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1,399
|
insurance_fnol
|
spider:train_spider.json:921
|
Find the names of customers who have used either the service "Close a policy" or the service "Upgrade a policy".
|
SELECT t1.customer_name FROM customers AS t1 JOIN first_notification_of_loss AS t2 ON t1.customer_id = t2.customer_id JOIN services AS t3 ON t2.service_id = t3.service_id WHERE t3.service_name = "Close a policy" OR t3.service_name = "Upgrade a policy"
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"."
] |
[
{
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{
"id": 7,
"type": "column",
"value": "Upgrade a policy"
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{
"id": 6,
"type": "column",
"value": "Close a policy"
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{
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"type": "column",
"value": "customer_name"
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{
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"value": "service_name"
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"type": "column",
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{
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"type": "table",
"value": "customers"
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{
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"value": "services"
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1,400
|
game_injury
|
spider:train_spider.json:1283
|
Find the id and name of the stadium where the largest number of injury accidents occurred.
|
SELECT T1.id , T1.name FROM stadium AS T1 JOIN game AS T2 ON T1.id = T2.stadium_id JOIN injury_accident AS T3 ON T2.id = T3.game_id GROUP BY T1.id ORDER BY count(*) DESC LIMIT 1
|
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{
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{
"id": 3,
"type": "table",
"value": "stadium"
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{
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"type": "column",
"value": "game_id"
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"value": "name"
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"type": "table",
"value": "game"
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{
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"value": "id"
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"O",
"O"
] |
1,401
|
donor
|
bird:train.json:3260
|
What date did the project with he 'Lets Share Ideas essay' went live?
|
SELECT T1.date_posted FROM projects AS T1 INNER JOIN essays AS T2 ON T1.projectid = T2.projectid WHERE T2.title LIKE 'Lets Share Ideas'
|
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"?"
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[
{
"id": 4,
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"id": 0,
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"value": "date_posted"
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{
"id": 5,
"type": "column",
"value": "projectid"
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{
"id": 1,
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"value": "projects"
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{
"id": 2,
"type": "table",
"value": "essays"
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{
"id": 3,
"type": "column",
"value": "title"
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"O",
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"O",
"B-VALUE",
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"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,402
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4174
|
What is the date when the document "Marry CV" was stored?
|
SELECT date_stored FROM All_documents WHERE Document_name = "Marry CV"
|
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[
{
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"type": "column",
"value": "date_stored"
},
{
"id": 3,
"type": "column",
"value": "Marry CV"
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{
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] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
1,404
|
retails
|
bird:train.json:6699
|
Give the name of the customer who made an order with Clerk#000000803 on 1997/12/10.
|
SELECT T2.c_name FROM orders AS T1 INNER JOIN customer AS T2 ON T1.o_custkey = T2.c_custkey WHERE T1.o_orderdate = '1997-12-10' AND T1.o_clerk = 'Clerk#000000803'
|
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"."
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[
{
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"value": "Clerk#000000803"
},
{
"id": 5,
"type": "column",
"value": "o_orderdate"
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{
"id": 6,
"type": "value",
"value": "1997-12-10"
},
{
"id": 3,
"type": "column",
"value": "o_custkey"
},
{
"id": 4,
"type": "column",
"value": "c_custkey"
},
{
"id": 2,
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{
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"type": "column",
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{
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"type": "column",
"value": "c_name"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
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[
"O",
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"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,405
|
theme_gallery
|
spider:train_spider.json:1682
|
What are the names of artists who did not have an exhibition in 2004?
|
SELECT name FROM artist EXCEPT SELECT T2.name FROM exhibition AS T1 JOIN artist AS T2 ON T1.artist_id = T2.artist_id WHERE T1.year = 2004
|
[
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[
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"value": "artist_id"
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{
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"type": "table",
"value": "artist"
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{
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{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2004"
}
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"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,406
|
flight_1
|
spider:train_spider.json:371
|
What is average and maximum salary of all employees.
|
SELECT avg(salary) , max(salary) FROM Employee
|
[
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"."
] |
[
{
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"type": "table",
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{
"id": 1,
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[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,407
|
school_player
|
spider:train_spider.json:4866
|
What are the enrollments of schools whose denomination is not "Catholic"?
|
SELECT Enrollment FROM school WHERE Denomination != "Catholic"
|
[
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"?"
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[
{
"id": 2,
"type": "column",
"value": "denomination"
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{
"id": 1,
"type": "column",
"value": "enrollment"
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{
"id": 3,
"type": "column",
"value": "Catholic"
},
{
"id": 0,
"type": "table",
"value": "school"
}
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[
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"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,408
|
olympics
|
bird:train.json:5070
|
Give the NOC code and region name of the heaviest competitor.
|
SELECT T1.noc, T1.region_name 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 ORDER BY T3.weight DESC LIMIT 1
|
[
"Give",
"the",
"NOC",
"code",
"and",
"region",
"name",
"of",
"the",
"heaviest",
"competitor",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "person_region"
},
{
"id": 1,
"type": "column",
"value": "region_name"
},
{
"id": 4,
"type": "table",
"value": "noc_region"
},
{
"id": 6,
"type": "column",
"value": "person_id"
},
{
"id": 8,
"type": "column",
"value": "region_id"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "weight"
},
{
"id": 0,
"type": "column",
"value": "noc"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
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"token_idxs": []
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"entity_id": 13,
"token_idxs": []
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"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
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"entity_id": 16,
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"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
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"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,409
|
formula_1
|
bird:dev.json:937
|
What's the finish time for the driver who ranked second in 2008's AustChineseralian Grand Prix?
|
SELECT T1.time FROM results AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId WHERE T1.rank = 2 AND T2.name = 'Chinese Grand Prix' AND T2.year = 2008
|
[
"What",
"'s",
"the",
"finish",
"time",
"for",
"the",
"driver",
"who",
"ranked",
"second",
"in",
"2008",
"'s",
"AustChineseralian",
"Grand",
"Prix",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Chinese Grand Prix"
},
{
"id": 1,
"type": "table",
"value": "results"
},
{
"id": 3,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 0,
"type": "column",
"value": "time"
},
{
"id": 4,
"type": "column",
"value": "rank"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2008"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"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": [
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]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
12
]
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,410
|
professional_basketball
|
bird:train.json:2947
|
For all the full attendence players in 1995, which player had most turnovers? Give the full name of the player.
|
SELECT T1.firstName, T1.middleName, T1.lastName FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE T2.GP = 82 AND T2.year = 1995 ORDER BY T2.turnovers DESC LIMIT 1
|
[
"For",
"all",
"the",
"full",
"attendence",
"players",
"in",
"1995",
",",
"which",
"player",
"had",
"most",
"turnovers",
"?",
"Give",
"the",
"full",
"name",
"of",
"the",
"player",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "players_teams"
},
{
"id": 1,
"type": "column",
"value": "middlename"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "turnovers"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 6,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "table",
"value": "players"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "1995"
},
{
"id": 7,
"type": "column",
"value": "gp"
},
{
"id": 8,
"type": "value",
"value": "82"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
10
]
},
{
"entity_id": 10,
"token_idxs": [
7
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,411
|
professional_basketball
|
bird:train.json:2840
|
Please list down the last name of players from "BLB" team.
|
SELECT T1.lastName FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE T2.tmID = 'BLB'
|
[
"Please",
"list",
"down",
"the",
"last",
"name",
"of",
"players",
"from",
"\"",
"BLB",
"\"",
"team",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "players_teams"
},
{
"id": 0,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 1,
"type": "table",
"value": "players"
},
{
"id": 3,
"type": "column",
"value": "tmid"
},
{
"id": 4,
"type": "value",
"value": "BLB"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,412
|
movie_3
|
bird:train.json:9251
|
Give the full name of the actor who acted the most in drama movies?
|
SELECT T.first_name, T.last_name FROM ( SELECT T1.first_name, T1.last_name, COUNT(T2.film_id) AS num FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film_category AS T3 ON T2.film_id = T3.film_id WHERE T3.category_id = 7 GROUP BY T1.first_name, T1.last_name ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"Give",
"the",
"full",
"name",
"of",
"the",
"actor",
"who",
"acted",
"the",
"most",
"in",
"drama",
"movies",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "film_category"
},
{
"id": 4,
"type": "column",
"value": "category_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 9,
"type": "column",
"value": "actor_id"
},
{
"id": 6,
"type": "column",
"value": "film_id"
},
{
"id": 7,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "column",
"value": "num"
},
{
"id": 5,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,413
|
game_1
|
spider:train_spider.json:5989
|
Show ids for all students who live in CHI.
|
SELECT StuID FROM Student WHERE city_code = "CHI"
|
[
"Show",
"ids",
"for",
"all",
"students",
"who",
"live",
"in",
"CHI",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "city_code"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "column",
"value": "CHI"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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": []
},
{
"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",
"B-COLUMN",
"O"
] |
1,414
|
mondial_geo
|
bird:train.json:8508
|
Indicate the coordinates of all the deserts whose area is in more than one country.
|
SELECT T1.Latitude, T1.Longitude FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert GROUP BY T1.Name, T1.Latitude, T1.Longitude HAVING COUNT(T1.Name) > 1
|
[
"Indicate",
"the",
"coordinates",
"of",
"all",
"the",
"deserts",
"whose",
"area",
"is",
"in",
"more",
"than",
"one",
"country",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "geo_desert"
},
{
"id": 2,
"type": "column",
"value": "longitude"
},
{
"id": 1,
"type": "column",
"value": "latitude"
},
{
"id": 3,
"type": "table",
"value": "desert"
},
{
"id": 6,
"type": "column",
"value": "desert"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"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": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,415
|
book_publishing_company
|
bird:train.json:177
|
Name the store with the highest quantity in sales? What is the least quantity title from the store's sale?
|
SELECT T3.stor_id, T2.title FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id INNER JOIN stores AS T3 ON T3.stor_id = T1.stor_id WHERE T3.stor_id = ( SELECT stor_id FROM sales GROUP BY stor_id ORDER BY SUM(qty) DESC LIMIT 1 ) GROUP BY T3.stor_id, T2.title ORDER BY SUM(T1.qty) ASC LIMIT 1
|
[
"Name",
"the",
"store",
"with",
"the",
"highest",
"quantity",
"in",
"sales",
"?",
"What",
"is",
"the",
"least",
"quantity",
"title",
"from",
"the",
"store",
"'s",
"sale",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "title_id"
},
{
"id": 0,
"type": "column",
"value": "stor_id"
},
{
"id": 2,
"type": "table",
"value": "stores"
},
{
"id": 4,
"type": "table",
"value": "titles"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "sales"
},
{
"id": 5,
"type": "column",
"value": "qty"
}
] |
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{
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"token_idxs": []
},
{
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"token_idxs": [
15
]
},
{
"entity_id": 2,
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18,
19
]
},
{
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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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
1,416
|
election
|
spider:train_spider.json:2735
|
Count the total number of counties.
|
SELECT count(*) FROM county
|
[
"Count",
"the",
"total",
"number",
"of",
"counties",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,417
|
customers_and_invoices
|
spider:train_spider.json:1547
|
Show the number of accounts.
|
SELECT count(*) FROM Accounts
|
[
"Show",
"the",
"number",
"of",
"accounts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "accounts"
}
] |
[
{
"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"
] |
1,418
|
company_office
|
spider:train_spider.json:4576
|
Which buildings do not have any company office? Give me the building names.
|
SELECT name FROM buildings WHERE id NOT IN (SELECT building_id FROM Office_locations)
|
[
"Which",
"buildings",
"do",
"not",
"have",
"any",
"company",
"office",
"?",
"Give",
"me",
"the",
"building",
"names",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "office_locations"
},
{
"id": 4,
"type": "column",
"value": "building_id"
},
{
"id": 0,
"type": "table",
"value": "buildings"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
1,419
|
chinook_1
|
spider:train_spider.json:832
|
Find the maximum and minimum durations of tracks in milliseconds.
|
SELECT max(Milliseconds) , min(Milliseconds) FROM TRACK
|
[
"Find",
"the",
"maximum",
"and",
"minimum",
"durations",
"of",
"tracks",
"in",
"milliseconds",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "milliseconds"
},
{
"id": 0,
"type": "table",
"value": "track"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"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": []
},
{
"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",
"B-COLUMN",
"O"
] |
1,420
|
chicago_crime
|
bird:train.json:8692
|
Calculate the difference in the average number of vehicular hijackings and aggravated vehicular hijackings in the districts.
|
SELECT ROUND(CAST(COUNT(CASE WHEN T1.secondary_description = 'VEHICULAR HIJACKING' THEN T1.iucr_no END) AS REAL) / CAST(COUNT(DISTINCT CASE WHEN T1.secondary_description = 'VEHICULAR HIJACKING' THEN T3.district_name END) AS REAL) - CAST(COUNT(CASE WHEN T1.secondary_description = 'AGGRAVATED VEHICULAR HIJACKING' THEN T1.iucr_no END) AS REAL) / CAST(COUNT(DISTINCT CASE WHEN T1.secondary_description = 'AGGRAVATED VEHICULAR HIJACKING' THEN T3.district_name END) AS REAL), 4) AS "difference" FROM IUCR AS T1 INNER JOIN Crime AS T2 ON T2.iucr_no = T1.iucr_no INNER JOIN District AS T3 ON T3.district_no = T2.district_no
|
[
"Calculate",
"the",
"difference",
"in",
"the",
"average",
"number",
"of",
"vehicular",
"hijackings",
"and",
"aggravated",
"vehicular",
"hijackings",
"in",
"the",
"districts",
"."
] |
[
{
"id": 9,
"type": "value",
"value": "AGGRAVATED VEHICULAR HIJACKING"
},
{
"id": 7,
"type": "column",
"value": "secondary_description"
},
{
"id": 8,
"type": "value",
"value": "VEHICULAR HIJACKING"
},
{
"id": 6,
"type": "column",
"value": "district_name"
},
{
"id": 4,
"type": "column",
"value": "district_no"
},
{
"id": 0,
"type": "table",
"value": "district"
},
{
"id": 5,
"type": "column",
"value": "iucr_no"
},
{
"id": 3,
"type": "table",
"value": "crime"
},
{
"id": 2,
"type": "table",
"value": "iucr"
},
{
"id": 1,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"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": [
12,
13
]
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"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",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
1,421
|
public_review_platform
|
bird:train.json:4081
|
List the user ID, business ID with review length of the business which received the most likes in tips.
|
SELECT T1.user_id, T1.business_id, T2.review_length FROM Tips AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id ORDER BY T1.likes DESC LIMIT 1
|
[
"List",
"the",
"user",
"ID",
",",
"business",
"ID",
"with",
"review",
"length",
"of",
"the",
"business",
"which",
"received",
"the",
"most",
"likes",
"in",
"tips",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "review_length"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "table",
"value": "reviews"
},
{
"id": 5,
"type": "column",
"value": "likes"
},
{
"id": 3,
"type": "table",
"value": "tips"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"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",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
1,422
|
synthea
|
bird:train.json:1511
|
List out full name of patients who have "Diabetic diet" in the description of the care plan.
|
SELECT DISTINCT T2.first, T2.last FROM careplans AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T1.DESCRIPTION = 'Diabetic diet'
|
[
"List",
"out",
"full",
"name",
"of",
"patients",
"who",
"have",
"\"",
"Diabetic",
"diet",
"\"",
"in",
"the",
"description",
"of",
"the",
"care",
"plan",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Diabetic diet"
},
{
"id": 4,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "careplans"
},
{
"id": 3,
"type": "table",
"value": "patients"
},
{
"id": 6,
"type": "column",
"value": "patient"
},
{
"id": 0,
"type": "column",
"value": "first"
},
{
"id": 1,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"entity_id": 2,
"token_idxs": [
17,
18
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
9,
10
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
1,423
|
image_and_language
|
bird:train.json:7582
|
How many images have "vegetable" and "fruits" as their object classes?
|
SELECT COUNT(T1.IMG_ID) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T2.OBJ_CLASS = 'vegetables' OR T2.OBJ_CLASS = 'fruits'
|
[
"How",
"many",
"images",
"have",
"\"",
"vegetable",
"\"",
"and",
"\"",
"fruits",
"\"",
"as",
"their",
"object",
"classes",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "obj_class_id"
},
{
"id": 1,
"type": "table",
"value": "obj_classes"
},
{
"id": 5,
"type": "value",
"value": "vegetables"
},
{
"id": 4,
"type": "column",
"value": "obj_class"
},
{
"id": 0,
"type": "table",
"value": "img_obj"
},
{
"id": 2,
"type": "column",
"value": "img_id"
},
{
"id": 6,
"type": "value",
"value": "fruits"
}
] |
[
{
"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": [
13,
14
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,425
|
public_review_platform
|
bird:train.json:3942
|
List the categories of all active businesses that were not in Arizona.
|
SELECT T3.category_name FROM Business AS T1 INNER JOIN Business_Categories ON T1.business_id = Business_Categories.business_id INNER JOIN Categories AS T3 ON Business_Categories.category_id = T3.category_id WHERE T1.active LIKE 'TRUE' AND T1.state NOT LIKE 'AZ'
|
[
"List",
"the",
"categories",
"of",
"all",
"active",
"businesses",
"that",
"were",
"not",
"in",
"Arizona",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "business_categories"
},
{
"id": 0,
"type": "column",
"value": "category_name"
},
{
"id": 4,
"type": "column",
"value": "category_id"
},
{
"id": 9,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "categories"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "column",
"value": "active"
},
{
"id": 7,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "value",
"value": "TRUE"
},
{
"id": 8,
"type": "value",
"value": "AZ"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,426
|
college_1
|
spider:train_spider.json:3186
|
What is the description for the CIS-220 and how many credits does it have?
|
SELECT crs_credit , crs_description FROM course WHERE crs_code = 'CIS-220'
|
[
"What",
"is",
"the",
"description",
"for",
"the",
"CIS-220",
"and",
"how",
"many",
"credits",
"does",
"it",
"have",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "crs_description"
},
{
"id": 1,
"type": "column",
"value": "crs_credit"
},
{
"id": 3,
"type": "column",
"value": "crs_code"
},
{
"id": 4,
"type": "value",
"value": "CIS-220"
},
{
"id": 0,
"type": "table",
"value": "course"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,427
|
retail_world
|
bird:train.json:6627
|
What product have the highest unit price and how many quantity have been being sold?
|
SELECT T1.ProductName, T2.Quantity FROM Products AS T1 INNER JOIN `Order Details` AS T2 ON T1.ProductID = T2.ProductID ORDER BY T1.UnitPrice DESC LIMIT 1
|
[
"What",
"product",
"have",
"the",
"highest",
"unit",
"price",
"and",
"how",
"many",
"quantity",
"have",
"been",
"being",
"sold",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "Order Details"
},
{
"id": 0,
"type": "column",
"value": "productname"
},
{
"id": 4,
"type": "column",
"value": "unitprice"
},
{
"id": 5,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "column",
"value": "quantity"
},
{
"id": 2,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
1,428
|
movie_3
|
bird:train.json:9132
|
Please list the full names of all the customers who have rented the film with the highest replacement cost.
|
SELECT T1.first_name, T1.last_name FROM customer AS T1 INNER JOIN rental AS T2 ON T1.customer_id = T2.customer_id INNER JOIN inventory AS T3 ON T2.inventory_id = T3.inventory_id INNER JOIN film AS T4 ON T3.film_id = T4.film_id ORDER BY T4.replacement_cost DESC LIMIT 1
|
[
"Please",
"list",
"the",
"full",
"names",
"of",
"all",
"the",
"customers",
"who",
"have",
"rented",
"the",
"film",
"with",
"the",
"highest",
"replacement",
"cost",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "replacement_cost"
},
{
"id": 8,
"type": "column",
"value": "inventory_id"
},
{
"id": 9,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "table",
"value": "inventory"
},
{
"id": 6,
"type": "table",
"value": "customer"
},
{
"id": 5,
"type": "column",
"value": "film_id"
},
{
"id": 7,
"type": "table",
"value": "rental"
},
{
"id": 2,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
17,
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,429
|
works_cycles
|
bird:train.json:7068
|
Please give the additional contact information of the oldest employee with the jod position of sales person.
|
SELECT T2.AdditionalContactInfo FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE PersonType = 'SP' ORDER BY T1.BirthDate ASC LIMIT 1
|
[
"Please",
"give",
"the",
"additional",
"contact",
"information",
"of",
"the",
"oldest",
"employee",
"with",
"the",
"jod",
"position",
"of",
"sales",
"person",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "additionalcontactinfo"
},
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 3,
"type": "column",
"value": "persontype"
},
{
"id": 5,
"type": "column",
"value": "birthdate"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 4,
"type": "value",
"value": "SP"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,430
|
cre_Students_Information_Systems
|
bird:test.json:479
|
Show the biographical information of the students whose details include the substring 'Suite'.
|
SELECT bio_data FROM Students WHERE student_details LIKE '%Suite%'
|
[
"Show",
"the",
"biographical",
"information",
"of",
"the",
"students",
"whose",
"details",
"include",
"the",
"substring",
"'",
"Suite",
"'",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "student_details"
},
{
"id": 0,
"type": "table",
"value": "students"
},
{
"id": 1,
"type": "column",
"value": "bio_data"
},
{
"id": 3,
"type": "value",
"value": "%Suite%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
1,431
|
hockey
|
bird:train.json:7725
|
How many players were included in the Hall of Fame on average between 1950 and 1980?
|
SELECT CAST(COUNT(name) AS REAL) / 30 FROM HOF WHERE year BETWEEN 1950 AND 1980 AND category = 'Player'
|
[
"How",
"many",
"players",
"were",
"included",
"in",
"the",
"Hall",
"of",
"Fame",
"on",
"average",
"between",
"1950",
"and",
"1980",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "category"
},
{
"id": 6,
"type": "value",
"value": "Player"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "1950"
},
{
"id": 4,
"type": "value",
"value": "1980"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "table",
"value": "hof"
},
{
"id": 1,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,432
|
movies_4
|
bird:train.json:473
|
Which actor plays Optimus Prime?
|
SELECT DISTINCT T1.person_name FROM person AS T1 INNER JOIN movie_cast AS T2 ON T1.person_id = T2.person_id WHERE T2.character_name = 'Optimus Prime (voice)'
|
[
"Which",
"actor",
"plays",
"Optimus",
"Prime",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Optimus Prime (voice)"
},
{
"id": 3,
"type": "column",
"value": "character_name"
},
{
"id": 0,
"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": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
3,
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,433
|
superhero
|
bird:dev.json:778
|
Provide superheroes' names who have the adaptation power.
|
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T3.power_name = 'Adaptation'
|
[
"Provide",
"superheroes",
"'",
"names",
"who",
"have",
"the",
"adaptation",
"power",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "superhero_name"
},
{
"id": 1,
"type": "table",
"value": "superpower"
},
{
"id": 2,
"type": "column",
"value": "power_name"
},
{
"id": 3,
"type": "value",
"value": "Adaptation"
},
{
"id": 5,
"type": "table",
"value": "hero_power"
},
{
"id": 4,
"type": "table",
"value": "superhero"
},
{
"id": 6,
"type": "column",
"value": "power_id"
},
{
"id": 8,
"type": "column",
"value": "hero_id"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
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{
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3
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{
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1
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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",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,434
|
aan_1
|
bird:test.json:986
|
What are the titles and paper ids which have Mckeown as an author, but not Rambow?
|
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Mckeown%" EXCEPT SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Rambow%"
|
[
"What",
"are",
"the",
"titles",
"and",
"paper",
"ids",
"which",
"have",
"Mckeown",
"as",
"an",
"author",
",",
"but",
"not",
"Rambow",
"?"
] |
[
{
"id": 7,
"type": "table",
"value": "author_list"
},
{
"id": 4,
"type": "column",
"value": "%Mckeown%"
},
{
"id": 8,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "column",
"value": "paper_id"
},
{
"id": 5,
"type": "column",
"value": "%Rambow%"
},
{
"id": 2,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
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3
]
},
{
"entity_id": 1,
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6
]
},
{
"entity_id": 2,
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12
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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9
]
},
{
"entity_id": 5,
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16
]
},
{
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5
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},
{
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},
{
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{
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{
"entity_id": 13,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,435
|
soccer_2016
|
bird:train.json:1846
|
List the cities located in U.A.E.
|
SELECT T1.City_Name FROM City AS T1 INNER JOIN Country AS T2 ON T2.Country_Id = T1.Country_id WHERE T2.Country_Name = 'U.A.E'
|
[
"List",
"the",
"cities",
"located",
"in",
"U.A.E."
] |
[
{
"id": 3,
"type": "column",
"value": "country_name"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "column",
"value": "city_name"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "U.A.E"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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2
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE"
] |
1,436
|
csu_1
|
spider:train_spider.json:2348
|
Which campus has the most degrees conferred in all times?
|
SELECT campus FROM degrees GROUP BY campus ORDER BY sum(degrees) DESC LIMIT 1
|
[
"Which",
"campus",
"has",
"the",
"most",
"degrees",
"conferred",
"in",
"all",
"times",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "degrees"
},
{
"id": 2,
"type": "column",
"value": "degrees"
},
{
"id": 1,
"type": "column",
"value": "campus"
}
] |
[
{
"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",
"O",
"O",
"O",
"O"
] |
1,437
|
food_inspection
|
bird:train.json:8819
|
What is the name of the establishment with the highest number of low risk violations in 2014?
|
SELECT T2.name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE STRFTIME('%Y', T1.`date`) = '2014' AND T1.risk_category = 'Low Risk' GROUP BY T2.name ORDER BY COUNT(T2.business_id) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"establishment",
"with",
"the",
"highest",
"number",
"of",
"low",
"risk",
"violations",
"in",
"2014",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "risk_category"
},
{
"id": 3,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "violations"
},
{
"id": 2,
"type": "table",
"value": "businesses"
},
{
"id": 6,
"type": "value",
"value": "Low Risk"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "2014"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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12,
13
]
},
{
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"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",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,438
|
codebase_community
|
bird:dev.json:656
|
Describe the display name of the parent ID for child post with the highest score.
|
SELECT DisplayName FROM users WHERE Id = ( SELECT OwnerUserId FROM posts WHERE ParentId IS NOT NULL ORDER BY Score DESC LIMIT 1 )
|
[
"Describe",
"the",
"display",
"name",
"of",
"the",
"parent",
"ID",
"for",
"child",
"post",
"with",
"the",
"highest",
"score",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "displayname"
},
{
"id": 4,
"type": "column",
"value": "owneruserid"
},
{
"id": 5,
"type": "column",
"value": "parentid"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 3,
"type": "table",
"value": "posts"
},
{
"id": 6,
"type": "column",
"value": "score"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": [
14
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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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},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,439
|
aircraft
|
spider:train_spider.json:4817
|
Please show the names and descriptions of aircrafts associated with airports that have a total number of passengers bigger than 10000000.
|
SELECT T1.Aircraft , T1.Description 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 T3.Total_Passengers > 10000000
|
[
"Please",
"show",
"the",
"names",
"and",
"descriptions",
"of",
"aircrafts",
"associated",
"with",
"airports",
"that",
"have",
"a",
"total",
"number",
"of",
"passengers",
"bigger",
"than",
"10000000",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "total_passengers"
},
{
"id": 6,
"type": "table",
"value": "airport_aircraft"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 8,
"type": "column",
"value": "aircraft_id"
},
{
"id": 7,
"type": "column",
"value": "airport_id"
},
{
"id": 0,
"type": "column",
"value": "aircraft"
},
{
"id": 4,
"type": "value",
"value": "10000000"
},
{
"id": 5,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "table",
"value": "airport"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
20
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
1,440
|
student_1
|
spider:train_spider.json:4035
|
List the first names of all the students in room 107.
|
SELECT DISTINCT firstname FROM list WHERE classroom = 107
|
[
"List",
"the",
"first",
"names",
"of",
"all",
"the",
"students",
"in",
"room",
"107",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 2,
"type": "column",
"value": "classroom"
},
{
"id": 0,
"type": "table",
"value": "list"
},
{
"id": 3,
"type": "value",
"value": "107"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,441
|
aircraft
|
spider:train_spider.json:4837
|
find the name and age of the pilot who has won the most number of times among the pilots who are younger than 30.
|
SELECT t1.name , t1.age FROM pilot AS t1 JOIN MATCH AS t2 ON t1.pilot_id = t2.winning_pilot WHERE t1.age < 30 GROUP BY t2.winning_pilot ORDER BY count(*) DESC LIMIT 1
|
[
"find",
"the",
"name",
"and",
"age",
"of",
"the",
"pilot",
"who",
"has",
"won",
"the",
"most",
"number",
"of",
"times",
"among",
"the",
"pilots",
"who",
"are",
"younger",
"than",
"30",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "winning_pilot"
},
{
"id": 6,
"type": "column",
"value": "pilot_id"
},
{
"id": 3,
"type": "table",
"value": "pilot"
},
{
"id": 4,
"type": "table",
"value": "match"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "value",
"value": "30"
}
] |
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,442
|
hr_1
|
spider:train_spider.json:3430
|
What are the job ids and dates of hire for employees hired after November 5th, 2007 and before July 5th, 2009?
|
SELECT job_id , hire_date FROM employees WHERE hire_date BETWEEN '2007-11-05' AND '2009-07-05'
|
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"value": "employees"
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{
"id": 2,
"type": "column",
"value": "hire_date"
},
{
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"type": "column",
"value": "job_id"
}
] |
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[
"O",
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"O",
"O",
"O",
"O",
"B-TABLE",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,443
|
law_episode
|
bird:train.json:1327
|
What was the role of Jason Kuschner in episode 9?
|
SELECT T1.role FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id INNER JOIN Episode AS T3 ON T1.episode_id = T3.episode_id WHERE T3.episode = 9 AND T2.name = 'Jason Kuschner'
|
[
"What",
"was",
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"role",
"of",
"Jason",
"Kuschner",
"in",
"episode",
"9",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Jason Kuschner"
},
{
"id": 4,
"type": "column",
"value": "episode_id"
},
{
"id": 9,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 5,
"type": "column",
"value": "episode"
},
{
"id": 2,
"type": "table",
"value": "credit"
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{
"id": 3,
"type": "table",
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},
{
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"type": "column",
"value": "role"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "9"
}
] |
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[
"O",
"O",
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"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,444
|
ice_hockey_draft
|
bird:train.json:6946
|
Identify the players with the same height as Brian Gionta. How tall are they?
|
SELECT T2.PlayerName, T1.height_in_cm FROM height_info AS T1 INNER JOIN PlayerInfo AS T2 ON T1.height_id = T2.height WHERE T2.height = ( SELECT height FROM PlayerInfo WHERE PlayerName = 'Brian Gionta' )
|
[
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"Gionta",
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"are",
"they",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "height_in_cm"
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{
"id": 6,
"type": "value",
"value": "Brian Gionta"
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{
"id": 2,
"type": "table",
"value": "height_info"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 3,
"type": "table",
"value": "playerinfo"
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{
"id": 5,
"type": "column",
"value": "height_id"
},
{
"id": 4,
"type": "column",
"value": "height"
}
] |
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{
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{
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] |
[
"O",
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"O",
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"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,445
|
video_games
|
bird:train.json:3418
|
How many publishers published the Minecraft game?
|
SELECT COUNT(T2.publisher_id) FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id WHERE T1.game_name = 'Minecraft'
|
[
"How",
"many",
"publishers",
"published",
"the",
"Minecraft",
"game",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "game_publisher"
},
{
"id": 4,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "column",
"value": "game_name"
},
{
"id": 3,
"type": "value",
"value": "Minecraft"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 0,
"type": "table",
"value": "game"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
1,446
|
codebase_community
|
bird:dev.json:698
|
How many comments and answers were left by the users on the post with the title 'Clustering 1D data'?
|
SELECT CommentCount, AnswerCount FROM posts WHERE Title = 'Clustering 1D data'
|
[
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"were",
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"title",
"'",
"Clustering",
"1D",
"data",
"'",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Clustering 1D data"
},
{
"id": 1,
"type": "column",
"value": "commentcount"
},
{
"id": 2,
"type": "column",
"value": "answercount"
},
{
"id": 0,
"type": "table",
"value": "posts"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
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] |
[
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,447
|
retail_world
|
bird:train.json:6357
|
What is the Island Trading customer's complete address?
|
SELECT Address, City, Region, Country, PostalCode FROM Customers WHERE CompanyName = 'Island Trading'
|
[
"What",
"is",
"the",
"Island",
"Trading",
"customer",
"'s",
"complete",
"address",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Island Trading"
},
{
"id": 6,
"type": "column",
"value": "companyname"
},
{
"id": 5,
"type": "column",
"value": "postalcode"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "region"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
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{
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{
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}
] |
[
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O"
] |
1,448
|
movie_3
|
bird:train.json:9185
|
What is the name of the most rented movie?
|
SELECT T.title FROM ( SELECT T1.title, COUNT(T3.rental_id) AS num FROM film AS T1 INNER JOIN inventory AS T2 ON T1.film_id = T2.film_id INNER JOIN rental AS T3 ON T2.inventory_id = T3.inventory_id GROUP BY T1.title ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"most",
"rented",
"movie",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "inventory_id"
},
{
"id": 3,
"type": "column",
"value": "rental_id"
},
{
"id": 5,
"type": "table",
"value": "inventory"
},
{
"id": 7,
"type": "column",
"value": "film_id"
},
{
"id": 2,
"type": "table",
"value": "rental"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "table",
"value": "film"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
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{
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},
{
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}
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[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
1,449
|
restaurant
|
bird:train.json:1681
|
In which counties are there A&W Root Beer Restaurants?
|
SELECT DISTINCT T2.county FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.label = 'a & w root beer'
|
[
"In",
"which",
"counties",
"are",
"there",
"A&W",
"Root",
"Beer",
"Restaurants",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "a & w root beer"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "table",
"value": "geographic"
},
{
"id": 0,
"type": "column",
"value": "county"
},
{
"id": 3,
"type": "column",
"value": "label"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
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"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,450
|
synthea
|
bird:train.json:1452
|
On what dates did the billable period begin for patients with the last name Dickinson?
|
SELECT DISTINCT T2.BILLABLEPERIOD FROM patients AS T1 INNER JOIN claims AS T2 ON T1.patient = T2.PATIENT WHERE T1.last = 'Dickinson'
|
[
"On",
"what",
"dates",
"did",
"the",
"billable",
"period",
"begin",
"for",
"patients",
"with",
"the",
"last",
"name",
"Dickinson",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "billableperiod"
},
{
"id": 4,
"type": "value",
"value": "Dickinson"
},
{
"id": 1,
"type": "table",
"value": "patients"
},
{
"id": 5,
"type": "column",
"value": "patient"
},
{
"id": 2,
"type": "table",
"value": "claims"
},
{
"id": 3,
"type": "column",
"value": "last"
}
] |
[
{
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"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
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},
{
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"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,451
|
movie
|
bird:train.json:775
|
List the character's name of actress born in Sherman Oaks and starred in the movie Bruce Almighty with height greater than the 50% of average height of all actors listed.
|
SELECT T3.Name FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE T3.Gender = 'Female' AND T1.Title = 'Godzilla' AND T3.`Birth City` = 'Sherman Oaks' AND T3.`Height (Inches)` * 100 > ( SELECT AVG(`Height (Inches)`) FROM actor ) * 50
|
[
"List",
"the",
"character",
"'s",
"name",
"of",
"actress",
"born",
"in",
"Sherman",
"Oaks",
"and",
"starred",
"in",
"the",
"movie",
"Bruce",
"Almighty",
"with",
"height",
"greater",
"than",
"the",
"50",
"%",
"of",
"average",
"height",
"of",
"all",
"actors",
"listed",
"."
] |
[
{
"id": 12,
"type": "column",
"value": "Height (Inches)"
},
{
"id": 10,
"type": "value",
"value": "Sherman Oaks"
},
{
"id": 3,
"type": "table",
"value": "characters"
},
{
"id": 9,
"type": "column",
"value": "Birth City"
},
{
"id": 8,
"type": "value",
"value": "Godzilla"
},
{
"id": 4,
"type": "column",
"value": "actorid"
},
{
"id": 11,
"type": "column",
"value": "movieid"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "value",
"value": "Female"
},
{
"id": 1,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 7,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 13,
"type": "value",
"value": "100"
},
{
"id": 14,
"type": "value",
"value": "50"
}
] |
[
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"token_idxs": [
4
]
},
{
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]
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10
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},
{
"entity_id": 12,
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27,
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": [
23
]
},
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"entity_id": 15,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
1,452
|
world_development_indicators
|
bird:train.json:2109
|
What are the Indicator names and aggregation methods when the topic is Economic Policy & Debt: Balance of payments: Capital & financial account?
|
SELECT IndicatorName, AggregationMethod FROM Series WHERE Topic = 'Economic Policy & Debt: Balance of payments: Capital & financial account'
|
[
"What",
"are",
"the",
"Indicator",
"names",
"and",
"aggregation",
"methods",
"when",
"the",
"topic",
"is",
"Economic",
"Policy",
"&",
"Debt",
":",
"Balance",
"of",
"payments",
":",
"Capital",
"&",
"financial",
"account",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Economic Policy & Debt: Balance of payments: Capital & financial account"
},
{
"id": 2,
"type": "column",
"value": "aggregationmethod"
},
{
"id": 1,
"type": "column",
"value": "indicatorname"
},
{
"id": 0,
"type": "table",
"value": "series"
},
{
"id": 3,
"type": "column",
"value": "topic"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
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"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
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"token_idxs": [
12,
13,
14,
15,
16,
17,
18,
19,
20,
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22,
23,
24
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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": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,453
|
financial
|
bird:dev.json:186
|
What percentage of male clients request for weekly statements to be issued?
|
SELECT CAST(SUM(T1.gender = 'M') AS REAL) * 100 / COUNT(T1.client_id) FROM client AS T1 INNER JOIN district AS T3 ON T1.district_id = T3.district_id INNER JOIN account AS T2 ON T2.district_id = T3.district_id INNER JOIN disp as T4 on T1.client_id = T4.client_id AND T2.account_id = T4.account_id WHERE T2.frequency = 'POPLATEK TYDNE'
|
[
"What",
"percentage",
"of",
"male",
"clients",
"request",
"for",
"weekly",
"statements",
"to",
"be",
"issued",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "POPLATEK TYDNE"
},
{
"id": 8,
"type": "column",
"value": "district_id"
},
{
"id": 9,
"type": "column",
"value": "account_id"
},
{
"id": 1,
"type": "column",
"value": "frequency"
},
{
"id": 5,
"type": "column",
"value": "client_id"
},
{
"id": 7,
"type": "table",
"value": "district"
},
{
"id": 3,
"type": "table",
"value": "account"
},
{
"id": 6,
"type": "table",
"value": "client"
},
{
"id": 10,
"type": "column",
"value": "gender"
},
{
"id": 0,
"type": "table",
"value": "disp"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 11,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
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},
{
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"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
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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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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,454
|
ship_1
|
spider:train_spider.json:6253
|
What are the names of ships, ordered by year they were built and their class?
|
SELECT name FROM ship ORDER BY built_year , CLASS
|
[
"What",
"are",
"the",
"names",
"of",
"ships",
",",
"ordered",
"by",
"year",
"they",
"were",
"built",
"and",
"their",
"class",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "built_year"
},
{
"id": 3,
"type": "column",
"value": "class"
},
{
"id": 0,
"type": "table",
"value": "ship"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
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12
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
1,455
|
customer_complaints
|
spider:train_spider.json:5795
|
What is the last name of the staff member in charge of the complaint on the product with the lowest price?
|
SELECT t1.last_name FROM staff AS t1 JOIN complaints AS t2 ON t1.staff_id = t2.staff_id JOIN products AS t3 ON t2.product_id = t3.product_id ORDER BY t3.product_price LIMIT 1
|
[
"What",
"is",
"the",
"last",
"name",
"of",
"the",
"staff",
"member",
"in",
"charge",
"of",
"the",
"complaint",
"on",
"the",
"product",
"with",
"the",
"lowest",
"price",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_price"
},
{
"id": 4,
"type": "table",
"value": "complaints"
},
{
"id": 5,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "column",
"value": "last_name"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "staff_id"
},
{
"id": 3,
"type": "table",
"value": "staff"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,456
|
synthea
|
bird:train.json:1365
|
Please list all the medication that are prescribed to Elly Koss.
|
SELECT DISTINCT T2.description FROM patients AS T1 INNER JOIN medications AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Elly' AND T1.last = 'Koss'
|
[
"Please",
"list",
"all",
"the",
"medication",
"that",
"are",
"prescribed",
"to",
"Elly",
"Koss",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "medications"
},
{
"id": 1,
"type": "table",
"value": "patients"
},
{
"id": 3,
"type": "column",
"value": "patient"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 5,
"type": "value",
"value": "Elly"
},
{
"id": 6,
"type": "column",
"value": "last"
},
{
"id": 7,
"type": "value",
"value": "Koss"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7,
8
]
},
{
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},
{
"entity_id": 2,
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4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
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{
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{
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"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-VALUE",
"O"
] |
1,457
|
airline
|
bird:train.json:5846
|
For the flight with the tail number 'N702SK', which air carrier does it belong to?
|
SELECT T2.Description FROM Airlines AS T1 INNER JOIN `Air Carriers` AS T2 ON T1.OP_CARRIER_AIRLINE_ID = T2.Code WHERE T1.TAIL_NUM = 'N702SK' GROUP BY T2.Description
|
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"'",
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"?"
] |
[
{
"id": 5,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 2,
"type": "table",
"value": "Air Carriers"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "table",
"value": "airlines"
},
{
"id": 3,
"type": "column",
"value": "tail_num"
},
{
"id": 4,
"type": "value",
"value": "N702SK"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
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"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,458
|
aircraft
|
spider:train_spider.json:4818
|
What are the names and descriptions of aircrafts associated with an airport that has more total passengers than 10000000?
|
SELECT T1.Aircraft , T1.Description 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 T3.Total_Passengers > 10000000
|
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"that",
"has",
"more",
"total",
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"than",
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"?"
] |
[
{
"id": 3,
"type": "column",
"value": "total_passengers"
},
{
"id": 6,
"type": "table",
"value": "airport_aircraft"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 8,
"type": "column",
"value": "aircraft_id"
},
{
"id": 7,
"type": "column",
"value": "airport_id"
},
{
"id": 0,
"type": "column",
"value": "aircraft"
},
{
"id": 4,
"type": "value",
"value": "10000000"
},
{
"id": 5,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "table",
"value": "airport"
}
] |
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[
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"O",
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"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,459
|
mondial_geo
|
bird:train.json:8349
|
Which countries are dependent on the British Crown?
|
SELECT Country FROM politics WHERE Government = 'British crown dependency'
|
[
"Which",
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"on",
"the",
"British",
"Crown",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "British crown dependency"
},
{
"id": 2,
"type": "column",
"value": "government"
},
{
"id": 0,
"type": "table",
"value": "politics"
},
{
"id": 1,
"type": "column",
"value": "country"
}
] |
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},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,460
|
retails
|
bird:train.json:6705
|
How many orders were shipped in 1998?
|
SELECT COUNT(l_orderkey) FROM lineitem WHERE STRFTIME('%Y', l_shipdate) = '1998'
|
[
"How",
"many",
"orders",
"were",
"shipped",
"in",
"1998",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "l_orderkey"
},
{
"id": 4,
"type": "column",
"value": "l_shipdate"
},
{
"id": 0,
"type": "table",
"value": "lineitem"
},
{
"id": 1,
"type": "value",
"value": "1998"
},
{
"id": 3,
"type": "value",
"value": "%Y"
}
] |
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{
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{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,461
|
small_bank_1
|
spider:train_spider.json:1819
|
What are the names, checking balances, and savings balances of customers, ordered by the total of checking and savings balances descending?
|
SELECT T2.balance , T3.balance , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance DESC
|
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"total",
"of",
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"and",
"savings",
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"descending",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "accounts"
},
{
"id": 4,
"type": "table",
"value": "checking"
},
{
"id": 0,
"type": "column",
"value": "balance"
},
{
"id": 2,
"type": "table",
"value": "savings"
},
{
"id": 5,
"type": "column",
"value": "custid"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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{
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"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,462
|
customers_and_addresses
|
spider:train_spider.json:6106
|
What are the name and active date of the customers whose contact channel code is email?
|
SELECT t1.customer_name , t2.active_from_date FROM customers AS t1 JOIN customer_contact_channels AS t2 ON t1.customer_id = t2.customer_id WHERE t2.channel_code = 'Email'
|
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"active",
"date",
"of",
"the",
"customers",
"whose",
"contact",
"channel",
"code",
"is",
"email",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "customer_contact_channels"
},
{
"id": 1,
"type": "column",
"value": "active_from_date"
},
{
"id": 0,
"type": "column",
"value": "customer_name"
},
{
"id": 4,
"type": "column",
"value": "channel_code"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "value",
"value": "Email"
}
] |
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"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,463
|
hockey
|
bird:train.json:7732
|
How many players, whose shooting/catching hand is both left and right, debuted their first NHL in 2011?
|
SELECT COUNT(playerID) FROM Master WHERE shootCatch IS NULL AND firstNHL = '2011'
|
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",",
"whose",
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",",
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"?"
] |
[
{
"id": 2,
"type": "column",
"value": "shootcatch"
},
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "column",
"value": "firstnhl"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 4,
"type": "value",
"value": "2011"
}
] |
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"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,464
|
retail_complains
|
bird:train.json:299
|
How many male clients are from the state of Massachusetts?
|
SELECT COUNT(T3.sex) FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN client AS T3 ON T2.district_id = T3.district_id WHERE T1.state = 'Massachusetts' AND T3.sex = 'Male'
|
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"are",
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"Massachusetts",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Massachusetts"
},
{
"id": 9,
"type": "column",
"value": "state_abbrev"
},
{
"id": 4,
"type": "column",
"value": "district_id"
},
{
"id": 8,
"type": "column",
"value": "statecode"
},
{
"id": 3,
"type": "table",
"value": "district"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 2,
"type": "table",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "state"
},
{
"id": 7,
"type": "value",
"value": "Male"
},
{
"id": 1,
"type": "column",
"value": "sex"
}
] |
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{
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"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,465
|
talkingdata
|
bird:train.json:1107
|
List at least 10 device models that male users over the age of 39 usually use.
|
SELECT T1.device_model FROM phone_brand_device_model2 AS T1 INNER JOIN gender_age AS T2 ON T1.device_id = T2.device_id WHERE T2.`group` = 'M39+' AND T2.gender = 'M' LIMIT 10
|
[
"List",
"at",
"least",
"10",
"device",
"models",
"that",
"male",
"users",
"over",
"the",
"age",
"of",
"39",
"usually",
"use",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 0,
"type": "column",
"value": "device_model"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 3,
"type": "column",
"value": "device_id"
},
{
"id": 6,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "group"
},
{
"id": 5,
"type": "value",
"value": "M39+"
},
{
"id": 7,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
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",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,466
|
social_media
|
bird:train.json:850
|
Please list all the cities from where tweets with neutral sentiments were posted.
|
SELECT DISTINCT T2.City FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE Sentiment = 0
|
[
"Please",
"list",
"all",
"the",
"cities",
"from",
"where",
"tweets",
"with",
"neutral",
"sentiments",
"were",
"posted",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "locationid"
},
{
"id": 3,
"type": "column",
"value": "sentiment"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"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-COLUMN",
"O",
"O",
"O"
] |
1,467
|
election
|
spider:train_spider.json:2752
|
Show the lieutenant governor and comptroller from the democratic party.
|
SELECT Lieutenant_Governor , Comptroller FROM party WHERE Party = "Democratic"
|
[
"Show",
"the",
"lieutenant",
"governor",
"and",
"comptroller",
"from",
"the",
"democratic",
"party",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "lieutenant_governor"
},
{
"id": 2,
"type": "column",
"value": "comptroller"
},
{
"id": 4,
"type": "column",
"value": "Democratic"
},
{
"id": 0,
"type": "table",
"value": "party"
},
{
"id": 3,
"type": "column",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"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",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
1,468
|
customers_card_transactions
|
spider:train_spider.json:698
|
How many customer cards are there?
|
SELECT count(*) FROM Customers_cards
|
[
"How",
"many",
"customer",
"cards",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customers_cards"
}
] |
[
{
"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": []
},
{
"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",
"I-TABLE",
"O",
"O",
"O"
] |
1,469
|
products_gen_characteristics
|
spider:train_spider.json:5594
|
What is the characteristic name used by most number of the products?
|
SELECT t3.characteristic_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id GROUP BY t3.characteristic_name ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"characteristic",
"name",
"used",
"by",
"most",
"number",
"of",
"the",
"products",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "product_characteristics"
},
{
"id": 0,
"type": "column",
"value": "characteristic_name"
},
{
"id": 4,
"type": "column",
"value": "characteristic_id"
},
{
"id": 1,
"type": "table",
"value": "characteristics"
},
{
"id": 5,
"type": "column",
"value": "product_id"
},
{
"id": 2,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,470
|
california_schools
|
bird:dev.json:29
|
When did the first-through-twelfth-grade school with the largest enrollment open?
|
SELECT T2.OpenDate FROM frpm AS T1 INNER JOIN schools AS T2 ON T1.CDSCode = T2.CDSCode ORDER BY T1.`Enrollment (K-12)` DESC LIMIT 1
|
[
"When",
"did",
"the",
"first",
"-",
"through",
"-",
"twelfth",
"-",
"grade",
"school",
"with",
"the",
"largest",
"enrollment",
"open",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Enrollment (K-12)"
},
{
"id": 0,
"type": "column",
"value": "opendate"
},
{
"id": 2,
"type": "table",
"value": "schools"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 1,
"type": "table",
"value": "frpm"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
1,471
|
world_development_indicators
|
bird:train.json:2246
|
What is the average value of Adolescent fertility rate in the country whose Alpha2Code is 1A?
|
SELECT CAST(SUM(T2.Value) AS REAL) * 100 / COUNT(T2.Year) FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.Alpha2Code = '1A' AND T2.IndicatorName = 'Adolescent fertility rate (births per 1,000 women ages 15-19)'
|
[
"What",
"is",
"the",
"average",
"value",
"of",
"Adolescent",
"fertility",
"rate",
"in",
"the",
"country",
"whose",
"Alpha2Code",
"is",
"1A",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Adolescent fertility rate (births per 1,000 women ages 15-19)"
},
{
"id": 5,
"type": "column",
"value": "indicatorname"
},
{
"id": 2,
"type": "column",
"value": "countrycode"
},
{
"id": 1,
"type": "table",
"value": "indicators"
},
{
"id": 3,
"type": "column",
"value": "alpha2code"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 9,
"type": "column",
"value": "value"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "1A"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6,
7,
8,
9,
10,
12,
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
4
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"B-VALUE",
"B-COLUMN",
"B-VALUE",
"B-VALUE",
"O"
] |
1,472
|
flight_1
|
spider:train_spider.json:355
|
Show the id and name of the aircraft with the maximum distance.
|
SELECT aid , name FROM Aircraft ORDER BY distance DESC LIMIT 1
|
[
"Show",
"the",
"i",
"d",
"and",
"name",
"of",
"the",
"aircraft",
"with",
"the",
"maximum",
"distance",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 3,
"type": "column",
"value": "distance"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "aid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,473
|
candidate_poll
|
spider:train_spider.json:2411
|
What are the names of people who have a height greater than 200 or less than 190?
|
SELECT name FROM people WHERE height > 200 OR height < 190
|
[
"What",
"are",
"the",
"names",
"of",
"people",
"who",
"have",
"a",
"height",
"greater",
"than",
"200",
"or",
"less",
"than",
"190",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "200"
},
{
"id": 4,
"type": "value",
"value": "190"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,474
|
shakespeare
|
bird:train.json:3031
|
Please name the latest historical work.
|
SELECT LongTitle FROM works WHERE GenreType = 'History' ORDER BY Date DESC LIMIT 1
|
[
"Please",
"name",
"the",
"latest",
"historical",
"work",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "longtitle"
},
{
"id": 2,
"type": "column",
"value": "genretype"
},
{
"id": 3,
"type": "value",
"value": "History"
},
{
"id": 0,
"type": "table",
"value": "works"
},
{
"id": 4,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"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-VALUE",
"B-TABLE",
"O"
] |
1,475
|
car_retails
|
bird:train.json:1608
|
Calculate the total quantity ordered for 18th Century Vintage Horse Carriage and the average price.
|
SELECT SUM(T2.quantityOrdered) , SUM(T2.quantityOrdered * T2.priceEach) / SUM(T2.quantityOrdered) FROM products AS T1 INNER JOIN orderdetails AS T2 ON T1.productCode = T2.productCode WHERE T1.productName = '18th Century Vintage Horse Carriage'
|
[
"Calculate",
"the",
"total",
"quantity",
"ordered",
"for",
"18th",
"Century",
"Vintage",
"Horse",
"Carriage",
"and",
"the",
"average",
"price",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "18th Century Vintage Horse Carriage"
},
{
"id": 4,
"type": "column",
"value": "quantityordered"
},
{
"id": 1,
"type": "table",
"value": "orderdetails"
},
{
"id": 2,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "productcode"
},
{
"id": 6,
"type": "column",
"value": "priceeach"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,476
|
codebase_community
|
bird:dev.json:599
|
What are the post history type IDs for post ID 3720 and how many unique users have commented on the post?
|
SELECT T1.PostHistoryTypeId, (SELECT COUNT(DISTINCT UserId) FROM comments WHERE PostId = 3720) AS NumberOfUsers FROM postHistory AS T1 WHERE T1.PostId = 3720
|
[
"What",
"are",
"the",
"post",
"history",
"type",
"IDs",
"for",
"post",
"ID",
"3720",
"and",
"how",
"many",
"unique",
"users",
"have",
"commented",
"on",
"the",
"post",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "posthistorytypeid"
},
{
"id": 0,
"type": "table",
"value": "posthistory"
},
{
"id": 4,
"type": "table",
"value": "comments"
},
{
"id": 2,
"type": "column",
"value": "postid"
},
{
"id": 5,
"type": "column",
"value": "userid"
},
{
"id": 3,
"type": "value",
"value": "3720"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,477
|
toxicology
|
bird:dev.json:303
|
How many double bonds does TR006 have and is it carcinogenic?
|
SELECT COUNT(T1.bond_id), T2.label FROM bond AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.bond_type = '=' AND T2.molecule_id = 'TR006' GROUP BY T2.label
|
[
"How",
"many",
"double",
"bonds",
"does",
"TR006",
"have",
"and",
"is",
"it",
"carcinogenic",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "molecule_id"
},
{
"id": 5,
"type": "column",
"value": "bond_type"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 3,
"type": "column",
"value": "bond_id"
},
{
"id": 0,
"type": "column",
"value": "label"
},
{
"id": 7,
"type": "value",
"value": "TR006"
},
{
"id": 1,
"type": "table",
"value": "bond"
},
{
"id": 6,
"type": "value",
"value": "="
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,478
|
movie_platform
|
bird:train.json:8
|
List all movie title rated in April 2020 from user who was a trialist.
|
SELECT T1.movie_title FROM movies AS T1 INNER JOIN ratings AS T2 ON T1.movie_id = T2.movie_id WHERE T2.user_trialist = 1 AND T2.rating_timestamp_utc LIKE '2020-04%'
|
[
"List",
"all",
"movie",
"title",
"rated",
"in",
"April",
"2020",
"from",
"user",
"who",
"was",
"a",
"trialist",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 4,
"type": "column",
"value": "user_trialist"
},
{
"id": 0,
"type": "column",
"value": "movie_title"
},
{
"id": 3,
"type": "column",
"value": "movie_id"
},
{
"id": 7,
"type": "value",
"value": "2020-04%"
},
{
"id": 2,
"type": "table",
"value": "ratings"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,479
|
address_1
|
bird:test.json:813
|
Show me the distance between Boston and Newark.
|
SELECT distance FROM Direct_distance AS T1 JOIN City AS T2 ON T1.city1_code = T2.city_code JOIN City AS T3 ON T1.city2_code = T3.city_code WHERE T2.city_name = "Boston" AND T3.city_name = "Newark"
|
[
"Show",
"me",
"the",
"distance",
"between",
"Boston",
"and",
"Newark",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "direct_distance"
},
{
"id": 3,
"type": "column",
"value": "city2_code"
},
{
"id": 8,
"type": "column",
"value": "city1_code"
},
{
"id": 4,
"type": "column",
"value": "city_code"
},
{
"id": 5,
"type": "column",
"value": "city_name"
},
{
"id": 0,
"type": "column",
"value": "distance"
},
{
"id": 6,
"type": "column",
"value": "Boston"
},
{
"id": 7,
"type": "column",
"value": "Newark"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
1,480
|
school_finance
|
spider:train_spider.json:1906
|
Show the names of schools with a total budget amount greater than 100 or a total endowment greater than 10.
|
SELECT T2.school_name FROM budget AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id JOIN endowment AS T3 ON T2.school_id = T3.school_id GROUP BY T2.school_name HAVING sum(T1.budgeted) > 100 OR sum(T3.amount) > 10
|
[
"Show",
"the",
"names",
"of",
"schools",
"with",
"a",
"total",
"budget",
"amount",
"greater",
"than",
"100",
"or",
"a",
"total",
"endowment",
"greater",
"than",
"10",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "school_name"
},
{
"id": 1,
"type": "table",
"value": "endowment"
},
{
"id": 4,
"type": "column",
"value": "school_id"
},
{
"id": 7,
"type": "column",
"value": "budgeted"
},
{
"id": 2,
"type": "table",
"value": "budget"
},
{
"id": 3,
"type": "table",
"value": "school"
},
{
"id": 8,
"type": "column",
"value": "amount"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
19
]
},
{
"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",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,481
|
retail_world
|
bird:train.json:6510
|
How many days was the fastest shipping of Berglunds snabbkp's order?
|
SELECT datediff(T2.ShippedDate, T2.OrderDate) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.CompanyName = 'Berglunds snabbkp' ORDER BY datediff(T2.ShippedDate, T2.OrderDate) LIMIT 1
|
[
"How",
"many",
"days",
"was",
"the",
"fastest",
"shipping",
"of",
"Berglunds",
"snabbkp",
"'s",
"order",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Berglunds snabbkp"
},
{
"id": 2,
"type": "column",
"value": "companyname"
},
{
"id": 4,
"type": "column",
"value": "shippeddate"
},
{
"id": 6,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "column",
"value": "orderdate"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"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,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
1,482
|
public_review_platform
|
bird:train.json:4040
|
Does the length of the tip influence the number of likes for hotel and travel business category?
|
SELECT T3.tip_length, SUM(T3.likes) AS likes FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Tips AS T3 ON T2.business_id = T3.business_id WHERE T1.category_name = 'Hotels & Travel' GROUP BY T3.tip_length
|
[
"Does",
"the",
"length",
"of",
"the",
"tip",
"influence",
"the",
"number",
"of",
"likes",
"for",
"hotel",
"and",
"travel",
"business",
"category",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "business_categories"
},
{
"id": 3,
"type": "value",
"value": "Hotels & Travel"
},
{
"id": 2,
"type": "column",
"value": "category_name"
},
{
"id": 7,
"type": "column",
"value": "business_id"
},
{
"id": 8,
"type": "column",
"value": "category_id"
},
{
"id": 0,
"type": "column",
"value": "tip_length"
},
{
"id": 5,
"type": "table",
"value": "categories"
},
{
"id": 4,
"type": "column",
"value": "likes"
},
{
"id": 1,
"type": "table",
"value": "tips"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"B-TABLE",
"O"
] |
1,483
|
california_schools
|
bird:dev.json:39
|
What is the average number of test takers from Fresno schools that opened between 1/1/1980 and 12/31/1980?
|
SELECT AVG(T1.NumTstTakr) FROM satscores AS T1 INNER JOIN schools AS T2 ON T1.cds = T2.CDSCode WHERE strftime('%Y', T2.OpenDate) = '1980' AND T2.County = 'Fresno'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"test",
"takers",
"from",
"Fresno",
"schools",
"that",
"opened",
"between",
"1/1/1980",
"and",
"12/31/1980",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "numtsttakr"
},
{
"id": 0,
"type": "table",
"value": "satscores"
},
{
"id": 9,
"type": "column",
"value": "opendate"
},
{
"id": 1,
"type": "table",
"value": "schools"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 6,
"type": "column",
"value": "county"
},
{
"id": 7,
"type": "value",
"value": "Fresno"
},
{
"id": 5,
"type": "value",
"value": "1980"
},
{
"id": 3,
"type": "column",
"value": "cds"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
12
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,484
|
video_game
|
bird:test.json:1972
|
What are the titles of games not played by any players who play the Guard position?
|
SELECT Title FROM game EXCEPT SELECT T1.Title FROM game AS T1 JOIN game_player AS T2 ON T1.Game_ID = T2.Game_ID JOIN player AS T3 ON T2.Player_ID = T3.Player_ID WHERE T3.Position = "Guard"
|
[
"What",
"are",
"the",
"titles",
"of",
"games",
"not",
"played",
"by",
"any",
"players",
"who",
"play",
"the",
"Guard",
"position",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "game_player"
},
{
"id": 6,
"type": "column",
"value": "player_id"
},
{
"id": 3,
"type": "column",
"value": "position"
},
{
"id": 7,
"type": "column",
"value": "game_id"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "Guard"
},
{
"id": 0,
"type": "table",
"value": "game"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
1,485
|
behavior_monitoring
|
spider:train_spider.json:3109
|
Find the id and city of the student address with the highest average monthly rental.
|
SELECT T2.address_id , T1.city FROM Addresses AS T1 JOIN Student_Addresses AS T2 ON T1.address_id = T2.address_id GROUP BY T2.address_id ORDER BY AVG(monthly_rental) DESC LIMIT 1
|
[
"Find",
"the",
"i",
"d",
"and",
"city",
"of",
"the",
"student",
"address",
"with",
"the",
"highest",
"average",
"monthly",
"rental",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "student_addresses"
},
{
"id": 4,
"type": "column",
"value": "monthly_rental"
},
{
"id": 0,
"type": "column",
"value": "address_id"
},
{
"id": 2,
"type": "table",
"value": "addresses"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
14,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,486
|
entertainment_awards
|
spider:train_spider.json:4604
|
What are the names of festivals held in year 2007?
|
SELECT Festival_Name FROM festival_detail WHERE YEAR = 2007
|
[
"What",
"are",
"the",
"names",
"of",
"festivals",
"held",
"in",
"year",
"2007",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "festival_detail"
},
{
"id": 1,
"type": "column",
"value": "festival_name"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2007"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,487
|
university_rank
|
bird:test.json:1759
|
Show name, city, and state for all universities in alphabetical order of university name.
|
SELECT university_name , city , state FROM University ORDER BY university_name
|
[
"Show",
"name",
",",
"city",
",",
"and",
"state",
"for",
"all",
"universities",
"in",
" ",
"alphabetical",
"order",
"of",
"university",
"name",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "university_name"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,488
|
food_inspection_2
|
bird:train.json:6210
|
Name the food businesses that passed the inspection in 2010.
|
SELECT DISTINCT T1.dba_name FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE strftime('%Y', T2.inspection_date) = '2010' AND T2.results = 'Pass' AND T1.facility_type = 'Liquor'
|
[
"Name",
"the",
"food",
"businesses",
"that",
"passed",
"the",
"inspection",
"in",
"2010",
"."
] |
[
{
"id": 10,
"type": "column",
"value": "inspection_date"
},
{
"id": 1,
"type": "table",
"value": "establishment"
},
{
"id": 7,
"type": "column",
"value": "facility_type"
},
{
"id": 2,
"type": "table",
"value": "inspection"
},
{
"id": 3,
"type": "column",
"value": "license_no"
},
{
"id": 0,
"type": "column",
"value": "dba_name"
},
{
"id": 5,
"type": "column",
"value": "results"
},
{
"id": 8,
"type": "value",
"value": "Liquor"
},
{
"id": 4,
"type": "value",
"value": "2010"
},
{
"id": 6,
"type": "value",
"value": "Pass"
},
{
"id": 9,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
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{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,490
|
address
|
bird:train.json:5101
|
In California, how many delivery receptacles are there in the community post office that has the highest number of delivery receptacles?
|
SELECT COUNT(*) FROM state AS T1 INNER JOIN zip_data AS T2 ON T1.abbreviation = T2.state WHERE T1.abbreviation = 'CA' AND T2.type LIKE '%Community Post Office%' AND T1.name = 'California' AND T2.state = 'CA'
|
[
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"California",
",",
"how",
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"delivery",
"receptacles",
"are",
"there",
"in",
"the",
"community",
"post",
"office",
"that",
"has",
"the",
"highest",
"number",
"of",
"delivery",
"receptacles",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "%Community Post Office%"
},
{
"id": 2,
"type": "column",
"value": "abbreviation"
},
{
"id": 8,
"type": "value",
"value": "California"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 0,
"type": "table",
"value": "state"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "type"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "CA"
}
] |
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"entity_id": 0,
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"entity_id": 1,
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{
"entity_id": 2,
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{
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{
"entity_id": 18,
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{
"entity_id": 19,
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}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,491
|
public_review_platform
|
bird:train.json:3801
|
How many businesses with the category are open from Monday to Thursday?
|
SELECT COUNT(T2.business_id) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id INNER JOIN Business_Hours AS T4 ON T3.business_id = T4.business_id INNER JOIN Days AS T5 ON T4.day_id = T5.day_id WHERE T5.day_of_week LIKE 'Monday' OR T5.day_of_week LIKE 'Tuesday' OR T5.day_of_week LIKE 'Wednesday' OR T5.day_of_week LIKE 'Thursday'
|
[
"How",
"many",
"businesses",
"with",
"the",
"category",
"are",
"open",
"from",
"Monday",
"to",
"Thursday",
"?"
] |
[
{
"id": 11,
"type": "table",
"value": "business_categories"
},
{
"id": 2,
"type": "table",
"value": "business_hours"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 4,
"type": "column",
"value": "day_of_week"
},
{
"id": 12,
"type": "column",
"value": "category_id"
},
{
"id": 10,
"type": "table",
"value": "categories"
},
{
"id": 7,
"type": "value",
"value": "Wednesday"
},
{
"id": 8,
"type": "value",
"value": "Thursday"
},
{
"id": 9,
"type": "table",
"value": "business"
},
{
"id": 6,
"type": "value",
"value": "Tuesday"
},
{
"id": 3,
"type": "column",
"value": "day_id"
},
{
"id": 5,
"type": "value",
"value": "Monday"
},
{
"id": 0,
"type": "table",
"value": "days"
}
] |
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2
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},
{
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{
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,492
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4246
|
Show the ids of all employees who don't destroy any document.
|
SELECT employee_id FROM Employees EXCEPT SELECT Destroyed_by_Employee_ID FROM Documents_to_be_destroyed
|
[
"Show",
"the",
"ids",
"of",
"all",
"employees",
"who",
"do",
"n't",
"destroy",
"any",
"document",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "documents_to_be_destroyed"
},
{
"id": 3,
"type": "column",
"value": "destroyed_by_employee_id"
},
{
"id": 2,
"type": "column",
"value": "employee_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
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7,
8,
9
]
},
{
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},
{
"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",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
1,493
|
cars
|
bird:train.json:3097
|
Which Dodge car is the cheapest?
|
SELECT T1.car_name FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.car_name LIKE 'dodge%' ORDER BY T2.price ASC LIMIT 1
|
[
"Which",
"Dodge",
"car",
"is",
"the",
"cheapest",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "car_name"
},
{
"id": 3,
"type": "value",
"value": "dodge%"
},
{
"id": 2,
"type": "table",
"value": "price"
},
{
"id": 4,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "data"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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1
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},
{
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},
{
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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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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"O",
"O",
"O",
"O"
] |
1,494
|
driving_school
|
spider:train_spider.json:6692
|
List the number of customers that did not have any payment history.
|
SELECT count(*) FROM Customers WHERE customer_id NOT IN ( SELECT customer_id FROM Customer_Payments );
|
[
"List",
"the",
"number",
"of",
"customers",
"that",
"did",
"not",
"have",
"any",
"payment",
"history",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "customer_payments"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"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": []
},
{
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},
{
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"token_idxs": []
},
{
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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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,495
|
formula_1
|
bird:dev.json:987
|
What is the average fastest lap time of the top 10 drivers in the 2006 United States Grand Prix?
|
SELECT AVG(T1.fastestLapTime) FROM results AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId WHERE T1.rank < 11 AND T2.year = 2006 AND T2.name = 'United States Grand Prix'
|
[
"What",
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"the",
"average",
"fastest",
"lap",
"time",
"of",
"the",
"top",
"10",
"drivers",
"in",
"the",
"2006",
"United",
"States",
"Grand",
"Prix",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "United States Grand Prix"
},
{
"id": 2,
"type": "column",
"value": "fastestlaptime"
},
{
"id": 0,
"type": "table",
"value": "results"
},
{
"id": 3,
"type": "column",
"value": "raceid"
},
{
"id": 1,
"type": "table",
"value": "races"
},
{
"id": 4,
"type": "column",
"value": "rank"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2006"
},
{
"id": 8,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "value",
"value": "11"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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4,
5,
6
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
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},
{
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},
{
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14
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},
{
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{
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15,
16,
18
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},
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{
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"token_idxs": []
},
{
"entity_id": 13,
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,496
|
legislator
|
bird:train.json:4787
|
Which state did Veronica Grace Boland represent and which party is she affiliated?
|
SELECT T2.state, T2.party FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T1.first_name OR T1.middle_name OR T1.last_name = 'VeronicaGraceBoland'
|
[
"Which",
"state",
"did",
"Veronica",
"Grace",
"Boland",
"represent",
"and",
"which",
"party",
"is",
"she",
"affiliated",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "VeronicaGraceBoland"
},
{
"id": 3,
"type": "table",
"value": "historical-terms"
},
{
"id": 5,
"type": "column",
"value": "middle_name"
},
{
"id": 6,
"type": "column",
"value": "bioguide_id"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "last_name"
},
{
"id": 7,
"type": "column",
"value": "bioguide"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "column",
"value": "party"
}
] |
[
{
"entity_id": 0,
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1
]
},
{
"entity_id": 1,
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9
]
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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3,
4,
5
]
},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,497
|
formula_1
|
bird:dev.json:851
|
Please list the positions of the circuits built by the constructor Renault.
|
SELECT DISTINCT T1.position FROM constructorStandings AS T1 INNER JOIN constructors AS T2 ON T2.constructorId = T1.constructorId WHERE T2.name = 'Renault'
|
[
"Please",
"list",
"the",
"positions",
"of",
"the",
"circuits",
"built",
"by",
"the",
"constructor",
"Renault",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "constructorstandings"
},
{
"id": 5,
"type": "column",
"value": "constructorid"
},
{
"id": 2,
"type": "table",
"value": "constructors"
},
{
"id": 0,
"type": "column",
"value": "position"
},
{
"id": 4,
"type": "value",
"value": "Renault"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
1,498
|
cre_Theme_park
|
spider:train_spider.json:5915
|
What are the details and opening hours of the museums?
|
SELECT T1.Museum_Details , T2.Opening_Hours FROM MUSEUMS AS T1 JOIN TOURIST_ATTRACTIONS AS T2 ON T1.Museum_ID = T2.Tourist_Attraction_ID
|
[
"What",
"are",
"the",
"details",
"and",
"opening",
"hours",
"of",
"the",
"museums",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "tourist_attraction_id"
},
{
"id": 3,
"type": "table",
"value": "tourist_attractions"
},
{
"id": 0,
"type": "column",
"value": "museum_details"
},
{
"id": 1,
"type": "column",
"value": "opening_hours"
},
{
"id": 4,
"type": "column",
"value": "museum_id"
},
{
"id": 2,
"type": "table",
"value": "museums"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,499
|
retail_world
|
bird:train.json:6613
|
Name the products where the suppliers come from Finland.
|
SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.Country = 'Finland'
|
[
"Name",
"the",
"products",
"where",
"the",
"suppliers",
"come",
"from",
"Finland",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "Finland"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,500
|
bike_share_1
|
bird:train.json:9090
|
Which city is Townsend at 7th Station located and how many bikes could it hold?
|
SELECT city, SUM(dock_count) FROM station WHERE name = 'Townsend at 7th'
|
[
"Which",
"city",
"is",
"Townsend",
"at",
"7th",
"Station",
"located",
"and",
"how",
"many",
"bikes",
"could",
"it",
"hold",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Townsend at 7th"
},
{
"id": 4,
"type": "column",
"value": "dock_count"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,501
|
real_estate_rentals
|
bird:test.json:1469
|
What are the last names and ids of users who have searched two or fewer times, and own two or more properties?
|
SELECT T1.last_name , T1.user_id FROM Users AS T1 JOIN User_Searches AS T2 ON T1.user_id = T2.user_id GROUP BY T1.user_id HAVING count(*) <= 2 INTERSECT SELECT T3.last_name , T3.user_id FROM Users AS T3 JOIN Properties AS T4 ON T3.user_id = T4.owner_user_id GROUP BY T3.user_id HAVING count(*) >= 2;
|
[
"What",
"are",
"the",
"last",
"names",
"and",
"ids",
"of",
"users",
"who",
"have",
"searched",
"two",
"or",
"fewer",
"times",
",",
"and",
"own",
"two",
"or",
"more",
"properties",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "user_searches"
},
{
"id": 6,
"type": "column",
"value": "owner_user_id"
},
{
"id": 5,
"type": "table",
"value": "properties"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 2,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
22
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
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