",
"the",
"the",
"customer",
"details",
"and",
"i",
"d",
"for",
"the",
"customers",
"who",
"had",
"more",
"than",
"one",
"policy",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "customer_policies"
},
{
"id": 1,
"type": "column",
"value": "customer_details"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,499
|
books
|
bird:train.json:6042
|
How many books have been published in Japanese?
|
SELECT COUNT(*) FROM book_language AS T1 INNER JOIN book AS T2 ON T1.language_id = T2.language_id WHERE T1.language_name = 'Japanese'
|
[
"How",
"many",
"books",
"have",
"been",
"published",
"in",
"Japanese",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "book_language"
},
{
"id": 2,
"type": "column",
"value": "language_name"
},
{
"id": 4,
"type": "column",
"value": "language_id"
},
{
"id": 3,
"type": "value",
"value": "Japanese"
},
{
"id": 1,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,500
|
legislator
|
bird:train.json:4835
|
Provide the google entity ID of the senators in New York.
|
SELECT T1.google_entity_id_id FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.type = 'sen' AND T2.state = 'NY'
|
[
"Provide",
"the",
"google",
"entity",
"ID",
"of",
"the",
"senators",
"in",
"New",
"York",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "google_entity_id_id"
},
{
"id": 2,
"type": "table",
"value": "historical-terms"
},
{
"id": 3,
"type": "column",
"value": "bioguide_id"
},
{
"id": 1,
"type": "table",
"value": "historical"
},
{
"id": 4,
"type": "column",
"value": "bioguide"
},
{
"id": 7,
"type": "column",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "type"
},
{
"id": 6,
"type": "value",
"value": "sen"
},
{
"id": 8,
"type": "value",
"value": "NY"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,501
|
olympics
|
bird:train.json:4964
|
How many males from Belgium have participated in an Olympic Games?
|
SELECT COUNT(T2.person_id) FROM noc_region AS T1 INNER JOIN person_region AS T2 ON T1.id = T2.region_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T1.region_name = 'Belgium' AND T3.gender = 'M'
|
[
"How",
"many",
"males",
"from",
"Belgium",
"have",
"participated",
"in",
"an",
"Olympic",
"Games",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "person_region"
},
{
"id": 5,
"type": "column",
"value": "region_name"
},
{
"id": 2,
"type": "table",
"value": "noc_region"
},
{
"id": 1,
"type": "column",
"value": "person_id"
},
{
"id": 9,
"type": "column",
"value": "region_id"
},
{
"id": 6,
"type": "value",
"value": "Belgium"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 7,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "M"
}
] |
[
{
"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": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,502
|
movies_4
|
bird:train.json:539
|
List the character names played by Catherine Deneuve.
|
SELECT T2.character_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T1.person_name = 'Catherine Deneuve'
|
[
"List",
"the",
"character",
"names",
"played",
"by",
"Catherine",
"Deneuve",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Catherine Deneuve"
},
{
"id": 0,
"type": "column",
"value": "character_name"
},
{
"id": 3,
"type": "column",
"value": "person_name"
},
{
"id": 2,
"type": "table",
"value": "movie_cast"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "person"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6,
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,503
|
image_and_language
|
bird:train.json:7483
|
How many pairs of object samples in image no.1 have the relation of "parked on"?
|
SELECT SUM(CASE WHEN T1.PRED_CLASS = 'parked on' THEN 1 ELSE 0 END) FROM PRED_CLASSES AS T1 INNER JOIN IMG_REL AS T2 ON T1.PRED_CLASS_ID = T2.PRED_CLASS_ID WHERE T2.IMG_ID = 1 AND T2.OBJ1_SAMPLE_ID != OBJ2_SAMPLE_ID
|
[
"How",
"many",
"pairs",
"of",
"object",
"samples",
"in",
"image",
"no.1",
"have",
"the",
"relation",
"of",
"\"",
"parked",
"on",
"\"",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "obj1_sample_id"
},
{
"id": 6,
"type": "column",
"value": "obj2_sample_id"
},
{
"id": 2,
"type": "column",
"value": "pred_class_id"
},
{
"id": 0,
"type": "table",
"value": "pred_classes"
},
{
"id": 8,
"type": "column",
"value": "pred_class"
},
{
"id": 9,
"type": "value",
"value": "parked on"
},
{
"id": 1,
"type": "table",
"value": "img_rel"
},
{
"id": 3,
"type": "column",
"value": "img_id"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
14,
15
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
15,504
|
pilot_1
|
bird:test.json:1167
|
Find the location of the plane that is owned by the youngest pilot.
|
SELECT T2.location FROM pilotskills AS T1 JOIN hangar AS T2 ON T1.plane_name = T2.plane_name WHERE T1.age = (SELECT min(age) FROM pilotskills)
|
[
"Find",
"the",
"location",
"of",
"the",
"plane",
"that",
"is",
"owned",
"by",
"the",
"youngest",
"pilot",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "pilotskills"
},
{
"id": 4,
"type": "column",
"value": "plane_name"
},
{
"id": 0,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "table",
"value": "hangar"
},
{
"id": 3,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,505
|
college_completion
|
bird:train.json:3719
|
Give the web site address for the school in "PA" state with the highest latitude.
|
SELECT DISTINCT T1.site FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.state = T1.state WHERE T2.state_abbr = 'PA' AND T1.lat_y = ( SELECT MAX(T1.lat_y) FROM institution_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.state = T1.state WHERE T2.state_abbr = 'PA' )
|
[
"Give",
"the",
"web",
"site",
"address",
"for",
"the",
"school",
"in",
"\"",
"PA",
"\"",
"state",
"with",
"the",
"highest",
"latitude",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "institution_details"
},
{
"id": 2,
"type": "table",
"value": "state_sector_grads"
},
{
"id": 4,
"type": "column",
"value": "state_abbr"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "lat_y"
},
{
"id": 0,
"type": "column",
"value": "site"
},
{
"id": 5,
"type": "value",
"value": "PA"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"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",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,506
|
storm_record
|
spider:train_spider.json:2697
|
Return the names of all regions other than Denmark.
|
SELECT region_name FROM region WHERE region_name != 'Denmark'
|
[
"Return",
"the",
"names",
"of",
"all",
"regions",
"other",
"than",
"Denmark",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "region_name"
},
{
"id": 2,
"type": "value",
"value": "Denmark"
},
{
"id": 0,
"type": "table",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,507
|
movie_3
|
bird:train.json:9337
|
Calculate the percentage of movie titles with a screen length of more than 120 minutes that have a category of horror movies.
|
SELECT CAST(SUM(IIF(T3.`name` = 'Horror', 1, 0)) * 100 / COUNT(T1.film_id) AS REAL) FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T3.category_id = T2.category_id WHERE T1.length > 120
|
[
"Calculate",
"the",
"percentage",
"of",
"movie",
"titles",
"with",
"a",
"screen",
"length",
"of",
"more",
"than",
"120",
"minutes",
"that",
"have",
"a",
"category",
"of",
"horror",
"movies",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "film_category"
},
{
"id": 5,
"type": "column",
"value": "category_id"
},
{
"id": 0,
"type": "table",
"value": "category"
},
{
"id": 6,
"type": "column",
"value": "film_id"
},
{
"id": 1,
"type": "column",
"value": "length"
},
{
"id": 11,
"type": "value",
"value": "Horror"
},
{
"id": 3,
"type": "table",
"value": "film"
},
{
"id": 10,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "value",
"value": "120"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
20
]
},
{
"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",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O"
] |
15,508
|
codebase_comments
|
bird:train.json:667
|
What is the solution path for method number 3?
|
SELECT T1.Path FROM Solution AS T1 INNER JOIN Method AS T2 ON T1.Id = T2.SolutionId WHERE T2.Id = 3
|
[
"What",
"is",
"the",
"solution",
"path",
"for",
"method",
"number",
"3",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "solutionid"
},
{
"id": 1,
"type": "table",
"value": "solution"
},
{
"id": 2,
"type": "table",
"value": "method"
},
{
"id": 0,
"type": "column",
"value": "path"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,509
|
student_assessment
|
spider:train_spider.json:61
|
What are the first and last names of all the candidates?
|
SELECT T2.first_name , T2.last_name FROM candidates AS T1 JOIN people AS T2 ON T1.candidate_id = T2.person_id
|
[
"What",
"are",
"the",
"first",
"and",
"last",
"names",
"of",
"all",
"the",
"candidates",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "candidate_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "table",
"value": "candidates"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 3,
"type": "table",
"value": "people"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5,
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",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,510
|
department_management
|
spider:train_spider.json:13
|
List the states where both the secretary of 'Treasury' department and the secretary of 'Homeland Security' were born.
|
SELECT T3.born_state FROM department AS T1 JOIN management AS T2 ON T1.department_id = T2.department_id JOIN head AS T3 ON T2.head_id = T3.head_id WHERE T1.name = 'Treasury' INTERSECT SELECT T3.born_state FROM department AS T1 JOIN management AS T2 ON T1.department_id = T2.department_id JOIN head AS T3 ON T2.head_id = T3.head_id WHERE T1.name = 'Homeland Security'
|
[
"List",
"the",
"states",
"where",
"both",
"the",
"secretary",
"of",
"'",
"Treasury",
"'",
"department",
"and",
"the",
"secretary",
"of",
"'",
"Homeland",
"Security",
"'",
"were",
"born",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Homeland Security"
},
{
"id": 8,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "column",
"value": "born_state"
},
{
"id": 5,
"type": "table",
"value": "department"
},
{
"id": 6,
"type": "table",
"value": "management"
},
{
"id": 3,
"type": "value",
"value": "Treasury"
},
{
"id": 7,
"type": "column",
"value": "head_id"
},
{
"id": 1,
"type": "table",
"value": "head"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"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",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
15,511
|
law_episode
|
bird:train.json:1353
|
Where is the place of birth of the actor with the number nm0007064 who has not been credited for playing the role of a "Narrator"?
|
SELECT DISTINCT T1.birth_place FROM Person AS T1 INNER JOIN Credit AS T2 ON T1.person_id = T2.person_id WHERE T1.person_id = 'nm0007064' AND T2.role = 'Narrator' AND T2.credited = 'false'
|
[
"Where",
"is",
"the",
"place",
"of",
"birth",
"of",
"the",
"actor",
"with",
"the",
"number",
"nm0007064",
"who",
"has",
"not",
"been",
"credited",
"for",
"playing",
"the",
"role",
"of",
"a",
"\"",
"Narrator",
"\"",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "birth_place"
},
{
"id": 3,
"type": "column",
"value": "person_id"
},
{
"id": 4,
"type": "value",
"value": "nm0007064"
},
{
"id": 6,
"type": "value",
"value": "Narrator"
},
{
"id": 7,
"type": "column",
"value": "credited"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 2,
"type": "table",
"value": "credit"
},
{
"id": 8,
"type": "value",
"value": "false"
},
{
"id": 5,
"type": "column",
"value": "role"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
17
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
21
]
},
{
"entity_id": 6,
"token_idxs": [
25
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,512
|
csu_1
|
spider:train_spider.json:2361
|
What are the names of the campus that have more faculties in 2002 than the maximum number in Orange county?
|
SELECT T1.campus FROM campuses AS T1 JOIN faculty AS T2 ON T1.id = T2.campus WHERE T2.year = 2002 AND faculty > (SELECT max(faculty) FROM campuses AS T1 JOIN faculty AS T2 ON T1.id = T2.campus WHERE T2.year = 2002 AND T1.county = "Orange")
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"campus",
"that",
"have",
"more",
"faculties",
"in",
"2002",
"than",
"the",
"maximum",
"number",
"in",
"Orange",
"county",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "campuses"
},
{
"id": 2,
"type": "table",
"value": "faculty"
},
{
"id": 6,
"type": "column",
"value": "faculty"
},
{
"id": 0,
"type": "column",
"value": "campus"
},
{
"id": 7,
"type": "column",
"value": "county"
},
{
"id": 8,
"type": "column",
"value": "Orange"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2002"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": [
18
]
},
{
"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-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
15,515
|
pilot_1
|
bird:test.json:1125
|
How many distinct planes are owned across all pilots?
|
SELECT count(DISTINCT plane_name) FROM pilotskills
|
[
"How",
"many",
"distinct",
"planes",
"are",
"owned",
"across",
"all",
"pilots",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "plane_name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,516
|
video_games
|
bird:train.json:3330
|
State the publisher name of the game "ModNation Racers".
|
SELECT T1.publisher_name FROM publisher AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.publisher_id INNER JOIN game AS T3 ON T2.game_id = T3.id WHERE T3.game_name = 'ModNation Racers'
|
[
"State",
"the",
"publisher",
"name",
"of",
"the",
"game",
"\"",
"ModNation",
"Racers",
"\"",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "ModNation Racers"
},
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 8,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "column",
"value": "game_name"
},
{
"id": 4,
"type": "table",
"value": "publisher"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
15,517
|
university
|
bird:train.json:8053
|
Provide the number of students at Yale University in 2016.
|
SELECT T1.num_students FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.university_name = 'Yale University' AND T1.year = 2016
|
[
"Provide",
"the",
"number",
"of",
"students",
"at",
"Yale",
"University",
"in",
"2016",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 5,
"type": "column",
"value": "university_name"
},
{
"id": 6,
"type": "value",
"value": "Yale University"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 0,
"type": "column",
"value": "num_students"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2016"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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7
]
},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
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},
{
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]
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{
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{
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},
{
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},
{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,518
|
chinook_1
|
spider:train_spider.json:867
|
What is the average duration in milliseconds of tracks that belong to Latin or Pop genre?
|
SELECT AVG(Milliseconds) FROM GENRE AS T1 JOIN TRACK AS T2 ON T1.GenreId = T2.GenreId WHERE T1.Name = "Latin" OR T1.Name = "Pop"
|
[
"What",
"is",
"the",
"average",
"duration",
"in",
"milliseconds",
"of",
"tracks",
"that",
"belong",
"to",
"Latin",
"or",
"Pop",
"genre",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "milliseconds"
},
{
"id": 3,
"type": "column",
"value": "genreid"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "track"
},
{
"id": 5,
"type": "column",
"value": "Latin"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "Pop"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
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8
]
},
{
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6
]
},
{
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},
{
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},
{
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12
]
},
{
"entity_id": 6,
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14
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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": 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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
15,519
|
financial
|
bird:dev.json:160
|
Among the weekly issuance accounts, how many have a loan of under 200000?
|
SELECT COUNT(T1.account_id) FROM loan AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id WHERE T2.frequency = 'POPLATEK TYDNE' AND T1.amount < 200000
|
[
"Among",
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"issuance",
"accounts",
",",
"how",
"many",
"have",
"a",
"loan",
"of",
"under",
"200000",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "POPLATEK TYDNE"
},
{
"id": 2,
"type": "column",
"value": "account_id"
},
{
"id": 3,
"type": "column",
"value": "frequency"
},
{
"id": 1,
"type": "table",
"value": "account"
},
{
"id": 5,
"type": "column",
"value": "amount"
},
{
"id": 6,
"type": "value",
"value": "200000"
},
{
"id": 0,
"type": "table",
"value": "loan"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
0
]
},
{
"entity_id": 6,
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13
]
},
{
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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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,520
|
shipping
|
bird:train.json:5645
|
How many customers are manufacturer?
|
SELECT COUNT(*) FROM customer WHERE cust_type = 'manufacturer'
|
[
"How",
"many",
"customers",
"are",
"manufacturer",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "manufacturer"
},
{
"id": 1,
"type": "column",
"value": "cust_type"
},
{
"id": 0,
"type": "table",
"value": "customer"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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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",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,521
|
driving_school
|
spider:train_spider.json:6678
|
What is maximum, minimum and average amount of outstanding of customer?
|
SELECT max(amount_outstanding) , min(amount_outstanding) , avg(amount_outstanding) FROM Customers;
|
[
"What",
"is",
"maximum",
",",
"minimum",
"and",
"average",
"amount",
"of",
"outstanding",
"of",
"customer",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "amount_outstanding"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
7,
8,
9
]
},
{
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
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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-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O"
] |
15,522
|
food_inspection_2
|
bird:train.json:6190
|
Calculate the average inspections per year done by Jessica Anthony from 2010 to 2017.
|
SELECT CAST(COUNT(CASE WHEN T1.first_name = 'Jessica' AND T1.last_name = 'Anthony' THEN T2.inspection_id ELSE 0 END) AS REAL) / 8 FROM employee AS T1 INNER JOIN inspection AS T2 ON T1.employee_id = T2.employee_id WHERE strftime('%Y', T2.inspection_date) BETWEEN '2010' AND '2017'
|
[
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"year",
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"by",
"Jessica",
"Anthony",
"from",
"2010",
"to",
"2017",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "inspection_date"
},
{
"id": 9,
"type": "column",
"value": "inspection_id"
},
{
"id": 5,
"type": "column",
"value": "employee_id"
},
{
"id": 1,
"type": "table",
"value": "inspection"
},
{
"id": 10,
"type": "column",
"value": "first_name"
},
{
"id": 12,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 11,
"type": "value",
"value": "Jessica"
},
{
"id": 13,
"type": "value",
"value": "Anthony"
},
{
"id": 2,
"type": "value",
"value": "2010"
},
{
"id": 3,
"type": "value",
"value": "2017"
},
{
"id": 6,
"type": "value",
"value": "%Y"
},
{
"id": 4,
"type": "value",
"value": "8"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
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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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8
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},
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"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
9
]
},
{
"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",
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"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,523
|
aircraft
|
spider:train_spider.json:4799
|
List the description of all aircrafts.
|
SELECT Description FROM aircraft
|
[
"List",
"the",
"description",
"of",
"all",
"aircrafts",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "aircraft"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
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2
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
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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-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,524
|
customers_card_transactions
|
spider:train_spider.json:742
|
What are the different transaction types, and how many transactions of each have taken place?
|
SELECT transaction_type , count(*) FROM Financial_transactions GROUP BY transaction_type
|
[
"What",
"are",
"the",
"different",
"transaction",
"types",
",",
"and",
"how",
"many",
"transactions",
"of",
"each",
"have",
"taken",
"place",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "financial_transactions"
},
{
"id": 1,
"type": "column",
"value": "transaction_type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9,
10
]
},
{
"entity_id": 1,
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4,
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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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,525
|
icfp_1
|
spider:train_spider.json:2881
|
What are the first and last name of the author who published the paper titled "Nameless, Painless"?
|
SELECT t1.fname , t1.lname FROM authors AS t1 JOIN authorship AS t2 ON t1.authid = t2.authid JOIN papers AS t3 ON t2.paperid = t3.paperid WHERE t3.title = "Nameless , Painless"
|
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"author",
"who",
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"paper",
"titled",
"\"",
"Nameless",
",",
"Painless",
"\"",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "Nameless , Painless"
},
{
"id": 6,
"type": "table",
"value": "authorship"
},
{
"id": 5,
"type": "table",
"value": "authors"
},
{
"id": 7,
"type": "column",
"value": "paperid"
},
{
"id": 2,
"type": "table",
"value": "papers"
},
{
"id": 8,
"type": "column",
"value": "authid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
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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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
15,526
|
farm
|
spider:train_spider.json:41
|
What are the themes of competitions that have corresponding host cities with more than 1000 residents?
|
SELECT T2.Theme FROM city AS T1 JOIN farm_competition AS T2 ON T1.City_ID = T2.Host_city_ID WHERE T1.Population > 1000
|
[
"What",
"are",
"the",
"themes",
"of",
"competitions",
"that",
"have",
"corresponding",
"host",
"cities",
"with",
"more",
"than",
"1000",
"residents",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "farm_competition"
},
{
"id": 6,
"type": "column",
"value": "host_city_id"
},
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 0,
"type": "column",
"value": "theme"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "1000"
}
] |
[
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"token_idxs": [
3
]
},
{
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10
]
},
{
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5
]
},
{
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},
{
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14
]
},
{
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},
{
"entity_id": 6,
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9
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},
{
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},
{
"entity_id": 8,
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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,
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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,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,527
|
legislator
|
bird:train.json:4910
|
What is the contact form of the legislator named Rick Crawford?
|
SELECT T2.contact_form FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.official_full_name = 'Rick Crawford'
|
[
"What",
"is",
"the",
"contact",
"form",
"of",
"the",
"legislator",
"named",
"Rick",
"Crawford",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "official_full_name"
},
{
"id": 2,
"type": "table",
"value": "current-terms"
},
{
"id": 4,
"type": "value",
"value": "Rick Crawford"
},
{
"id": 0,
"type": "column",
"value": "contact_form"
},
{
"id": 5,
"type": "column",
"value": "bioguide_id"
},
{
"id": 6,
"type": "column",
"value": "bioguide"
},
{
"id": 1,
"type": "table",
"value": "current"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,528
|
soccer_2016
|
bird:train.json:1852
|
Provide the point of the winning margin in a match between Mumbai Indians and Royal Challengers Bangalore on May 28, 2008.
|
SELECT T1.Win_Margin FROM Match AS T1 INNER JOIN Team AS T2 ON T2.Team_Id = T1.Team_1 INNER JOIN Team AS T3 ON T3.Team_Id = T1.Team_2 WHERE (T2.Team_Name = 'Mumbai Indians' AND T3.Team_Name = 'Royal Challengers Bangalore' AND T1.Match_Date = '2008-05-28') OR (T2.Team_Name = 'Royal Challengers Bangalore' AND T3.Team_Name = 'Mumbai Indians' AND T1.Match_Date = '2008-05-28')
|
[
"Provide",
"the",
"point",
"of",
"the",
"winning",
"margin",
"in",
"a",
"match",
"between",
"Mumbai",
"Indians",
"and",
"Royal",
"Challengers",
"Bangalore",
"on",
"May",
"28",
",",
"2008",
"."
] |
[
{
"id": 8,
"type": "value",
"value": "Royal Challengers Bangalore"
},
{
"id": 7,
"type": "value",
"value": "Mumbai Indians"
},
{
"id": 0,
"type": "column",
"value": "win_margin"
},
{
"id": 9,
"type": "column",
"value": "match_date"
},
{
"id": 10,
"type": "value",
"value": "2008-05-28"
},
{
"id": 6,
"type": "column",
"value": "team_name"
},
{
"id": 3,
"type": "column",
"value": "team_id"
},
{
"id": 4,
"type": "column",
"value": "team_2"
},
{
"id": 5,
"type": "column",
"value": "team_1"
},
{
"id": 2,
"type": "table",
"value": "match"
},
{
"id": 1,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
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},
{
"entity_id": 2,
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9
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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11,
12
]
},
{
"entity_id": 8,
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14,
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]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
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