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16.1k
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13,690
|
soccer_2016
|
bird:train.json:1898
|
In the players, how many were out by hit wicket?
|
SELECT Player_Out FROM Wicket_Taken AS T1 INNER JOIN Out_Type AS T2 ON T1.Kind_Out = T2.Out_Id WHERE Out_Name = 'hit wicket'
|
[
"In",
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"players",
",",
"how",
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"were",
"out",
"by",
"hit",
"wicket",
"?"
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[
{
"id": 1,
"type": "table",
"value": "wicket_taken"
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{
"id": 0,
"type": "column",
"value": "player_out"
},
{
"id": 4,
"type": "value",
"value": "hit wicket"
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{
"id": 2,
"type": "table",
"value": "out_type"
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{
"id": 3,
"type": "column",
"value": "out_name"
},
{
"id": 5,
"type": "column",
"value": "kind_out"
},
{
"id": 6,
"type": "column",
"value": "out_id"
}
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"B-COLUMN",
"O",
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"O"
] |
13,691
|
sakila_1
|
spider:train_spider.json:2975
|
Return the address of store 1.
|
SELECT T2.address FROM store AS T1 JOIN address AS T2 ON T1.address_id = T2.address_id WHERE store_id = 1
|
[
"Return",
"the",
"address",
"of",
"store",
"1",
"."
] |
[
{
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"O",
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13,693
|
retail_complains
|
bird:train.json:258
|
What was the serve time for the complaint call from client "C00007127" on 2017/2/22?
|
SELECT T1.ser_time FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.Client_ID = 'C00007127' AND T1.`Date received` = '2017-02-22'
|
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"\"",
"C00007127",
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"2017/2/22",
"?"
] |
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{
"id": 1,
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{
"id": 6,
"type": "column",
"value": "Date received"
},
{
"id": 3,
"type": "column",
"value": "Complaint ID"
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{
"id": 7,
"type": "value",
"value": "2017-02-22"
},
{
"id": 4,
"type": "column",
"value": "client_id"
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{
"id": 5,
"type": "value",
"value": "C00007127"
},
{
"id": 0,
"type": "column",
"value": "ser_time"
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{
"id": 2,
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"value": "events"
}
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"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
13,694
|
bike_1
|
spider:train_spider.json:154
|
What zip codes have a station with a max temperature greater than or equal to 80 and when did it reach that temperature?
|
SELECT date , zip_code FROM weather WHERE max_temperature_f >= 80
|
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] |
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{
"id": 3,
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{
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{
"id": 1,
"type": "column",
"value": "date"
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{
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"value": "80"
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"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,695
|
car_racing
|
bird:test.json:1602
|
Which make has more than one team?
|
SELECT make FROM team GROUP BY team HAVING count(*) > 1
|
[
"Which",
"make",
"has",
"more",
"than",
"one",
"team",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "team"
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{
"id": 1,
"type": "column",
"value": "team"
},
{
"id": 2,
"type": "column",
"value": "make"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
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"O",
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"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,696
|
olympics
|
bird:train.json:4943
|
What are the names of the events under Art Competitions?
|
SELECT T2.event_name FROM sport AS T1 INNER JOIN event AS T2 ON T1.id = T2.sport_id WHERE T1.sport_name = 'Art Competitions'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"events",
"under",
"Art",
"Competitions",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Art Competitions"
},
{
"id": 0,
"type": "column",
"value": "event_name"
},
{
"id": 3,
"type": "column",
"value": "sport_name"
},
{
"id": 6,
"type": "column",
"value": "sport_id"
},
{
"id": 1,
"type": "table",
"value": "sport"
},
{
"id": 2,
"type": "table",
"value": "event"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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"O",
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"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
13,698
|
store_1
|
spider:train_spider.json:569
|
List Aerosmith's albums.
|
SELECT T1.title FROM albums AS T1 JOIN artists AS T2 ON T1.artist_id = T2.id WHERE T2.name = "Aerosmith";
|
[
"List",
"Aerosmith",
"'s",
"albums",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "Aerosmith"
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{
"id": 5,
"type": "column",
"value": "artist_id"
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{
"id": 2,
"type": "table",
"value": "artists"
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{
"id": 1,
"type": "table",
"value": "albums"
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{
"id": 0,
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"value": "title"
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{
"id": 3,
"type": "column",
"value": "name"
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{
"id": 6,
"type": "column",
"value": "id"
}
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[
"O",
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"O"
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13,699
|
ice_hockey_draft
|
bird:train.json:6971
|
Who among the players in season 2000-2001 has committed the highest rule violations or penalty minutes?
|
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2000-2001' ORDER BY T1.PIM DESC LIMIT 1
|
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"-",
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"?"
] |
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{
"id": 1,
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{
"id": 0,
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"value": "playername"
},
{
"id": 2,
"type": "table",
"value": "playerinfo"
},
{
"id": 4,
"type": "value",
"value": "2000-2001"
},
{
"id": 6,
"type": "column",
"value": "eliteid"
},
{
"id": 3,
"type": "column",
"value": "season"
},
{
"id": 5,
"type": "column",
"value": "pim"
}
] |
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,700
|
hospital_1
|
spider:train_spider.json:3927
|
Find the name of the nurse who has the largest number of appointments.
|
SELECT T1.name FROM nurse AS T1 JOIN appointment AS T2 ON T1.employeeid = T2.prepnurse GROUP BY T1.employeeid ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
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"number",
"of",
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"."
] |
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{
"id": 3,
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{
"id": 0,
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{
"id": 4,
"type": "column",
"value": "prepnurse"
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{
"id": 2,
"type": "table",
"value": "nurse"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,701
|
county_public_safety
|
spider:train_spider.json:2559
|
What are the crime rates of counties that contain cities that have white percentages of over 90?
|
SELECT T2.Crime_rate FROM city AS T1 JOIN county_public_safety AS T2 ON T1.County_ID = T2.County_ID WHERE T1.White > 90
|
[
"What",
"are",
"the",
"crime",
"rates",
"of",
"counties",
"that",
"contain",
"cities",
"that",
"have",
"white",
"percentages",
"of",
"over",
"90",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "county_public_safety"
},
{
"id": 0,
"type": "column",
"value": "crime_rate"
},
{
"id": 5,
"type": "column",
"value": "county_id"
},
{
"id": 3,
"type": "column",
"value": "white"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "90"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,702
|
address
|
bird:train.json:5223
|
How many postal points are there under the congress representative in Puerto Rico?
|
SELECT COUNT(T2.zip_code) FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.state = 'Puerto Rico'
|
[
"How",
"many",
"postal",
"points",
"are",
"there",
"under",
"the",
"congress",
"representative",
"in",
"Puerto",
"Rico",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "cognress_rep_id"
},
{
"id": 1,
"type": "table",
"value": "zip_congress"
},
{
"id": 3,
"type": "value",
"value": "Puerto Rico"
},
{
"id": 0,
"type": "table",
"value": "congress"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 6,
"type": "column",
"value": "district"
},
{
"id": 2,
"type": "column",
"value": "state"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,703
|
movielens
|
bird:train.json:2285
|
Please list the genre of the movies that are directed by the directors with the highest level of average revenue.
|
SELECT T2.genre FROM directors AS T1 INNER JOIN movies2directors AS T2 ON T1.directorid = T2.directorid WHERE T1.avg_revenue = 4
|
[
"Please",
"list",
"the",
"genre",
"of",
"the",
"movies",
"that",
"are",
"directed",
"by",
"the",
"directors",
"with",
"the",
"highest",
"level",
"of",
"average",
"revenue",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "movies2directors"
},
{
"id": 3,
"type": "column",
"value": "avg_revenue"
},
{
"id": 5,
"type": "column",
"value": "directorid"
},
{
"id": 1,
"type": "table",
"value": "directors"
},
{
"id": 0,
"type": "column",
"value": "genre"
},
{
"id": 4,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,704
|
university
|
bird:train.json:8078
|
What is the name of the university with the highest score in teaching in the year 2011?
|
SELECT T3.university_name FROM ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id INNER JOIN university AS T3 ON T3.id = T2.university_id WHERE T1.criteria_name = 'Teaching' AND T2.year = 2011 ORDER BY T2.score DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"university",
"with",
"the",
"highest",
"score",
"in",
"teaching",
"in",
"the",
"year",
"2011",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 11,
"type": "column",
"value": "ranking_criteria_id"
},
{
"id": 3,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 6,
"type": "column",
"value": "university_id"
},
{
"id": 7,
"type": "column",
"value": "criteria_name"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 8,
"type": "value",
"value": "Teaching"
},
{
"id": 2,
"type": "column",
"value": "score"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "2011"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
1,
2,
3
]
},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": [
16
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,705
|
retails
|
bird:train.json:6710
|
When was the order with the highest amount of total price shipped?
|
SELECT T2.l_shipdate FROM orders AS T1 INNER JOIN lineitem AS T2 ON T1.o_orderkey = T2.l_orderkey ORDER BY T1.o_totalprice DESC LIMIT 1
|
[
"When",
"was",
"the",
"order",
"with",
"the",
"highest",
"amount",
"of",
"total",
"price",
"shipped",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "o_totalprice"
},
{
"id": 0,
"type": "column",
"value": "l_shipdate"
},
{
"id": 4,
"type": "column",
"value": "o_orderkey"
},
{
"id": 5,
"type": "column",
"value": "l_orderkey"
},
{
"id": 2,
"type": "table",
"value": "lineitem"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
13,706
|
bakery_1
|
bird:test.json:1504
|
Count the number of types of cake this bakery sells.
|
SELECT count(*) FROM goods WHERE food = "Cake"
|
[
"Count",
"the",
"number",
"of",
"types",
"of",
"cake",
"this",
"bakery",
"sells",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 1,
"type": "column",
"value": "food"
},
{
"id": 2,
"type": "column",
"value": "Cake"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,707
|
formula_1
|
bird:dev.json:975
|
Which year has the lowest speed of lap time?
|
SELECT T2.year FROM lapTimes AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId ORDER BY T1.time DESC LIMIT 1
|
[
"Which",
"year",
"has",
"the",
"lowest",
"speed",
"of",
"lap",
"time",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laptimes"
},
{
"id": 4,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 0,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "column",
"value": "time"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,708
|
movies_4
|
bird:train.json:475
|
List all companies who worked in the movie 'Ultramarines: A Warhammer 40,000 Movie.'
|
SELECT T1.company_name FROM production_company AS T1 INNER JOIN movie_company AS T2 ON T1.company_id = T2.company_id INNER JOIN movie AS T3 ON T2.movie_id = T3.movie_id WHERE T3.title = 'Ultramarines: A Warhammer 40,000 Movie'
|
[
"List",
"all",
"companies",
"who",
"worked",
"in",
"the",
"movie",
"'",
"Ultramarines",
":",
"A",
"Warhammer",
"40,000",
"Movie",
".",
"'"
] |
[
{
"id": 3,
"type": "value",
"value": "Ultramarines: A Warhammer 40,000 Movie"
},
{
"id": 4,
"type": "table",
"value": "production_company"
},
{
"id": 5,
"type": "table",
"value": "movie_company"
},
{
"id": 0,
"type": "column",
"value": "company_name"
},
{
"id": 7,
"type": "column",
"value": "company_id"
},
{
"id": 6,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "movie"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O"
] |
13,709
|
shop_membership
|
spider:train_spider.json:5429
|
What is the name and opening year for the branch that registered the most members in 2016?
|
SELECT T2.name , T2.open_year FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year = 2016 GROUP BY T2.branch_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"and",
"opening",
"year",
"for",
"the",
"branch",
"that",
"registered",
"the",
"most",
"members",
"in",
"2016",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "membership_register_branch"
},
{
"id": 5,
"type": "column",
"value": "register_year"
},
{
"id": 0,
"type": "column",
"value": "branch_id"
},
{
"id": 2,
"type": "column",
"value": "open_year"
},
{
"id": 4,
"type": "table",
"value": "branch"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "2016"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,710
|
retail_world
|
bird:train.json:6411
|
What is the name of the contact person of the Pavlova supplier company?
|
SELECT T2.ContactName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ProductName = 'Pavlova'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"contact",
"person",
"of",
"the",
"Pavlova",
"supplier",
"company",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "contactname"
},
{
"id": 3,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 4,
"type": "value",
"value": "Pavlova"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"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,
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},
{
"entity_id": 9,
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O"
] |
13,711
|
app_store
|
bird:train.json:2551
|
List out genre that have downloads more than 1000000000.
|
SELECT Genres FROM playstore WHERE Installs = '1,000,000,000+' GROUP BY Genres
|
[
"List",
"out",
"genre",
"that",
"have",
"downloads",
"more",
"than",
"1000000000",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "1,000,000,000+"
},
{
"id": 0,
"type": "table",
"value": "playstore"
},
{
"id": 2,
"type": "column",
"value": "installs"
},
{
"id": 1,
"type": "column",
"value": "genres"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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,
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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",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,712
|
retails
|
bird:train.json:6852
|
Among the providers in Argentina, which supplier has an account that is in debt?
|
SELECT T1.s_name FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey WHERE T1.s_acctbal < 0 AND T2.n_name = 'ARGENTINA'
|
[
"Among",
"the",
"providers",
"in",
"Argentina",
",",
"which",
"supplier",
"has",
"an",
"account",
"that",
"is",
"in",
"debt",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "s_nationkey"
},
{
"id": 4,
"type": "column",
"value": "n_nationkey"
},
{
"id": 5,
"type": "column",
"value": "s_acctbal"
},
{
"id": 8,
"type": "value",
"value": "ARGENTINA"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 0,
"type": "column",
"value": "s_name"
},
{
"id": 2,
"type": "table",
"value": "nation"
},
{
"id": 7,
"type": "column",
"value": "n_name"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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7
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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4
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
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},
{
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},
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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-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,713
|
menu
|
bird:train.json:5546
|
How many menus include puree of split peas aux croutons?
|
SELECT SUM(CASE WHEN T1.name = 'Puree of split peas aux croutons' THEN 1 ELSE 0 END) FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id
|
[
"How",
"many",
"menus",
"include",
"puree",
"of",
"split",
"peas",
"aux",
"croutons",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Puree of split peas aux croutons"
},
{
"id": 1,
"type": "table",
"value": "menuitem"
},
{
"id": 3,
"type": "column",
"value": "dish_id"
},
{
"id": 0,
"type": "table",
"value": "dish"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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2
]
},
{
"entity_id": 2,
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},
{
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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4,
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6,
7,
8,
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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},
{
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},
{
"entity_id": 16,
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,714
|
movie_1
|
spider:train_spider.json:2527
|
What are the names of all movies made before 1980 or had James Cameron as the director?
|
SELECT title FROM Movie WHERE director = "James Cameron" OR YEAR < 1980
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"movies",
"made",
"before",
"1980",
"or",
"had",
"James",
"Cameron",
"as",
"the",
"director",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "James Cameron"
},
{
"id": 2,
"type": "column",
"value": "director"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "1980"
}
] |
[
{
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6
]
},
{
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},
{
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16
]
},
{
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12,
13
]
},
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{
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},
{
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{
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{
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{
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},
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},
{
"entity_id": 16,
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},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
13,715
|
boat_1
|
bird:test.json:903
|
Find the name, rating and age of all sailors ordered by rating and age.
|
SELECT name , rating , age FROM Sailors ORDER BY rating , age
|
[
"Find",
"the",
"name",
",",
"rating",
"and",
"age",
"of",
"all",
"sailors",
"ordered",
"by",
"rating",
"and",
"age",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "sailors"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,716
|
movie_3
|
bird:train.json:9203
|
How many films rented on 26th May, 2005 were returned on 30th May, 2005?
|
SELECT COUNT(DISTINCT rental_id) FROM rental WHERE date(rental_date) BETWEEN '2005-05-26' AND '2005-05-30'
|
[
"How",
"many",
"films",
"rented",
"on",
"26th",
"May",
",",
"2005",
"were",
"returned",
"on",
"30th",
"May",
",",
"2005",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "rental_date"
},
{
"id": 1,
"type": "value",
"value": "2005-05-26"
},
{
"id": 2,
"type": "value",
"value": "2005-05-30"
},
{
"id": 3,
"type": "column",
"value": "rental_id"
},
{
"id": 0,
"type": "table",
"value": "rental"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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},
{
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},
{
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},
{
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{
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{
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},
{
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},
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},
{
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},
{
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{
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{
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},
{
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},
{
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},
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,717
|
superhero
|
bird:dev.json:755
|
List down at least five full name of Demi-God superheroes.
|
SELECT T1.full_name FROM superhero AS T1 INNER JOIN race AS T2 ON T1.race_id = T2.id WHERE T2.race = 'Demi-God'
|
[
"List",
"down",
"at",
"least",
"five",
"full",
"name",
"of",
"Demi",
"-",
"God",
"superheroes",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "full_name"
},
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 4,
"type": "value",
"value": "Demi-God"
},
{
"id": 5,
"type": "column",
"value": "race_id"
},
{
"id": 2,
"type": "table",
"value": "race"
},
{
"id": 3,
"type": "column",
"value": "race"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
13,718
|
inn_1
|
spider:train_spider.json:2603
|
How many times the number of adults and kids staying in a room reached the maximum capacity of the room?
|
SELECT count(*) FROM Reservations AS T1 JOIN Rooms AS T2 ON T1.Room = T2.RoomId WHERE T2.maxOccupancy = T1.Adults + T1.Kids;
|
[
"How",
"many",
"times",
"the",
"number",
"of",
"adults",
"and",
"kids",
"staying",
"in",
"a",
"room",
"reached",
"the",
"maximum",
"capacity",
"of",
"the",
"room",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "reservations"
},
{
"id": 2,
"type": "column",
"value": "maxoccupancy"
},
{
"id": 4,
"type": "column",
"value": "roomid"
},
{
"id": 5,
"type": "column",
"value": "adults"
},
{
"id": 1,
"type": "table",
"value": "rooms"
},
{
"id": 3,
"type": "column",
"value": "room"
},
{
"id": 6,
"type": "column",
"value": "kids"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
19
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,719
|
manufactory_1
|
spider:train_spider.json:5318
|
Find the name of companies that do not make DVD drive.
|
SELECT name FROM manufacturers EXCEPT SELECT T2.name FROM products AS T1 JOIN manufacturers AS T2 ON T1.Manufacturer = T2.code WHERE T1.name = 'DVD drive'
|
[
"Find",
"the",
"name",
"of",
"companies",
"that",
"do",
"not",
"make",
"DVD",
"drive",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 4,
"type": "column",
"value": "manufacturer"
},
{
"id": 3,
"type": "value",
"value": "DVD drive"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,720
|
book_1
|
bird:test.json:536
|
What are all isbns for each book, and how many times has each been ordered?
|
SELECT isbn , count(*) FROM Books_Order GROUP BY isbn
|
[
"What",
"are",
"all",
"isbns",
"for",
"each",
"book",
",",
"and",
"how",
"many",
"times",
"has",
"each",
"been",
"ordered",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "books_order"
},
{
"id": 1,
"type": "column",
"value": "isbn"
}
] |
[
{
"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": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,721
|
works_cycles
|
bird:train.json:7193
|
Which sales person achieved the highest sales YTD? What is the projected yearly sales quota in 2011 for this person?
|
SELECT T1.BusinessEntityID, SUM(T1.SalesQuota) FROM SalesPerson AS T1 INNER JOIN SalesPersonQuotaHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE STRFTIME('%Y', T2.QuotaDate) = '2011' GROUP BY T1.BusinessEntityID ORDER BY SUM(T1.SalesYTD) DESC LIMIT 1
|
[
"Which",
"sales",
"person",
"achieved",
"the",
"highest",
"sales",
"YTD",
"?",
"What",
"is",
"the",
"projected",
"yearly",
"sales",
"quota",
"in",
"2011",
"for",
"this",
"person",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "salespersonquotahistory"
},
{
"id": 0,
"type": "column",
"value": "businessentityid"
},
{
"id": 1,
"type": "table",
"value": "salesperson"
},
{
"id": 4,
"type": "column",
"value": "salesquota"
},
{
"id": 6,
"type": "column",
"value": "quotadate"
},
{
"id": 7,
"type": "column",
"value": "salesytd"
},
{
"id": 3,
"type": "value",
"value": "2011"
},
{
"id": 5,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
6,
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",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
13,722
|
retails
|
bird:train.json:6823
|
How many part supplies are close to being out of stock?
|
SELECT COUNT(ps_suppkey) FROM partsupp WHERE ps_availqty < 10
|
[
"How",
"many",
"part",
"supplies",
"are",
"close",
"to",
"being",
"out",
"of",
"stock",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "ps_availqty"
},
{
"id": 3,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 0,
"type": "table",
"value": "partsupp"
},
{
"id": 2,
"type": "value",
"value": "10"
}
] |
[
{
"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",
"O",
"O",
"O",
"O",
"O"
] |
13,723
|
real_estate_rentals
|
bird:test.json:1429
|
Return the search strings and corresonding time stamps for all user searches, sorted by search string descending.
|
SELECT search_datetime , search_string FROM User_Searches ORDER BY search_string DESC;
|
[
"Return",
"the",
"search",
"strings",
"and",
"corresonding",
"time",
"stamps",
"for",
"all",
"user",
"searches",
",",
"sorted",
"by",
"search",
"string",
"descending",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "search_datetime"
},
{
"id": 0,
"type": "table",
"value": "user_searches"
},
{
"id": 2,
"type": "column",
"value": "search_string"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10,
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15,
16
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,724
|
social_media
|
bird:train.json:781
|
Please list all the cities in Argentina.
|
SELECT City FROM location WHERE City IS NOT NULL AND Country = 'Argentina'
|
[
"Please",
"list",
"all",
"the",
"cities",
"in",
"Argentina",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Argentina"
},
{
"id": 0,
"type": "table",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,725
|
hospital_1
|
spider:train_spider.json:3977
|
Compute the mean price of procedures physician John Wen was trained in.
|
SELECT avg(T3.cost) FROM physician AS T1 JOIN trained_in AS T2 ON T1.employeeid = T2.physician JOIN procedures AS T3 ON T3.code = T2.treatment WHERE T1.name = "John Wen"
|
[
"Compute",
"the",
"mean",
"price",
"of",
"procedures",
"physician",
"John",
"Wen",
"was",
"trained",
"in",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "procedures"
},
{
"id": 5,
"type": "table",
"value": "trained_in"
},
{
"id": 8,
"type": "column",
"value": "employeeid"
},
{
"id": 4,
"type": "table",
"value": "physician"
},
{
"id": 7,
"type": "column",
"value": "treatment"
},
{
"id": 9,
"type": "column",
"value": "physician"
},
{
"id": 2,
"type": "column",
"value": "John Wen"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "cost"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"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": [
1,
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
13,726
|
farm
|
spider:train_spider.json:21
|
Return the hosts of competitions for which the theme is not Aliens?
|
SELECT Hosts FROM farm_competition WHERE Theme != 'Aliens'
|
[
"Return",
"the",
"hosts",
"of",
"competitions",
"for",
"which",
"the",
"theme",
"is",
"not",
"Aliens",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "farm_competition"
},
{
"id": 3,
"type": "value",
"value": "Aliens"
},
{
"id": 1,
"type": "column",
"value": "hosts"
},
{
"id": 2,
"type": "column",
"value": "theme"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,727
|
retail_world
|
bird:train.json:6519
|
What is the total sales amount of all discontinued products?
|
SELECT SUM(T2.UnitPrice * T2.Quantity) FROM Products AS T1 INNER JOIN `Order Details` AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Discontinued = 1
|
[
"What",
"is",
"the",
"total",
"sales",
"amount",
"of",
"all",
"discontinued",
"products",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "Order Details"
},
{
"id": 2,
"type": "column",
"value": "discontinued"
},
{
"id": 4,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "column",
"value": "unitprice"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "quantity"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
13,728
|
language_corpus
|
bird:train.json:5774
|
How many words are there on the page titled "Asclepi"?
|
SELECT words FROM pages WHERE title = 'Asclepi'
|
[
"How",
"many",
"words",
"are",
"there",
"on",
"the",
"page",
"titled",
"\"",
"Asclepi",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Asclepi"
},
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 1,
"type": "column",
"value": "words"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
13,729
|
formula_1
|
spider:train_spider.json:2209
|
What are the drivers' last names and id who had 11 pit stops and participated in more than 5 race results?
|
SELECT T1.surname , T1.driverid FROM drivers AS T1 JOIN pitstops AS T2 ON T1.driverid = T2.driverid GROUP BY T1.driverid HAVING count(*) = 11 INTERSECT SELECT T1.surname , T1.driverid FROM drivers AS T1 JOIN results AS T2 ON T1.driverid = T2.driverid GROUP BY T1.driverid HAVING count(*) > 5
|
[
"What",
"are",
"the",
"drivers",
"'",
"last",
"names",
"and",
"i",
"d",
"who",
"had",
"11",
"pit",
"stops",
"and",
"participated",
"in",
"more",
"than",
"5",
"race",
"results",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "driverid"
},
{
"id": 3,
"type": "table",
"value": "pitstops"
},
{
"id": 1,
"type": "column",
"value": "surname"
},
{
"id": 2,
"type": "table",
"value": "drivers"
},
{
"id": 5,
"type": "table",
"value": "results"
},
{
"id": 4,
"type": "value",
"value": "11"
},
{
"id": 6,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13,
14
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
22
]
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O"
] |
13,730
|
movie_3
|
bird:train.json:9283
|
What is the average amount of rent that Christy Vargas paid?
|
SELECT AVG(T2.amount) FROM customer AS T1 INNER JOIN payment AS T2 ON T1.customer_id = T2.customer_id WHERE T1.first_name = 'CHRISTY' AND T1.Last_name = 'VARGAS'
|
[
"What",
"is",
"the",
"average",
"amount",
"of",
"rent",
"that",
"Christy",
"Vargas",
"paid",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "table",
"value": "payment"
},
{
"id": 5,
"type": "value",
"value": "CHRISTY"
},
{
"id": 2,
"type": "column",
"value": "amount"
},
{
"id": 7,
"type": "value",
"value": "VARGAS"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
13,731
|
movie_3
|
bird:train.json:9369
|
Give me the title and category name of films whose price per day is more than $30. Please include their special features.
|
SELECT T1.title, T3.name, T1.special_features FROM film AS T1 INNER JOIN film_category AS T2 ON T1.film_id = T2.film_id INNER JOIN category AS T3 ON T2.category_id = T3.category_id WHERE T1.rental_duration * T1.rental_rate > 30
|
[
"Give",
"me",
"the",
"title",
"and",
"category",
"name",
"of",
"films",
"whose",
"price",
"per",
"day",
"is",
"more",
"than",
"$",
"30",
".",
"Please",
"include",
"their",
"special",
"features",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "special_features"
},
{
"id": 8,
"type": "column",
"value": "rental_duration"
},
{
"id": 6,
"type": "table",
"value": "film_category"
},
{
"id": 7,
"type": "column",
"value": "category_id"
},
{
"id": 9,
"type": "column",
"value": "rental_rate"
},
{
"id": 3,
"type": "table",
"value": "category"
},
{
"id": 10,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "table",
"value": "film"
},
{
"id": 4,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
22,
23
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,732
|
car_road_race
|
bird:test.json:1322
|
What are the distinct entrant types of drivers aged 20 or older?
|
SELECT DISTINCT Entrant FROM driver WHERE Age >= 20
|
[
"What",
"are",
"the",
"distinct",
"entrant",
"types",
"of",
"drivers",
"aged",
"20",
"or",
"older",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "entrant"
},
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O"
] |
13,733
|
superhero
|
bird:dev.json:843
|
List the hero ID of superheroes have intellegence as their power.
|
SELECT T1.hero_id FROM hero_power AS T1 INNER JOIN superpower AS T2 ON T1.power_id = T2.id WHERE T2.power_name = 'Intelligence'
|
[
"List",
"the",
"hero",
"ID",
"of",
"superheroes",
"have",
"intellegence",
"as",
"their",
"power",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Intelligence"
},
{
"id": 1,
"type": "table",
"value": "hero_power"
},
{
"id": 2,
"type": "table",
"value": "superpower"
},
{
"id": 3,
"type": "column",
"value": "power_name"
},
{
"id": 5,
"type": "column",
"value": "power_id"
},
{
"id": 0,
"type": "column",
"value": "hero_id"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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9
]
},
{
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5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,734
|
olympics
|
bird:train.json:5055
|
In Barcelona, how many Olympic games were held?
|
SELECT COUNT(T1.games_id) FROM games_city AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.id WHERE T2.city_name = 'Barcelona'
|
[
"In",
"Barcelona",
",",
"how",
"many",
"Olympic",
"games",
"were",
"held",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "games_city"
},
{
"id": 2,
"type": "column",
"value": "city_name"
},
{
"id": 3,
"type": "value",
"value": "Barcelona"
},
{
"id": 4,
"type": "column",
"value": "games_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"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
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"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",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
13,735
|
student_club
|
bird:dev.json:1372
|
When did the member, Casey Mason, received the income?
|
SELECT T2.date_received FROM member AS T1 INNER JOIN income AS T2 ON T1.member_id = T2.link_to_member WHERE T1.first_name = 'Casey' AND T1.last_name = 'Mason'
|
[
"When",
"did",
"the",
"member",
",",
"Casey",
"Mason",
",",
"received",
"the",
"income",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_member"
},
{
"id": 0,
"type": "column",
"value": "date_received"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "column",
"value": "member_id"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 2,
"type": "table",
"value": "income"
},
{
"id": 6,
"type": "value",
"value": "Casey"
},
{
"id": 8,
"type": "value",
"value": "Mason"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
13,736
|
pilot_1
|
bird:test.json:1170
|
What are the names and ages of pilots who have planes located in Austin?
|
SELECT T1.pilot_name , T1.age FROM pilotskills AS T1 JOIN hangar AS T2 ON T1.plane_name = T2.plane_name WHERE T2.location = "Austin"
|
[
"What",
"are",
"the",
"names",
"and",
"ages",
"of",
"pilots",
"who",
"have",
"planes",
"located",
"in",
"Austin",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "pilotskills"
},
{
"id": 0,
"type": "column",
"value": "pilot_name"
},
{
"id": 6,
"type": "column",
"value": "plane_name"
},
{
"id": 4,
"type": "column",
"value": "location"
},
{
"id": 3,
"type": "table",
"value": "hangar"
},
{
"id": 5,
"type": "column",
"value": "Austin"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
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5
]
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
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10
]
},
{
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
13,737
|
restaurant
|
bird:train.json:1727
|
What is the address of the Peking Duck restaurant?
|
SELECT T2.street_name FROM generalinfo AS T1 INNER JOIN location AS T2 ON T1.id_restaurant = T2.id_restaurant WHERE T1.label = 'peking duck restaurant'
|
[
"What",
"is",
"the",
"address",
"of",
"the",
"Peking",
"Duck",
"restaurant",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "peking duck restaurant"
},
{
"id": 5,
"type": "column",
"value": "id_restaurant"
},
{
"id": 0,
"type": "column",
"value": "street_name"
},
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 3,
"type": "column",
"value": "label"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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6,
7
]
},
{
"entity_id": 5,
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8
]
},
{
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},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
13,738
|
game_1
|
spider:train_spider.json:6032
|
What is the total number of hours per week and number of games played by students under 20?
|
SELECT sum(hoursperweek) , sum(gamesplayed) FROM Sportsinfo AS T1 JOIN Student AS T2 ON T1.StuID = T2.StuID WHERE T2.age < 20
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"hours",
"per",
"week",
"and",
"number",
"of",
"games",
"played",
"by",
"students",
"under",
"20",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "hoursperweek"
},
{
"id": 5,
"type": "column",
"value": "gamesplayed"
},
{
"id": 0,
"type": "table",
"value": "sportsinfo"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 6,
"type": "column",
"value": "stuid"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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},
{
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},
{
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17
]
},
{
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6,
7,
8
]
},
{
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12,
13
]
},
{
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15
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},
{
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},
{
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},
{
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},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
13,739
|
soccer_2
|
spider:train_spider.json:5047
|
How many states have a college with more students than average?
|
SELECT count(DISTINCT state) FROM college WHERE enr > (SELECT avg(enr) FROM college)
|
[
"How",
"many",
"states",
"have",
"a",
"college",
"with",
"more",
"students",
"than",
"average",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "college"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 1,
"type": "column",
"value": "enr"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
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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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},
{
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{
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,740
|
disney
|
bird:train.json:4666
|
List all the songs associated with drama movies.
|
SELECT song FROM movies_total_gross AS T1 INNER JOIN characters AS T2 ON T1.movie_title = T2.movie_title WHERE T1.genre = 'Drama' GROUP BY song
|
[
"List",
"all",
"the",
"songs",
"associated",
"with",
"drama",
"movies",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "movies_total_gross"
},
{
"id": 5,
"type": "column",
"value": "movie_title"
},
{
"id": 2,
"type": "table",
"value": "characters"
},
{
"id": 3,
"type": "column",
"value": "genre"
},
{
"id": 4,
"type": "value",
"value": "Drama"
},
{
"id": 0,
"type": "column",
"value": "song"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
13,741
|
software_company
|
bird:train.json:8535
|
What is the number of inhabitants and income of geographic identifier 239?
|
SELECT INHABITANTS_K FROM Demog WHERE GEOID = 239
|
[
"What",
"is",
"the",
"number",
"of",
"inhabitants",
"and",
"income",
"of",
"geographic",
"identifier",
"239",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "inhabitants_k"
},
{
"id": 0,
"type": "table",
"value": "demog"
},
{
"id": 2,
"type": "column",
"value": "geoid"
},
{
"id": 3,
"type": "value",
"value": "239"
}
] |
[
{
"entity_id": 0,
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},
{
"entity_id": 1,
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5
]
},
{
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},
{
"entity_id": 3,
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11
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{
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},
{
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{
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},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,743
|
products_for_hire
|
spider:train_spider.json:1962
|
What is the maximum total amount paid by a customer? List the customer id and amount.
|
SELECT customer_id , sum(amount_paid) FROM Payments GROUP BY customer_id ORDER BY sum(amount_paid) DESC LIMIT 1
|
[
"What",
"is",
"the",
"maximum",
"total",
"amount",
"paid",
"by",
"a",
"customer",
"?",
"List",
"the",
"customer",
"i",
"d",
"and",
"amount",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "column",
"value": "amount_paid"
},
{
"id": 0,
"type": "table",
"value": "payments"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
13,744
|
gymnast
|
spider:train_spider.json:1760
|
What are the hometowns of gymnasts and the corresponding number of gymnasts?
|
SELECT T2.Hometown , COUNT(*) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown
|
[
"What",
"are",
"the",
"hometowns",
"of",
"gymnasts",
"and",
"the",
"corresponding",
"number",
"of",
"gymnasts",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "gymnast_id"
},
{
"id": 4,
"type": "column",
"value": "people_id"
},
{
"id": 0,
"type": "column",
"value": "hometown"
},
{
"id": 1,
"type": "table",
"value": "gymnast"
},
{
"id": 2,
"type": "table",
"value": "people"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,745
|
allergy_1
|
spider:train_spider.json:445
|
Show all allergies and their types.
|
SELECT allergy , allergytype FROM Allergy_type
|
[
"Show",
"all",
"allergies",
"and",
"their",
"types",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "allergy_type"
},
{
"id": 2,
"type": "column",
"value": "allergytype"
},
{
"id": 1,
"type": "column",
"value": "allergy"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,746
|
movie_platform
|
bird:train.json:97
|
What's the cover image of the user who created the movie list 'Georgia related films'?
|
SELECT T1.user_cover_image_url FROM lists_users AS T1 INNER JOIN lists AS T2 ON T1.list_id = T2.list_id WHERE T2.list_title LIKE 'Georgia related films'
|
[
"What",
"'s",
"the",
"cover",
"image",
"of",
"the",
"user",
"who",
"created",
"the",
"movie",
"list",
"'",
"Georgia",
"related",
"films",
"'",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Georgia related films"
},
{
"id": 0,
"type": "column",
"value": "user_cover_image_url"
},
{
"id": 1,
"type": "table",
"value": "lists_users"
},
{
"id": 3,
"type": "column",
"value": "list_title"
},
{
"id": 5,
"type": "column",
"value": "list_id"
},
{
"id": 2,
"type": "table",
"value": "lists"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,747
|
cars
|
bird:train.json:3137
|
Which is the most fuel efficient car in 1975?
|
SELECT T1.car_name FROM data AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID WHERE T2.model_year = '1975' ORDER BY T1.mpg DESC LIMIT 1
|
[
"Which",
"is",
"the",
"most",
"fuel",
"efficient",
"car",
"in",
"1975",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "production"
},
{
"id": 3,
"type": "column",
"value": "model_year"
},
{
"id": 0,
"type": "column",
"value": "car_name"
},
{
"id": 1,
"type": "table",
"value": "data"
},
{
"id": 4,
"type": "value",
"value": "1975"
},
{
"id": 5,
"type": "column",
"value": "mpg"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,748
|
candidate_poll
|
spider:train_spider.json:2406
|
List all people names in the order of their date of birth from old to young.
|
SELECT name FROM people ORDER BY date_of_birth
|
[
"List",
"all",
"people",
"names",
"in",
"the",
"order",
"of",
"their",
"date",
"of",
"birth",
"from",
"old",
"to",
"young",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "date_of_birth"
},
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
13,749
|
manufacturer
|
spider:train_spider.json:3395
|
Which manufacturer has the most number of shops? List its name and year of opening.
|
SELECT open_year , name FROM manufacturer ORDER BY num_of_shops DESC LIMIT 1
|
[
"Which",
"manufacturer",
"has",
"the",
"most",
"number",
"of",
"shops",
"?",
"List",
"its",
"name",
"and",
"year",
"of",
"opening",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturer"
},
{
"id": 3,
"type": "column",
"value": "num_of_shops"
},
{
"id": 1,
"type": "column",
"value": "open_year"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
13,750
|
formula_1
|
spider:train_spider.json:2178
|
What is the first and last name of all the German drivers?
|
SELECT forename , surname FROM drivers WHERE nationality = "German"
|
[
"What",
"is",
"the",
"first",
"and",
"last",
"name",
"of",
"all",
"the",
"German",
"drivers",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "nationality"
},
{
"id": 1,
"type": "column",
"value": "forename"
},
{
"id": 0,
"type": "table",
"value": "drivers"
},
{
"id": 2,
"type": "column",
"value": "surname"
},
{
"id": 4,
"type": "column",
"value": "German"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
13,751
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4215
|
Find the names of all the employees whose the role name is "Editor".
|
SELECT T1.employee_name FROM Employees AS T1 JOIN ROLES AS T2 ON T1.role_code = T2.role_code WHERE T2.role_name = "Editor"
|
[
"Find",
"the",
"names",
"of",
"all",
"the",
"employees",
"whose",
"the",
"role",
"name",
"is",
"\"",
"Editor",
"\"",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "employee_name"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "role_name"
},
{
"id": 5,
"type": "column",
"value": "role_code"
},
{
"id": 4,
"type": "column",
"value": "Editor"
},
{
"id": 2,
"type": "table",
"value": "roles"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"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",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,752
|
authors
|
bird:train.json:3648
|
Who are the authors of the paper "Determination of Planetary Meteorology from Aerobot Flight Sensors"?
|
SELECT T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Title = 'Determination of Planetary Meteorology FROM Aerobot Flight Sensors'
|
[
"Who",
"are",
"the",
"authors",
"of",
"the",
"paper",
"\"",
"Determination",
"of",
"Planetary",
"Meteorology",
"from",
"Aerobot",
"Flight",
"Sensors",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Determination of Planetary Meteorology FROM Aerobot Flight Sensors"
},
{
"id": 2,
"type": "table",
"value": "paperauthor"
},
{
"id": 6,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9,
10,
11,
12,
13,
14,
15
]
},
{
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},
{
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},
{
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"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,753
|
student_club
|
bird:dev.json:1421
|
Calculate the percentage of members who are major Business in the list?
|
SELECT CAST(SUM(CASE WHEN T2.major_name = 'Business' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.member_id) FROM member AS T1 INNER JOIN major AS T2 ON T2.major_id = T1.link_to_major WHERE T1.position = 'Member'
|
[
"Calculate",
"the",
"percentage",
"of",
"members",
"who",
"are",
"major",
"Business",
"in",
"the",
"list",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "link_to_major"
},
{
"id": 10,
"type": "column",
"value": "major_name"
},
{
"id": 7,
"type": "column",
"value": "member_id"
},
{
"id": 2,
"type": "column",
"value": "position"
},
{
"id": 4,
"type": "column",
"value": "major_id"
},
{
"id": 11,
"type": "value",
"value": "Business"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 3,
"type": "value",
"value": "Member"
},
{
"id": 1,
"type": "table",
"value": "major"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
8
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
13,754
|
tracking_orders
|
spider:train_spider.json:6912
|
Which customers have both "On Road" and "Shipped" as order status? List the customer ids.
|
SELECT T1.customer_id FROM customers AS T1 JOIN orders AS T2 ON T1.customer_id = T2.customer_id WHERE T2.order_status = "On Road" INTERSECT SELECT T1.customer_id FROM customers AS T1 JOIN orders AS T2 ON T1.customer_id = T2.customer_id WHERE T2.order_status = "Shipped"
|
[
"Which",
"customers",
"have",
"both",
"\"",
"On",
"Road",
"\"",
"and",
"\"",
"Shipped",
"\"",
"as",
"order",
"status",
"?",
"List",
"the",
"customer",
"ids",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "order_status"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "On Road"
},
{
"id": 5,
"type": "column",
"value": "Shipped"
},
{
"id": 2,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18,
19
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,755
|
car_retails
|
bird:train.json:1633
|
What is the total price of the order made by Cruz & Sons Co. on 2003/3/3?
|
SELECT SUM(t1.priceEach * t1.quantityOrdered) FROM orderdetails AS t1 INNER JOIN orders AS t2 ON t1.orderNumber = t2.orderNumber INNER JOIN customers AS t3 ON t2.customerNumber = t3.customerNumber WHERE t3.customerName = 'Cruz & Sons Co.' AND t2.orderDate = '2003-03-03'
|
[
"What",
"is",
"the",
"total",
"price",
"of",
"the",
"order",
"made",
"by",
"Cruz",
"&",
"Sons",
"Co.",
"on",
"2003/3/3",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Cruz & Sons Co."
},
{
"id": 9,
"type": "column",
"value": "quantityordered"
},
{
"id": 3,
"type": "column",
"value": "customernumber"
},
{
"id": 1,
"type": "table",
"value": "orderdetails"
},
{
"id": 4,
"type": "column",
"value": "customername"
},
{
"id": 10,
"type": "column",
"value": "ordernumber"
},
{
"id": 7,
"type": "value",
"value": "2003-03-03"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "orderdate"
},
{
"id": 8,
"type": "column",
"value": "priceeach"
},
{
"id": 2,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11,
12,
13
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": [
4
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
13,756
|
debate
|
spider:train_spider.json:1502
|
Show the names of people, and dates and venues of debates they are on the negative side, ordered in ascending alphabetical order of name.
|
SELECT T3.Name , T2.Date , T2.Venue FROM debate_people AS T1 JOIN debate AS T2 ON T1.Debate_ID = T2.Debate_ID JOIN people AS T3 ON T1.Negative = T3.People_ID ORDER BY T3.Name ASC
|
[
"Show",
"the",
"names",
"of",
"people",
",",
"and",
"dates",
"and",
"venues",
"of",
"debates",
"they",
"are",
"on",
"the",
"negative",
"side",
",",
"ordered",
"in",
"ascending",
"alphabetical",
"order",
"of",
"name",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "debate_people"
},
{
"id": 7,
"type": "column",
"value": "people_id"
},
{
"id": 8,
"type": "column",
"value": "debate_id"
},
{
"id": 6,
"type": "column",
"value": "negative"
},
{
"id": 3,
"type": "table",
"value": "people"
},
{
"id": 5,
"type": "table",
"value": "debate"
},
{
"id": 2,
"type": "column",
"value": "venue"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
25
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
16
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,757
|
insurance_fnol
|
spider:train_spider.json:899
|
Find the policy type used by more than 4 customers.
|
SELECT policy_type_code FROM available_policies GROUP BY policy_type_code HAVING count(*) > 4
|
[
"Find",
"the",
"policy",
"type",
"used",
"by",
"more",
"than",
"4",
"customers",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "available_policies"
},
{
"id": 1,
"type": "column",
"value": "policy_type_code"
},
{
"id": 2,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,758
|
planet_1
|
bird:test.json:1899
|
List all shipment ids on the planet Mars or under the management of Turanga Leela.
|
SELECT T1.ShipmentID FROM Shipment AS T1 JOIN Planet AS T2 ON T1.Planet = T2.PlanetID JOIN Employee AS T3 ON T3.EmployeeID = T1.Manager WHERE T2.Name = "Mars" OR T3.Name = "Turanga Leela";
|
[
"List",
"all",
"shipment",
"ids",
"on",
"the",
"planet",
"Mars",
"or",
"under",
"the",
"management",
"of",
"Turanga",
"Leela",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "Turanga Leela"
},
{
"id": 0,
"type": "column",
"value": "shipmentid"
},
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 10,
"type": "column",
"value": "planetid"
},
{
"id": 5,
"type": "column",
"value": "manager"
},
{
"id": 3,
"type": "table",
"value": "planet"
},
{
"id": 9,
"type": "column",
"value": "planet"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "Mars"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": [
13,
14
]
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,759
|
food_inspection_2
|
bird:train.json:6171
|
What are the inspector's comments and clean operating requirement code for inspection ID 54216 and point ID 34?
|
SELECT T2.inspector_comment, T1.code FROM inspection_point AS T1 INNER JOIN violation AS T2 ON T1.point_id = T2.point_id WHERE T2.inspection_id = 54216 AND T2.point_id = 34
|
[
"What",
"are",
"the",
"inspector",
"'s",
"comments",
"and",
"clean",
"operating",
"requirement",
"code",
"for",
"inspection",
"ID",
"54216",
"and",
"point",
"ID",
"34",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "inspector_comment"
},
{
"id": 2,
"type": "table",
"value": "inspection_point"
},
{
"id": 5,
"type": "column",
"value": "inspection_id"
},
{
"id": 3,
"type": "table",
"value": "violation"
},
{
"id": 4,
"type": "column",
"value": "point_id"
},
{
"id": 6,
"type": "value",
"value": "54216"
},
{
"id": 1,
"type": "column",
"value": "code"
},
{
"id": 7,
"type": "value",
"value": "34"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16,
17
]
},
{
"entity_id": 5,
"token_idxs": [
12,
13
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
18
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
13,761
|
codebase_comments
|
bird:train.json:572
|
What is the name of the solution path with the highest processed time?
|
SELECT Path FROM Solution WHERE ProcessedTime = ( SELECT MAX(ProcessedTime) FROM Solution )
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"solution",
"path",
"with",
"the",
"highest",
"processed",
"time",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "processedtime"
},
{
"id": 0,
"type": "table",
"value": "solution"
},
{
"id": 1,
"type": "column",
"value": "path"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,762
|
card_games
|
bird:dev.json:451
|
How many cards available in paper have a positive starting maximum hand size?
|
SELECT SUM(CASE WHEN availability = 'paper' AND hAND = '3' THEN 1 ELSE 0 END) FROM cards
|
[
"How",
"many",
"cards",
"available",
"in",
"paper",
"have",
"a",
"positive",
"starting",
"maximum",
"hand",
"size",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "availability"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 4,
"type": "value",
"value": "paper"
},
{
"id": 5,
"type": "column",
"value": "hand"
},
{
"id": 1,
"type": "value",
"value": "0"
},
{
"id": 2,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,763
|
art_1
|
bird:test.json:1233
|
How wide were the paintings by the artist who was born prior to 1850?
|
SELECT T2.width_mm FROM artists AS T1 JOIN paintings AS T2 ON T1.artistID = T2.painterID WHERE T1.birthYear < 1850
|
[
"How",
"wide",
"were",
"the",
"paintings",
"by",
"the",
"artist",
"who",
"was",
"born",
"prior",
"to",
"1850",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "paintings"
},
{
"id": 3,
"type": "column",
"value": "birthyear"
},
{
"id": 6,
"type": "column",
"value": "painterid"
},
{
"id": 0,
"type": "column",
"value": "width_mm"
},
{
"id": 5,
"type": "column",
"value": "artistid"
},
{
"id": 1,
"type": "table",
"value": "artists"
},
{
"id": 4,
"type": "value",
"value": "1850"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,764
|
codebase_comments
|
bird:train.json:597
|
Please give the url of the repository whose files are contained in solution ID 9?
|
SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T2.Id = 9
|
[
"Please",
"give",
"the",
"url",
"of",
"the",
"repository",
"whose",
"files",
"are",
"contained",
"in",
"solution",
"ID",
"9",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "solution"
},
{
"id": 5,
"type": "column",
"value": "repoid"
},
{
"id": 1,
"type": "table",
"value": "repo"
},
{
"id": 0,
"type": "column",
"value": "url"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,765
|
tracking_grants_for_research
|
spider:train_spider.json:4390
|
How many tasks does each project have? List the task count and the project detail.
|
SELECT count(*) , T1.project_details FROM Projects AS T1 JOIN Tasks AS T2 ON T1.project_id = T2.project_id GROUP BY T1.project_id
|
[
"How",
"many",
"tasks",
"does",
"each",
"project",
"have",
"?",
"List",
"the",
"task",
"count",
"and",
"the",
"project",
"detail",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "project_details"
},
{
"id": 0,
"type": "column",
"value": "project_id"
},
{
"id": 2,
"type": "table",
"value": "projects"
},
{
"id": 3,
"type": "table",
"value": "tasks"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
13,766
|
works_cycles
|
bird:train.json:7345
|
How many of the approved documents are confidential?
|
SELECT COUNT(DocumentNode) FROM Document WHERE Status = 2 AND DocumentSummary IS NULL
|
[
"How",
"many",
"of",
"the",
"approved",
"documents",
"are",
"confidential",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "documentsummary"
},
{
"id": 1,
"type": "column",
"value": "documentnode"
},
{
"id": 0,
"type": "table",
"value": "document"
},
{
"id": 2,
"type": "column",
"value": "status"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O"
] |
13,767
|
retail_world
|
bird:train.json:6304
|
Which employee is in charge of the sales in Hollis? Please give the employee's full name.
|
SELECT T1.FirstName, T1.LastName FROM Employees AS T1 INNER JOIN EmployeeTerritories AS T2 ON T1.EmployeeID = T2.EmployeeID INNER JOIN Territories AS T3 ON T2.TerritoryID = T3.TerritoryID WHERE T3.TerritoryDescription = 'Hollis'
|
[
"Which",
"employee",
"is",
"in",
"charge",
"of",
"the",
"sales",
"in",
"Hollis",
"?",
"Please",
"give",
"the",
"employee",
"'s",
"full",
"name",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "territorydescription"
},
{
"id": 6,
"type": "table",
"value": "employeeterritories"
},
{
"id": 2,
"type": "table",
"value": "territories"
},
{
"id": 7,
"type": "column",
"value": "territoryid"
},
{
"id": 8,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 4,
"type": "value",
"value": "Hollis"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
14,
15
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
1
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O"
] |
13,768
|
car_racing
|
bird:test.json:1614
|
For each driver, return his or her name and country.
|
SELECT T2.Driver , T1.Country FROM country AS T1 JOIN driver AS T2 ON T1.Country_ID = T2.Country
|
[
"For",
"each",
"driver",
",",
"return",
"his",
"or",
"her",
"name",
"and",
"country",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "driver"
},
{
"id": 3,
"type": "table",
"value": "driver"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,769
|
shop_membership
|
spider:train_spider.json:5414
|
How many different levels do members have?
|
SELECT count(DISTINCT LEVEL) FROM member
|
[
"How",
"many",
"different",
"levels",
"do",
"members",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 1,
"type": "column",
"value": "level"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
13,771
|
restaurant
|
bird:train.json:1753
|
List down the restaurant ID of restaurants located in Sunnyvale.
|
SELECT id_restaurant FROM location WHERE city = 'sunnyvale'
|
[
"List",
"down",
"the",
"restaurant",
"ID",
"of",
"restaurants",
"located",
"in",
"Sunnyvale",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "id_restaurant"
},
{
"id": 3,
"type": "value",
"value": "sunnyvale"
},
{
"id": 0,
"type": "table",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-VALUE",
"O"
] |
13,772
|
sales
|
bird:train.json:5432
|
Among the products that have price ranges from 100 to 150, what is the customer ID and sales ID of the product with a quantity lower than 25?
|
SELECT T2.CustomerID, T2.SalesID FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Price BETWEEN 100 AND 150 AND T2.Quantity < 25
|
[
"Among",
"the",
"products",
"that",
"have",
"price",
"ranges",
"from",
"100",
"to",
"150",
",",
"what",
"is",
"the",
"customer",
"ID",
"and",
"sales",
"ID",
"of",
"the",
"product",
"with",
"a",
"quantity",
"lower",
"than",
"25",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 4,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 8,
"type": "column",
"value": "quantity"
},
{
"id": 1,
"type": "column",
"value": "salesid"
},
{
"id": 3,
"type": "table",
"value": "sales"
},
{
"id": 5,
"type": "column",
"value": "price"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "150"
},
{
"id": 9,
"type": "value",
"value": "25"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15,
16
]
},
{
"entity_id": 1,
"token_idxs": [
19
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
22
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": [
25
]
},
{
"entity_id": 9,
"token_idxs": [
28
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,773
|
formula_1
|
spider:train_spider.json:2221
|
What is the maximum fastest lap speed in race named 'Monaco Grand Prix' in 2008 ?
|
SELECT max(T2.fastestlapspeed) FROM races AS T1 JOIN results AS T2 ON T1.raceid = T2.raceid WHERE T1.year = 2008 AND T1.name = "Monaco Grand Prix"
|
[
"What",
"is",
"the",
"maximum",
"fastest",
"lap",
"speed",
"in",
"race",
"named",
"'",
"Monaco",
"Grand",
"Prix",
"'",
"in",
"2008",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "Monaco Grand Prix"
},
{
"id": 2,
"type": "column",
"value": "fastestlapspeed"
},
{
"id": 1,
"type": "table",
"value": "results"
},
{
"id": 3,
"type": "column",
"value": "raceid"
},
{
"id": 0,
"type": "table",
"value": "races"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2008"
},
{
"id": 6,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,774
|
book_1
|
bird:test.json:547
|
Show all client names and the number of orders each has made.
|
SELECT T2.name , count(*) FROM Orders AS T1 JOIN Client AS T2 ON T1.idClient = T2.idClient GROUP BY T1.idClient
|
[
"Show",
"all",
"client",
"names",
"and",
"the",
"number",
"of",
"orders",
"each",
"has",
"made",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "idclient"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 3,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
13,775
|
car_racing
|
bird:test.json:1633
|
Show total and average points of all drivers.
|
SELECT sum(Points) , avg(Points) FROM driver
|
[
"Show",
"total",
"and",
"average",
"points",
"of",
"all",
"drivers",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "points"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
13,776
|
medicine_enzyme_interaction
|
spider:train_spider.json:967
|
List the medicine name and trade name which can both interact as 'inhibitor' and 'activitor' with enzymes.
|
SELECT T1.name , T1.trade_name FROM medicine AS T1 JOIN medicine_enzyme_interaction AS T2 ON T2.medicine_id = T1.id WHERE interaction_type = 'inhibitor' INTERSECT SELECT T1.name , T1.trade_name FROM medicine AS T1 JOIN medicine_enzyme_interaction AS T2 ON T2.medicine_id = T1.id WHERE interaction_type = 'activitor'
|
[
"List",
"the",
"medicine",
"name",
"and",
"trade",
"name",
"which",
"can",
"both",
"interact",
"as",
"'",
"inhibitor",
"'",
"and",
"'",
"activitor",
"'",
"with",
"enzymes",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "medicine_enzyme_interaction"
},
{
"id": 4,
"type": "column",
"value": "interaction_type"
},
{
"id": 7,
"type": "column",
"value": "medicine_id"
},
{
"id": 1,
"type": "column",
"value": "trade_name"
},
{
"id": 5,
"type": "value",
"value": "inhibitor"
},
{
"id": 6,
"type": "value",
"value": "activitor"
},
{
"id": 2,
"type": "table",
"value": "medicine"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
3,
4
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
13,777
|
cre_Doc_and_collections
|
bird:test.json:694
|
What are the ids of the documents that have more than one child?
|
SELECT T2.Document_Object_ID FROM Document_Objects AS T1 JOIN Document_Objects AS T2 ON T1.Parent_Document_Object_ID = T2.Document_Object_ID GROUP BY T2.Document_Object_ID HAVING count(*) > 1;
|
[
"What",
"are",
"the",
"ids",
"of",
"the",
"documents",
"that",
"have",
"more",
"than",
"one",
"child",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "parent_document_object_id"
},
{
"id": 0,
"type": "column",
"value": "document_object_id"
},
{
"id": 1,
"type": "table",
"value": "document_objects"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,778
|
movie_3
|
bird:train.json:9135
|
Among the customers who have rented the film ACADEMY DINOSAUR, how many of them are active?
|
SELECT COUNT(T1.customer_id) 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 WHERE T1.active = 1 AND T4.title = 'ACADEMY DINOSAUR'
|
[
"Among",
"the",
"customers",
"who",
"have",
"rented",
"the",
"film",
"ACADEMY",
"DINOSAUR",
",",
"how",
"many",
"of",
"them",
"are",
"active",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "ACADEMY DINOSAUR"
},
{
"id": 10,
"type": "column",
"value": "inventory_id"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "inventory"
},
{
"id": 8,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "column",
"value": "film_id"
},
{
"id": 4,
"type": "column",
"value": "active"
},
{
"id": 9,
"type": "table",
"value": "rental"
},
{
"id": 6,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8,
9
]
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": [
5
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,779
|
headphone_store
|
bird:test.json:958
|
Find the headphone model whose total quantity in stock is the largest.
|
SELECT t1.model FROM headphone AS t1 JOIN stock AS t2 ON t1.headphone_id = t2.headphone_id GROUP BY t1.model ORDER BY sum(t2.quantity) DESC LIMIT 1
|
[
"Find",
"the",
"headphone",
"model",
"whose",
"total",
"quantity",
"in",
"stock",
"is",
"the",
"largest",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "headphone_id"
},
{
"id": 1,
"type": "table",
"value": "headphone"
},
{
"id": 4,
"type": "column",
"value": "quantity"
},
{
"id": 0,
"type": "column",
"value": "model"
},
{
"id": 2,
"type": "table",
"value": "stock"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
13,780
|
talkingdata
|
bird:train.json:1171
|
List down the app IDs under the category of game-Rowing .
|
SELECT T2.app_id FROM label_categories AS T1 INNER JOIN app_labels AS T2 ON T1.label_id = T2.label_id WHERE T1.category = 'game-Rowing'
|
[
"List",
"down",
"the",
"app",
"IDs",
"under",
"the",
"category",
"of",
"game",
"-",
"Rowing",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "label_categories"
},
{
"id": 4,
"type": "value",
"value": "game-Rowing"
},
{
"id": 2,
"type": "table",
"value": "app_labels"
},
{
"id": 3,
"type": "column",
"value": "category"
},
{
"id": 5,
"type": "column",
"value": "label_id"
},
{
"id": 0,
"type": "column",
"value": "app_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
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",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,781
|
entertainment_awards
|
spider:train_spider.json:4600
|
List the name of artworks whose type is not "Program Talent Show".
|
SELECT Name FROM artwork WHERE TYPE != "Program Talent Show"
|
[
"List",
"the",
"name",
"of",
"artworks",
"whose",
"type",
"is",
"not",
"\"",
"Program",
"Talent",
"Show",
"\"",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "Program Talent Show"
},
{
"id": 0,
"type": "table",
"value": "artwork"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
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",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,782
|
music_platform_2
|
bird:train.json:7927
|
List all content reviewed for podcast with the best rating under the 'fiction' category. State the podcast title.
|
SELECT DISTINCT T2.title FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id INNER JOIN reviews AS T3 ON T3.podcast_id = T2.podcast_id WHERE T3.rating = 5 AND T1.category = 'fiction'
|
[
"List",
"all",
"content",
"reviewed",
"for",
"podcast",
"with",
"the",
"best",
"rating",
"under",
"the",
"'",
"fiction",
"'",
"category",
".",
"State",
"the",
"podcast",
"title",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "categories"
},
{
"id": 4,
"type": "column",
"value": "podcast_id"
},
{
"id": 3,
"type": "table",
"value": "podcasts"
},
{
"id": 7,
"type": "column",
"value": "category"
},
{
"id": 1,
"type": "table",
"value": "reviews"
},
{
"id": 8,
"type": "value",
"value": "fiction"
},
{
"id": 5,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,783
|
real_estate_rentals
|
bird:test.json:1443
|
What are the first, middle, last, and login names for all users who are sellers?
|
SELECT first_name , middle_name , last_name , login_name FROM Users WHERE is_seller = 1;
|
[
"What",
"are",
"the",
"first",
",",
"middle",
",",
"last",
",",
"and",
"login",
"names",
"for",
"all",
"users",
"who",
"are",
"sellers",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "middle_name"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "login_name"
},
{
"id": 3,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "is_seller"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
13,784
|
conference
|
bird:test.json:1077
|
Show all staff name who are above the average age.
|
SELECT name FROM staff WHERE age > (SELECT avg(age) FROM staff)
|
[
"Show",
"all",
"staff",
"name",
"who",
"are",
"above",
"the",
"average",
"age",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,785
|
warehouse_1
|
bird:test.json:1717
|
Find the location of the warehouses which store contents Rocks and Scissors.
|
SELECT T2.location FROM boxes AS T1 JOIN warehouses AS T2 ON T1.warehouse = T2.code WHERE T1.contents = 'Rocks' INTERSECT SELECT T2.location FROM boxes AS T1 JOIN warehouses AS T2 ON T1.warehouse = T2.code WHERE T1.contents = 'Scissors'
|
[
"Find",
"the",
"location",
"of",
"the",
"warehouses",
"which",
"store",
"contents",
"Rocks",
"and",
"Scissors",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "warehouses"
},
{
"id": 6,
"type": "column",
"value": "warehouse"
},
{
"id": 0,
"type": "column",
"value": "location"
},
{
"id": 3,
"type": "column",
"value": "contents"
},
{
"id": 5,
"type": "value",
"value": "Scissors"
},
{
"id": 1,
"type": "table",
"value": "boxes"
},
{
"id": 4,
"type": "value",
"value": "Rocks"
},
{
"id": 7,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"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": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,786
|
vehicle_driver
|
bird:test.json:163
|
What are the build year, model name and builder of the vehicles?
|
SELECT build_year , model , builder FROM vehicle
|
[
"What",
"are",
"the",
"build",
"year",
",",
"model",
"name",
"and",
"builder",
"of",
"the",
"vehicles",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "build_year"
},
{
"id": 0,
"type": "table",
"value": "vehicle"
},
{
"id": 3,
"type": "column",
"value": "builder"
},
{
"id": 2,
"type": "column",
"value": "model"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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,
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},
{
"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
13,787
|
music_1
|
spider:train_spider.json:3569
|
Find the distinct names of all songs that have a higher resolution than some songs in English.
|
SELECT DISTINCT song_name FROM song WHERE resolution > (SELECT min(resolution) FROM song WHERE languages = "english")
|
[
"Find",
"the",
"distinct",
"names",
"of",
"all",
"songs",
"that",
"have",
"a",
"higher",
"resolution",
"than",
"some",
"songs",
"in",
"English",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "resolution"
},
{
"id": 1,
"type": "column",
"value": "song_name"
},
{
"id": 3,
"type": "column",
"value": "languages"
},
{
"id": 4,
"type": "column",
"value": "english"
},
{
"id": 0,
"type": "table",
"value": "song"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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16
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
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{
"entity_id": 10,
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-COLUMN",
"O"
] |
13,788
|
store_product
|
spider:train_spider.json:4930
|
Find products with max page size as "A4" and pages per minute color smaller than 5.
|
SELECT product FROM product WHERE max_page_size = "A4" AND pages_per_minute_color < 5
|
[
"Find",
"products",
"with",
"max",
"page",
"size",
"as",
"\"",
"A4",
"\"",
"and",
"pages",
"per",
"minute",
"color",
"smaller",
"than",
"5",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "pages_per_minute_color"
},
{
"id": 2,
"type": "column",
"value": "max_page_size"
},
{
"id": 0,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "column",
"value": "product"
},
{
"id": 3,
"type": "column",
"value": "A4"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12,
13,
14
]
},
{
"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",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,790
|
city_record
|
spider:train_spider.json:6296
|
Please give me a list of cities whose regional population is over 10000000.
|
SELECT city FROM city WHERE regional_population > 10000000
|
[
"Please",
"give",
"me",
"a",
"list",
"of",
"cities",
"whose",
"regional",
"population",
"is",
"over",
"10000000",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "regional_population"
},
{
"id": 3,
"type": "value",
"value": "10000000"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
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12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,791
|
bike_racing
|
bird:test.json:1480
|
How many different levels of heat are there for the cyclists?
|
SELECT count(DISTINCT heat) FROM cyclist
|
[
"How",
"many",
"different",
"levels",
"of",
"heat",
"are",
"there",
"for",
"the",
"cyclists",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "cyclist"
},
{
"id": 1,
"type": "column",
"value": "heat"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,792
|
regional_sales
|
bird:train.json:2643
|
What is the percentage of total orders of Stephen Payne that had a net profit of over 1000?
|
SELECT CAST(SUM(CASE WHEN REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '') > 1000 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T2.`Sales Team` = 'Stephen Payne'
|
[
"What",
"is",
"the",
"percentage",
"of",
"total",
"orders",
"of",
"Stephen",
"Payne",
"that",
"had",
"a",
"net",
"profit",
"of",
"over",
"1000",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Stephen Payne"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 5,
"type": "column",
"value": "_salesteamid"
},
{
"id": 4,
"type": "column",
"value": "salesteamid"
},
{
"id": 7,
"type": "column",
"value": "ordernumber"
},
{
"id": 1,
"type": "table",
"value": "Sales Team"
},
{
"id": 2,
"type": "column",
"value": "Sales Team"
},
{
"id": 11,
"type": "column",
"value": "Unit Price"
},
{
"id": 13,
"type": "column",
"value": "Unit Cost"
},
{
"id": 10,
"type": "value",
"value": "1000"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
},
{
"id": 12,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
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5
]
},
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},
{
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{
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9
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{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,793
|
beer_factory
|
bird:train.json:5347
|
What is the best seller root beer brand and what is the average star rating for this root beer?
|
SELECT T1.BrandID, AVG(T1.StarRating) FROM rootbeerreview AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID GROUP BY T3.BrandID ORDER BY COUNT(T1.BrandID) DESC LIMIT 1
|
[
"What",
"is",
"the",
"best",
"seller",
"root",
"beer",
"brand",
"and",
"what",
"is",
"the",
"average",
"star",
"rating",
"for",
"this",
"root",
"beer",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 1,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 4,
"type": "table",
"value": "transaction"
},
{
"id": 2,
"type": "column",
"value": "starrating"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "column",
"value": "brandid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
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14
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18
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{
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{
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{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
13,794
|
bike_share_1
|
bird:train.json:9032
|
What are the average maximum and minimum temperatures in May 2015 when the mean humidity is between 65 and 75?
|
SELECT AVG(max_temperature_f), AVG(min_temperature_f) FROM weather WHERE date LIKE '5/%/2015' AND mean_humidity BETWEEN 65 AND 75
|
[
"What",
"are",
"the",
"average",
"maximum",
"and",
"minimum",
"temperatures",
"in",
"May",
"2015",
"when",
"the",
"mean",
"humidity",
"is",
"between",
"65",
"and",
"75",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "max_temperature_f"
},
{
"id": 2,
"type": "column",
"value": "min_temperature_f"
},
{
"id": 5,
"type": "column",
"value": "mean_humidity"
},
{
"id": 4,
"type": "value",
"value": "5/%/2015"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 3,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "65"
},
{
"id": 7,
"type": "value",
"value": "75"
}
] |
[
{
"entity_id": 0,
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11,
12
]
},
{
"entity_id": 1,
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{
"entity_id": 2,
"token_idxs": [
6,
7
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},
{
"entity_id": 3,
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{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,795
|
game_1
|
spider:train_spider.json:6003
|
List ids for all student who are on scholarship.
|
SELECT StuID FROM Sportsinfo WHERE onscholarship = 'Y'
|
[
"List",
"ids",
"for",
"all",
"student",
"who",
"are",
"on",
"scholarship",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "onscholarship"
},
{
"id": 0,
"type": "table",
"value": "sportsinfo"
},
{
"id": 1,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "value",
"value": "Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
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