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2,893
|
student_loan
|
bird:train.json:4424
|
How many students who have never been absent from school?
|
SELECT COUNT(name) FROM longest_absense_from_school WHERE month = 0
|
[
"How",
"many",
"students",
"who",
"have",
"never",
"been",
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"school",
"?"
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[
{
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"type": "column",
"value": "name"
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{
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"type": "value",
"value": "0"
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"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
2,894
|
chicago_crime
|
bird:train.json:8678
|
What is the FBI code and definition of Gambling?
|
SELECT fbi_code_no, description FROM FBI_Code WHERE title = 'Gambling'
|
[
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"FBI",
"code",
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"Gambling",
"?"
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[
{
"id": 1,
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{
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"value": "description"
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{
"id": 0,
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{
"id": 4,
"type": "value",
"value": "Gambling"
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{
"id": 3,
"type": "column",
"value": "title"
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"O",
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"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,895
|
soccer_3
|
bird:test.json:13
|
From which countries are players who make more than 1200000 from?
|
SELECT DISTINCT Country FROM player WHERE Earnings > 1200000
|
[
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"countries",
"are",
"players",
"who",
"make",
"more",
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"1200000",
"from",
"?"
] |
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{
"id": 2,
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"value": "earnings"
},
{
"id": 1,
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"value": "country"
},
{
"id": 3,
"type": "value",
"value": "1200000"
},
{
"id": 0,
"type": "table",
"value": "player"
}
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[
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"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,896
|
behavior_monitoring
|
spider:train_spider.json:3115
|
Find the start and end dates of detentions of teachers with last name "Schultz".
|
SELECT T1.datetime_detention_start , datetime_detention_end FROM Detention AS T1 JOIN Teachers AS T2 ON T1.teacher_id = T2.teacher_id WHERE T2.last_name = "Schultz"
|
[
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"detentions",
"of",
"teachers",
"with",
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"name",
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"Schultz",
"\"",
"."
] |
[
{
"id": 0,
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{
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{
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"type": "column",
"value": "teacher_id"
},
{
"id": 2,
"type": "table",
"value": "detention"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "table",
"value": "teachers"
},
{
"id": 5,
"type": "column",
"value": "Schultz"
}
] |
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[
"O",
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"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
2,897
|
car_retails
|
bird:train.json:1615
|
What was the contact name for the check "NR157385"?
|
SELECT t2.contactFirstName, t2.contactLastName FROM payments AS t1 INNER JOIN customers AS t2 ON t1.customerNumber = t2.customerNumber WHERE t1.checkNumber = 'NR157385'
|
[
"What",
"was",
"the",
"contact",
"name",
"for",
"the",
"check",
"\"",
"NR157385",
"\"",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "contactfirstname"
},
{
"id": 1,
"type": "column",
"value": "contactlastname"
},
{
"id": 6,
"type": "column",
"value": "customernumber"
},
{
"id": 4,
"type": "column",
"value": "checknumber"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "payments"
},
{
"id": 5,
"type": "value",
"value": "NR157385"
}
] |
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[
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"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
2,898
|
works_cycles
|
bird:train.json:7177
|
How much is HL Grip Tape's profit ratio?
|
SELECT (T1.LastReceiptCost - T1.StandardPrice) / T1.StandardPrice FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'HL Grip Tape'
|
[
"How",
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"HL",
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"Tape",
"'s",
"profit",
"ratio",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "lastreceiptcost"
},
{
"id": 0,
"type": "table",
"value": "productvendor"
},
{
"id": 4,
"type": "column",
"value": "standardprice"
},
{
"id": 3,
"type": "value",
"value": "HL Grip Tape"
},
{
"id": 5,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
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[
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O",
"O"
] |
2,899
|
movie_2
|
bird:test.json:1805
|
Find the names of movies whose rating is ‘G’.
|
SELECT title FROM movies WHERE rating = 'G'
|
[
"Find",
"the",
"names",
"of",
"movies",
"whose",
"rating",
"is",
"‘",
"G",
"’",
"."
] |
[
{
"id": 0,
"type": "table",
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{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "value",
"value": "G"
}
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[
"O",
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"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,901
|
hockey
|
bird:train.json:7723
|
Which NHL award was most frequently won by the coach with the most wins?
|
SELECT award FROM Teams AS T1 INNER JOIN AwardsCoaches AS T2 ON T1.lgID = T2.lgID WHERE T1.lgID = 'NHL' GROUP BY T2.coachID, T2.award ORDER BY COUNT(T2.award) DESC LIMIT 1
|
[
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"was",
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"frequently",
"won",
"by",
"the",
"coach",
"with",
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"most",
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"?"
] |
[
{
"id": 3,
"type": "table",
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},
{
"id": 0,
"type": "column",
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{
"id": 1,
"type": "column",
"value": "award"
},
{
"id": 2,
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"value": "teams"
},
{
"id": 4,
"type": "column",
"value": "lgid"
},
{
"id": 5,
"type": "value",
"value": "NHL"
}
] |
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[
"O",
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"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
2,902
|
menu
|
bird:train.json:5567
|
Which menu page of "Ritz Carlton" has the biggest height?
|
SELECT T1.page_number FROM MenuPage AS T1 INNER JOIN Menu AS T2 ON T2.id = T1.menu_id WHERE T2.name = 'Ritz Carlton' ORDER BY T1.full_height DESC LIMIT 1
|
[
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"\"",
"Ritz",
"Carlton",
"\"",
"has",
"the",
"biggest",
"height",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Ritz Carlton"
},
{
"id": 0,
"type": "column",
"value": "page_number"
},
{
"id": 5,
"type": "column",
"value": "full_height"
},
{
"id": 1,
"type": "table",
"value": "menupage"
},
{
"id": 7,
"type": "column",
"value": "menu_id"
},
{
"id": 2,
"type": "table",
"value": "menu"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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"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",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,903
|
college_2
|
spider:train_spider.json:1324
|
Count the number of rooms that are not in the Lamberton building.
|
SELECT count(*) FROM classroom WHERE building != 'Lamberton'
|
[
"Count",
"the",
"number",
"of",
"rooms",
"that",
"are",
"not",
"in",
"the",
"Lamberton",
"building",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "classroom"
},
{
"id": 2,
"type": "value",
"value": "Lamberton"
},
{
"id": 1,
"type": "column",
"value": "building"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,904
|
car_retails
|
bird:train.json:1598
|
Calculate the average amount of payments made by customers during the first half of 2004.
|
SELECT AVG(amount) FROM payments WHERE paymentDate BETWEEN '2004-01-01' AND '2004-06-30'
|
[
"Calculate",
"the",
"average",
"amount",
"of",
"payments",
"made",
"by",
"customers",
"during",
"the",
"first",
"half",
"of",
"2004",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "paymentdate"
},
{
"id": 2,
"type": "value",
"value": "2004-01-01"
},
{
"id": 3,
"type": "value",
"value": "2004-06-30"
},
{
"id": 0,
"type": "table",
"value": "payments"
},
{
"id": 4,
"type": "column",
"value": "amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,905
|
boat_1
|
bird:test.json:895
|
Find the number of reservations for each boat with id greater than 50.
|
SELECT bid , count(*) FROM Reserves GROUP BY bid HAVING bid > 50
|
[
"Find",
"the",
"number",
"of",
"reservations",
"for",
"each",
"boat",
"with",
"i",
"d",
"greater",
"than",
"50",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "reserves"
},
{
"id": 1,
"type": "column",
"value": "bid"
},
{
"id": 2,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,906
|
thrombosis_prediction
|
bird:dev.json:1277
|
How many patients have a normal anti-DNA level, yet their data are not recorded.
|
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.DNA < 8 AND T1.Description IS NULL
|
[
"How",
"many",
"patients",
"have",
"a",
"normal",
"anti",
"-",
"DNA",
"level",
",",
"yet",
"their",
"data",
"are",
"not",
"recorded",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "dna"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "8"
}
] |
[
{
"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": []
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,907
|
soccer_2016
|
bird:train.json:1803
|
What is the average winning margin of all the matches SC Ganguly has played in?
|
SELECT CAST(SUM(T3.Win_Margin) AS REAL) / COUNT(*) FROM Player AS T1 INNER JOIN Player_Match AS T2 ON T1.Player_Id = T2.Player_Id INNER JOIN Match AS T3 ON T2.Match_Id = T3.Match_Id WHERE T1.Player_Name = 'SC Ganguly'
|
[
"What",
"is",
"the",
"average",
"winning",
"margin",
"of",
"all",
"the",
"matches",
"SC",
"Ganguly",
"has",
"played",
"in",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "player_match"
},
{
"id": 1,
"type": "column",
"value": "player_name"
},
{
"id": 2,
"type": "value",
"value": "SC Ganguly"
},
{
"id": 7,
"type": "column",
"value": "win_margin"
},
{
"id": 6,
"type": "column",
"value": "player_id"
},
{
"id": 5,
"type": "column",
"value": "match_id"
},
{
"id": 3,
"type": "table",
"value": "player"
},
{
"id": 0,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
2,908
|
vehicle_driver
|
bird:test.json:171
|
What are the distinct driver names who have driven vehicles with power more than 5000 ?
|
select distinct t1.name from driver as t1 join vehicle_driver as t2 on t1.driver_id = t2.driver_id join vehicle as t3 on t2.vehicle_id = t3.vehicle_id where t3.power > 5000
|
[
"What",
"are",
"the",
"distinct",
"driver",
"names",
"who",
"have",
"driven",
"vehicles",
"with",
"power",
"more",
"than",
"5000",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "vehicle_driver"
},
{
"id": 6,
"type": "column",
"value": "vehicle_id"
},
{
"id": 7,
"type": "column",
"value": "driver_id"
},
{
"id": 1,
"type": "table",
"value": "vehicle"
},
{
"id": 4,
"type": "table",
"value": "driver"
},
{
"id": 2,
"type": "column",
"value": "power"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "5000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,909
|
formula_1
|
bird:dev.json:902
|
Which race was Alex Yoong in when he was in track number less than 20?
|
SELECT T1.name FROM races AS T1 INNER JOIN driverStandings AS T2 ON T2.raceId = T1.raceId INNER JOIN drivers AS T3 ON T3.driverId = T2.driverId WHERE T3.forename = 'Alex' AND T3.surname = 'Yoong' AND T2.position < 20
|
[
"Which",
"race",
"was",
"Alex",
"Yoong",
"in",
"when",
"he",
"was",
"in",
"track",
"number",
"less",
"than",
"20",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "driverstandings"
},
{
"id": 4,
"type": "column",
"value": "driverid"
},
{
"id": 5,
"type": "column",
"value": "forename"
},
{
"id": 9,
"type": "column",
"value": "position"
},
{
"id": 1,
"type": "table",
"value": "drivers"
},
{
"id": 7,
"type": "column",
"value": "surname"
},
{
"id": 11,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 8,
"type": "value",
"value": "Yoong"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "Alex"
},
{
"id": 10,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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3
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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4
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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14
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,910
|
small_bank_1
|
spider:train_spider.json:1783
|
What is the average balance in checking accounts?
|
SELECT avg(balance) FROM checking
|
[
"What",
"is",
"the",
"average",
"balance",
"in",
"checking",
"accounts",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "checking"
},
{
"id": 1,
"type": "column",
"value": "balance"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"O",
"O"
] |
2,911
|
boat_1
|
bird:test.json:853
|
return the unique ids of sailors who are older than any sailors.
|
SELECT DISTINCT sid FROM Sailors WHERE age > (SELECT min(age) FROM Sailors);
|
[
"return",
"the",
"unique",
"ids",
"of",
"sailors",
"who",
"are",
"older",
"than",
"any",
"sailors",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "sailors"
},
{
"id": 1,
"type": "column",
"value": "sid"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
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11
]
},
{
"entity_id": 1,
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3
]
},
{
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7
]
},
{
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},
{
"entity_id": 4,
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{
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},
{
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},
{
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},
{
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},
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,912
|
workshop_paper
|
spider:train_spider.json:5829
|
Which college has the most authors with submissions?
|
SELECT College FROM submission GROUP BY College ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Which",
"college",
"has",
"the",
"most",
"authors",
"with",
"submissions",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "submission"
},
{
"id": 1,
"type": "column",
"value": "college"
}
] |
[
{
"entity_id": 0,
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7
]
},
{
"entity_id": 1,
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1
]
},
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},
{
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},
{
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},
{
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},
{
"entity_id": 6,
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},
{
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},
{
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{
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{
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{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"O"
] |
2,913
|
college_1
|
spider:train_spider.json:3291
|
Find the first name of the professor who is teaching two courses with code CIS-220 and QM-261.
|
SELECT T1.emp_fname FROM employee AS T1 JOIN CLASS AS T2 ON T1.emp_num = T2.prof_num WHERE crs_code = 'CIS-220' INTERSECT SELECT T1.emp_fname FROM employee AS T1 JOIN CLASS AS T2 ON T1.emp_num = T2.prof_num WHERE crs_code = 'QM-261'
|
[
"Find",
"the",
"first",
"name",
"of",
"the",
"professor",
"who",
"is",
"teaching",
"two",
"courses",
"with",
"code",
"CIS-220",
"and",
"QM-261",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "emp_fname"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 3,
"type": "column",
"value": "crs_code"
},
{
"id": 7,
"type": "column",
"value": "prof_num"
},
{
"id": 4,
"type": "value",
"value": "CIS-220"
},
{
"id": 6,
"type": "column",
"value": "emp_num"
},
{
"id": 5,
"type": "value",
"value": "QM-261"
},
{
"id": 2,
"type": "table",
"value": "class"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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},
{
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},
{
"entity_id": 3,
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]
},
{
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14
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,914
|
human_resources
|
bird:train.json:8951
|
State the name of the city where Jose Rodriguez works.
|
SELECT T2.locationcity FROM employee AS T1 INNER JOIN location AS T2 ON T1.locationID = T2.locationID WHERE T1.firstname = 'Jose' AND T1.lastname = 'Rodriguez'
|
[
"State",
"the",
"name",
"of",
"the",
"city",
"where",
"Jose",
"Rodriguez",
"works",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "locationcity"
},
{
"id": 3,
"type": "column",
"value": "locationid"
},
{
"id": 4,
"type": "column",
"value": "firstname"
},
{
"id": 7,
"type": "value",
"value": "Rodriguez"
},
{
"id": 1,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 6,
"type": "column",
"value": "lastname"
},
{
"id": 5,
"type": "value",
"value": "Jose"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
2,915
|
flight_4
|
spider:train_spider.json:6855
|
List the cities which have more than one airport and number of airports.
|
SELECT city , count(*) FROM airports GROUP BY city HAVING count(*) > 1
|
[
"List",
"the",
"cities",
"which",
"have",
"more",
"than",
"one",
"airport",
"and",
"number",
"of",
"airports",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "airports"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,916
|
restaurant
|
bird:train.json:1732
|
What type of restaurant is most common in Monterey county?
|
SELECT T2.food_type FROM geographic AS T1 INNER JOIN generalinfo AS T2 ON T1.city = T2.city WHERE T1.county = 'Monterey' GROUP BY T2.food_type ORDER BY COUNT(T2.food_type) DESC LIMIT 1
|
[
"What",
"type",
"of",
"restaurant",
"is",
"most",
"common",
"in",
"Monterey",
"county",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "generalinfo"
},
{
"id": 1,
"type": "table",
"value": "geographic"
},
{
"id": 0,
"type": "column",
"value": "food_type"
},
{
"id": 4,
"type": "value",
"value": "Monterey"
},
{
"id": 3,
"type": "column",
"value": "county"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,917
|
customers_card_transactions
|
spider:train_spider.json:740
|
What are the different card types, and how many transactions have been made with each?
|
SELECT T2.card_type_code , count(*) FROM Financial_transactions AS T1 JOIN Customers_cards AS T2 ON T1.card_id = T2.card_id GROUP BY T2.card_type_code
|
[
"What",
"are",
"the",
"different",
"card",
"types",
",",
"and",
"how",
"many",
"transactions",
"have",
"been",
"made",
"with",
"each",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "financial_transactions"
},
{
"id": 2,
"type": "table",
"value": "customers_cards"
},
{
"id": 0,
"type": "column",
"value": "card_type_code"
},
{
"id": 3,
"type": "column",
"value": "card_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,918
|
movie
|
bird:train.json:772
|
What is the gross of a comedy movie with a rating lower than 7 and starred by an actor with a net worth greater than $375,000,000.00?
|
SELECT SUM(T1.Gross) FROM movie AS T1 INNER JOIN characters AS T2 ON T1.MovieID = T2.MovieID INNER JOIN actor AS T3 ON T3.ActorID = T2.ActorID WHERE CAST(REPLACE(REPLACE(T3.NetWorth, ',', ''), '$', '') AS REAL) > 375000000 AND T1.Rating < 7 AND T1.Genre = 'Comedy'
|
[
"What",
"is",
"the",
"gross",
"of",
"a",
"comedy",
"movie",
"with",
"a",
"rating",
"lower",
"than",
"7",
"and",
"starred",
"by",
"an",
"actor",
"with",
"a",
"net",
"worth",
"greater",
"than",
"$",
"375,000,000.00",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "characters"
},
{
"id": 5,
"type": "value",
"value": "375000000"
},
{
"id": 12,
"type": "column",
"value": "networth"
},
{
"id": 4,
"type": "column",
"value": "actorid"
},
{
"id": 10,
"type": "column",
"value": "movieid"
},
{
"id": 6,
"type": "column",
"value": "rating"
},
{
"id": 9,
"type": "value",
"value": "Comedy"
},
{
"id": 0,
"type": "table",
"value": "actor"
},
{
"id": 1,
"type": "column",
"value": "gross"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 8,
"type": "column",
"value": "genre"
},
{
"id": 7,
"type": "value",
"value": "7"
},
{
"id": 11,
"type": "value",
"value": "$"
},
{
"id": 13,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
23
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
26
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
25
]
},
{
"entity_id": 12,
"token_idxs": [
21,
22
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
2,919
|
insurance_fnol
|
spider:train_spider.json:904
|
Which services have been used more than twice in first notification of loss? Return the service name.
|
SELECT t2.service_name FROM first_notification_of_loss AS t1 JOIN services AS t2 ON t1.service_id = t2.service_id GROUP BY t1.service_id HAVING count(*) > 2
|
[
"Which",
"services",
"have",
"been",
"used",
"more",
"than",
"twice",
"in",
"first",
"notification",
"of",
"loss",
"?",
"Return",
"the",
"service",
"name",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "first_notification_of_loss"
},
{
"id": 1,
"type": "column",
"value": "service_name"
},
{
"id": 0,
"type": "column",
"value": "service_id"
},
{
"id": 3,
"type": "table",
"value": "services"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
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9,
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11,
12
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,920
|
tracking_orders
|
spider:train_spider.json:6902
|
Which orders are made by the customer named "Jeramie"? Give me the order ids and status.
|
SELECT T2.order_id , T2.order_status FROM customers AS T1 JOIN orders AS T2 ON T1.customer_id = T2.customer_id WHERE T1.customer_name = "Jeramie"
|
[
"Which",
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"are",
"made",
"by",
"the",
"customer",
"named",
"\"",
"Jeramie",
"\"",
"?",
"Give",
"me",
"the",
"order",
"ids",
"and",
"status",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "customer_name"
},
{
"id": 1,
"type": "column",
"value": "order_status"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "order_id"
},
{
"id": 5,
"type": "column",
"value": "Jeramie"
},
{
"id": 3,
"type": "table",
"value": "orders"
}
] |
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{
"entity_id": 0,
"token_idxs": [
15,
16
]
},
{
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17,
18
]
},
{
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"token_idxs": [
6
]
},
{
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"token_idxs": [
1
]
},
{
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7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
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},
{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,921
|
chicago_crime
|
bird:train.json:8619
|
What is the percentage of under $500 thefts among all cases that happened in West Englewood?
|
SELECT CAST(SUM(CASE WHEN T2.secondary_description = '$500 AND UNDER' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.case_number) FROM Crime AS T1 INNER JOIN IUCR AS T2 ON T1.iucr_no = T2.iucr_no INNER JOIN Community_Area AS T3 ON T1.community_area_no = T3.community_area_no WHERE T2.primary_description = 'THEFT' AND T3.community_area_name = 'West Englewood'
|
[
"What",
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"the",
"percentage",
"of",
"under",
"$",
"500",
"thefts",
"among",
"all",
"cases",
"that",
"happened",
"in",
"West",
"Englewood",
"?"
] |
[
{
"id": 13,
"type": "column",
"value": "secondary_description"
},
{
"id": 4,
"type": "column",
"value": "primary_description"
},
{
"id": 6,
"type": "column",
"value": "community_area_name"
},
{
"id": 3,
"type": "column",
"value": "community_area_no"
},
{
"id": 0,
"type": "table",
"value": "community_area"
},
{
"id": 7,
"type": "value",
"value": "West Englewood"
},
{
"id": 14,
"type": "value",
"value": "$500 AND UNDER"
},
{
"id": 9,
"type": "column",
"value": "case_number"
},
{
"id": 10,
"type": "column",
"value": "iucr_no"
},
{
"id": 1,
"type": "table",
"value": "crime"
},
{
"id": 5,
"type": "value",
"value": "THEFT"
},
{
"id": 2,
"type": "table",
"value": "iucr"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 11,
"type": "value",
"value": "0"
},
{
"id": 12,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
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"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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15,
16
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
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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",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,922
|
movielens
|
bird:train.json:2332
|
How many of the worst actors are men and how many of the worst actors are women? Indicate your answer in ratio form.
|
SELECT CAST(SUM(IIF(a_gender = 'M', 1, 0)) AS REAL) / SUM(IIF(a_gender = 'F', 1, 0)) FROM actors WHERE a_quality = 0
|
[
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"many",
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"the",
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"actors",
"are",
"men",
"and",
"how",
"many",
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"worst",
"actors",
"are",
"women",
"?",
"Indicate",
"your",
"answer",
"in",
"ratio",
"form",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "a_quality"
},
{
"id": 4,
"type": "column",
"value": "a_gender"
},
{
"id": 0,
"type": "table",
"value": "actors"
},
{
"id": 2,
"type": "value",
"value": "0"
},
{
"id": 3,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "F"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
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},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": []
},
{
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"token_idxs": []
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{
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"token_idxs": []
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{
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},
{
"entity_id": 6,
"token_idxs": []
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{
"entity_id": 13,
"token_idxs": []
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{
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"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,923
|
hockey
|
bird:train.json:7810
|
Which player ID are left winger and weight more than 200?
|
SELECT DISTINCT playerID FROM Master WHERE pos LIKE '%L%' AND weight > 200 AND playerID IS NOT NULL AND pos = 'L'
|
[
"Which",
"player",
"ID",
"are",
"left",
"winger",
"and",
"weight",
"more",
"than",
"200",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 4,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "column",
"value": "pos"
},
{
"id": 3,
"type": "value",
"value": "%L%"
},
{
"id": 5,
"type": "value",
"value": "200"
},
{
"id": 6,
"type": "value",
"value": "L"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"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": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,924
|
movie_3
|
bird:train.json:9237
|
What is the inventory ID of the films starred by Russell Close with a duration between 110 to 150 minutes?
|
SELECT T4.inventory_id FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id INNER JOIN inventory AS T4 ON T3.film_id = T4.film_id WHERE T3.length BETWEEN 110 AND 150 AND T1.first_name = 'Russell' AND T1.last_name = 'Close'
|
[
"What",
"is",
"the",
"inventory",
"ID",
"of",
"the",
"films",
"starred",
"by",
"Russell",
"Close",
"with",
"a",
"duration",
"between",
"110",
"to",
"150",
"minutes",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "inventory_id"
},
{
"id": 7,
"type": "column",
"value": "first_name"
},
{
"id": 12,
"type": "table",
"value": "film_actor"
},
{
"id": 1,
"type": "table",
"value": "inventory"
},
{
"id": 9,
"type": "column",
"value": "last_name"
},
{
"id": 13,
"type": "column",
"value": "actor_id"
},
{
"id": 3,
"type": "column",
"value": "film_id"
},
{
"id": 8,
"type": "value",
"value": "Russell"
},
{
"id": 4,
"type": "column",
"value": "length"
},
{
"id": 10,
"type": "value",
"value": "Close"
},
{
"id": 11,
"type": "table",
"value": "actor"
},
{
"id": 2,
"type": "table",
"value": "film"
},
{
"id": 5,
"type": "value",
"value": "110"
},
{
"id": 6,
"type": "value",
"value": "150"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
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"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
18
]
},
{
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"token_idxs": []
},
{
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{
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"token_idxs": []
},
{
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"token_idxs": [
11
]
},
{
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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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O"
] |
2,926
|
retail_complains
|
bird:train.json:394
|
Give the client ID of the complaint received on April 16, 2014 and submitted through fax.
|
SELECT T2.Client_ID FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.`Submitted via` = 'Fax' AND T1.`Date received` = '2014-04-16'
|
[
"Give",
"the",
"client",
"ID",
"of",
"the",
"complaint",
"received",
"on",
"April",
"16",
",",
"2014",
"and",
"submitted",
"through",
"fax",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 4,
"type": "column",
"value": "Submitted via"
},
{
"id": 6,
"type": "column",
"value": "Date received"
},
{
"id": 3,
"type": "column",
"value": "Complaint ID"
},
{
"id": 7,
"type": "value",
"value": "2014-04-16"
},
{
"id": 0,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "table",
"value": "events"
},
{
"id": 5,
"type": "value",
"value": "Fax"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
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{
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{
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"token_idxs": []
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{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,928
|
video_games
|
bird:train.json:3427
|
What is the number of games sold in Europe for game platform ID 26?
|
SELECT T2.num_sales * 100000 AS nums_eur FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id WHERE T2.game_platform_id = 26 AND T1.region_name = 'Europe'
|
[
"What",
"is",
"the",
"number",
"of",
"games",
"sold",
"in",
"Europe",
"for",
"game",
"platform",
"ID",
"26",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "game_platform_id"
},
{
"id": 1,
"type": "table",
"value": "region_sales"
},
{
"id": 8,
"type": "column",
"value": "region_name"
},
{
"id": 2,
"type": "column",
"value": "num_sales"
},
{
"id": 5,
"type": "column",
"value": "region_id"
},
{
"id": 0,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "value",
"value": "100000"
},
{
"id": 9,
"type": "value",
"value": "Europe"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "26"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10,
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,929
|
music_1
|
spider:train_spider.json:3533
|
Find the names of all English songs.
|
SELECT song_name FROM song WHERE languages = "english"
|
[
"Find",
"the",
"names",
"of",
"all",
"English",
"songs",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "song_name"
},
{
"id": 2,
"type": "column",
"value": "languages"
},
{
"id": 3,
"type": "column",
"value": "english"
},
{
"id": 0,
"type": "table",
"value": "song"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
2,930
|
regional_sales
|
bird:train.json:2595
|
List the ID, city, state and region for the store type which is fewer between borough and CDP.
|
SELECT DISTINCT T2.StoreID, T2.`City Name`, T1.State, T2.Type FROM Regions AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StateCode = T1.StateCode WHERE T2.Type = 'Borough' OR T2.Type = 'CDP'
|
[
"List",
"the",
"ID",
",",
"city",
",",
"state",
"and",
"region",
"for",
"the",
"store",
"type",
"which",
"is",
"fewer",
"between",
"borough",
"and",
"CDP",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "Store Locations"
},
{
"id": 1,
"type": "column",
"value": "City Name"
},
{
"id": 6,
"type": "column",
"value": "statecode"
},
{
"id": 0,
"type": "column",
"value": "storeid"
},
{
"id": 4,
"type": "table",
"value": "regions"
},
{
"id": 7,
"type": "value",
"value": "Borough"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "column",
"value": "type"
},
{
"id": 8,
"type": "value",
"value": "CDP"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
17
]
},
{
"entity_id": 8,
"token_idxs": [
19
]
},
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"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,931
|
college_2
|
spider:train_spider.json:1346
|
How many courses that do not have prerequisite?
|
SELECT count(*) FROM course WHERE course_id NOT IN (SELECT course_id FROM prereq)
|
[
"How",
"many",
"courses",
"that",
"do",
"not",
"have",
"prerequisite",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "table",
"value": "prereq"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,932
|
olympics
|
bird:train.json:4948
|
How many Summer games were held in Stockholm?
|
SELECT COUNT(T3.id) FROM games_city AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.id INNER JOIN games AS T3 ON T1.games_id = T3.id WHERE T2.city_name = 'Stockholm' AND T3.season = 'Summer'
|
[
"How",
"many",
"Summer",
"games",
"were",
"held",
"in",
"Stockholm",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "games_city"
},
{
"id": 5,
"type": "column",
"value": "city_name"
},
{
"id": 6,
"type": "value",
"value": "Stockholm"
},
{
"id": 4,
"type": "column",
"value": "games_id"
},
{
"id": 9,
"type": "column",
"value": "city_id"
},
{
"id": 7,
"type": "column",
"value": "season"
},
{
"id": 8,
"type": "value",
"value": "Summer"
},
{
"id": 0,
"type": "table",
"value": "games"
},
{
"id": 3,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,933
|
address
|
bird:train.json:5125
|
Which city and state has the bad alias of Lawrenceville?
|
SELECT T2.city, T2.state FROM avoid AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.bad_alias = 'Lawrenceville' GROUP BY T2.city, T2.state
|
[
"Which",
"city",
"and",
"state",
"has",
"the",
"bad",
"alias",
"of",
"Lawrenceville",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Lawrenceville"
},
{
"id": 4,
"type": "column",
"value": "bad_alias"
},
{
"id": 3,
"type": "table",
"value": "zip_data"
},
{
"id": 6,
"type": "column",
"value": "zip_code"
},
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "table",
"value": "avoid"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6,
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,934
|
hockey
|
bird:train.json:7745
|
Among the teams whose shorthanded goals are between 1 to 5, which player is the most trustworthy in the critical moment?
|
SELECT T2.nameGiven, T2.lastName FROM Scoring AS T1 INNER JOIN Master AS T2 ON T1.playerID = T2.playerID WHERE T1.SHG BETWEEN 1 AND 5 ORDER BY T1.GWG DESC LIMIT 1
|
[
"Among",
"the",
"teams",
"whose",
"shorthanded",
"goals",
"are",
"between",
"1",
"to",
"5",
",",
"which",
"player",
"is",
"the",
"most",
"trustworthy",
"in",
"the",
"critical",
"moment",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "namegiven"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 8,
"type": "column",
"value": "playerid"
},
{
"id": 2,
"type": "table",
"value": "scoring"
},
{
"id": 3,
"type": "table",
"value": "master"
},
{
"id": 4,
"type": "column",
"value": "shg"
},
{
"id": 7,
"type": "column",
"value": "gwg"
},
{
"id": 5,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
10
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},
{
"entity_id": 7,
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},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,935
|
mondial_geo
|
bird:train.json:8375
|
What is the capital of the 3rd most populated country in Asia and what is the capital city's ratio in percentage (%) against the overall population of the country?
|
SELECT T4.Capital, CAST(T3.Population AS REAL) * 100 / T4.Population FROM city AS T3 INNER JOIN ( SELECT T1.Capital , T1.Population FROM country AS T1 INNER JOIN encompasses AS T2 ON T1.Code = T2.Country WHERE T2.Continent = 'Asia' ORDER BY T1.Population DESC LIMIT 2, 1 ) AS T4 ON T3.Name = T4.Capital
|
[
"What",
"is",
"the",
"capital",
"of",
"the",
"3rd",
"most",
"populated",
"country",
"in",
"Asia",
"and",
"what",
"is",
"the",
"capital",
"city",
"'s",
"ratio",
"in",
"percentage",
"(",
"%",
")",
"against",
"the",
"overall",
"population",
"of",
"the",
"country",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "encompasses"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 7,
"type": "column",
"value": "continent"
},
{
"id": 0,
"type": "column",
"value": "capital"
},
{
"id": 5,
"type": "table",
"value": "country"
},
{
"id": 10,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "value",
"value": "Asia"
},
{
"id": 9,
"type": "column",
"value": "code"
},
{
"id": 4,
"type": "value",
"value": "100"
}
] |
[
{
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"token_idxs": [
16
]
},
{
"entity_id": 1,
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17
]
},
{
"entity_id": 2,
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28
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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10
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},
{
"entity_id": 8,
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11
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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9
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,936
|
conference
|
bird:test.json:1078
|
What are the names of all staff members who are older than average?
|
SELECT name FROM staff WHERE age > (SELECT avg(age) FROM staff)
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"staff",
"members",
"who",
"are",
"older",
"than",
"average",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,937
|
customers_and_addresses
|
spider:train_spider.json:6112
|
Tell me the payment method used by the customer who ordered the least amount of goods in total.
|
SELECT t1.payment_method FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id GROUP BY t1.customer_name ORDER BY sum(t3.order_quantity) LIMIT 1
|
[
"Tell",
"me",
"the",
"payment",
"method",
"used",
"by",
"the",
"customer",
"who",
"ordered",
"the",
"least",
"amount",
"of",
"goods",
"in",
"total",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "payment_method"
},
{
"id": 6,
"type": "column",
"value": "order_quantity"
},
{
"id": 0,
"type": "column",
"value": "customer_name"
},
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "column",
"value": "order_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,939
|
epinions_1
|
spider:train_spider.json:1696
|
How many different items were reviewed by some users?
|
SELECT count(DISTINCT i_id) FROM review
|
[
"How",
"many",
"different",
"items",
"were",
"reviewed",
"by",
"some",
"users",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "review"
},
{
"id": 1,
"type": "column",
"value": "i_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
2,940
|
hockey
|
bird:train.json:7763
|
How many wins did the Philadelphia Flyers have over the Boston Bruins in 1985?
|
SELECT T1.W FROM TeamVsTeam AS T1 INNER JOIN Teams AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.year = 1985 AND T1.tmID = ( SELECT DISTINCT tmID FROM Teams WHERE name = 'Philadelphia Flyers' ) AND T1.oppID = ( SELECT DISTINCT tmID FROM Teams WHERE name = 'Boston Bruins' )
|
[
"How",
"many",
"wins",
"did",
"the",
"Philadelphia",
"Flyers",
"have",
"over",
"the",
"Boston",
"Bruins",
"in",
"1985",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Philadelphia Flyers"
},
{
"id": 9,
"type": "value",
"value": "Boston Bruins"
},
{
"id": 1,
"type": "table",
"value": "teamvsteam"
},
{
"id": 2,
"type": "table",
"value": "teams"
},
{
"id": 6,
"type": "column",
"value": "oppid"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "1985"
},
{
"id": 5,
"type": "column",
"value": "tmid"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "w"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"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": [
5
]
},
{
"entity_id": 9,
"token_idxs": [
10,
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
2,941
|
hospital_1
|
spider:train_spider.json:3926
|
What is the name of the nurse has the most 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
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"nurse",
"has",
"the",
"most",
"appointments",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "appointment"
},
{
"id": 0,
"type": "column",
"value": "employeeid"
},
{
"id": 4,
"type": "column",
"value": "prepnurse"
},
{
"id": 2,
"type": "table",
"value": "nurse"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,942
|
language_corpus
|
bird:train.json:5717
|
What are the words that were paired with "John", list down 10 of them.
|
SELECT w2nd FROM biwords WHERE w1st = ( SELECT wid FROM words WHERE word = 'john' ) LIMIT 10
|
[
"What",
"are",
"the",
"words",
"that",
"were",
"paired",
"with",
"\"",
"John",
"\"",
",",
"list",
"down",
"10",
"of",
"them",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "biwords"
},
{
"id": 3,
"type": "table",
"value": "words"
},
{
"id": 1,
"type": "column",
"value": "w2nd"
},
{
"id": 2,
"type": "column",
"value": "w1st"
},
{
"id": 5,
"type": "column",
"value": "word"
},
{
"id": 6,
"type": "value",
"value": "john"
},
{
"id": 4,
"type": "column",
"value": "wid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,943
|
driving_school
|
spider:train_spider.json:6632
|
When did the staff member with first name as Janessa and last name as Sawayn join the company?
|
SELECT date_joined_staff FROM Staff WHERE first_name = "Janessa" AND last_name = "Sawayn";
|
[
"When",
"did",
"the",
"staff",
"member",
"with",
"first",
"name",
"as",
"Janessa",
"and",
"last",
"name",
"as",
"Sawayn",
"join",
"the",
"company",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "date_joined_staff"
},
{
"id": 2,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "Janessa"
},
{
"id": 5,
"type": "column",
"value": "Sawayn"
},
{
"id": 0,
"type": "table",
"value": "staff"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,944
|
soccer_2016
|
bird:train.json:2029
|
Which team won by wickets in match ID 335993?
|
SELECT T1.Team_Name FROM Team AS T1 INNER JOIN Match AS T2 ON T1.team_id = T2.match_winner INNER JOIN Player_Match AS T3 ON T1.Team_Id = T3.Team_Id INNER JOIN Win_By AS T4 ON T2.Win_Type = T4.Win_Id WHERE T2.Match_Id = '335993' GROUP BY T1.Team_Name
|
[
"Which",
"team",
"won",
"by",
"wickets",
"in",
"match",
"ID",
"335993",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "player_match"
},
{
"id": 10,
"type": "column",
"value": "match_winner"
},
{
"id": 0,
"type": "column",
"value": "team_name"
},
{
"id": 2,
"type": "column",
"value": "match_id"
},
{
"id": 5,
"type": "column",
"value": "win_type"
},
{
"id": 9,
"type": "column",
"value": "team_id"
},
{
"id": 1,
"type": "table",
"value": "win_by"
},
{
"id": 3,
"type": "value",
"value": "335993"
},
{
"id": 6,
"type": "column",
"value": "win_id"
},
{
"id": 8,
"type": "table",
"value": "match"
},
{
"id": 7,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,945
|
college_3
|
spider:train_spider.json:4648
|
How many students have had at least one "B" grade?
|
SELECT COUNT(DISTINCT StuID) FROM ENROLLED_IN WHERE Grade = "B"
|
[
"How",
"many",
"students",
"have",
"had",
"at",
"least",
"one",
"\"",
"B",
"\"",
"grade",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "enrolled_in"
},
{
"id": 1,
"type": "column",
"value": "grade"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 2,
"type": "column",
"value": "B"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,946
|
book_press
|
bird:test.json:1997
|
Find the name of authors who publish their books in both "MM" and "LT" series.
|
SELECT t1.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id WHERE t2.book_series = 'MM' INTERSECT SELECT t1.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id WHERE t2.book_series = 'LT'
|
[
"Find",
"the",
"name",
"of",
"authors",
"who",
"publish",
"their",
"books",
"in",
"both",
"\"",
"MM",
"\"",
"and",
"\"",
"LT",
"\"",
"series",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "book_series"
},
{
"id": 6,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "book"
},
{
"id": 4,
"type": "value",
"value": "MM"
},
{
"id": 5,
"type": "value",
"value": "LT"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
2,947
|
music_tracker
|
bird:train.json:2057
|
How many tags does the release "city funk" have？
|
SELECT COUNT(T2.tag) FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T1.groupName = 'city funk'
|
[
"How",
"many",
"tags",
"does",
"the",
"release",
"\"",
"city",
"funk",
"\"",
"have",
"？"
] |
[
{
"id": 2,
"type": "column",
"value": "groupname"
},
{
"id": 3,
"type": "value",
"value": "city funk"
},
{
"id": 0,
"type": "table",
"value": "torrents"
},
{
"id": 1,
"type": "table",
"value": "tags"
},
{
"id": 4,
"type": "column",
"value": "tag"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
2,948
|
real_estate_rentals
|
bird:test.json:1460
|
What are the different room sizes, and how many of each are there?
|
SELECT room_size , count(*) FROM Rooms GROUP BY room_size
|
[
"What",
"are",
"the",
"different",
"room",
"sizes",
",",
"and",
"how",
"many",
"of",
"each",
"are",
"there",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "room_size"
},
{
"id": 0,
"type": "table",
"value": "rooms"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,949
|
codebase_community
|
bird:dev.json:709
|
In comments with 0 score, how many of the posts have view count lower than 5?
|
SELECT COUNT(T1.Id) FROM comments AS T1 INNER JOIN posts AS T2 ON T1.PostId = T2.Id WHERE T2.ViewCount < 5 AND T2.Score = 0
|
[
"In",
"comments",
"with",
"0",
"score",
",",
"how",
"many",
"of",
"the",
"posts",
"have",
"view",
"count",
"lower",
"than",
"5",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "viewcount"
},
{
"id": 0,
"type": "table",
"value": "comments"
},
{
"id": 3,
"type": "column",
"value": "postid"
},
{
"id": 1,
"type": "table",
"value": "posts"
},
{
"id": 6,
"type": "column",
"value": "score"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "5"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,950
|
icfp_1
|
spider:train_spider.json:2914
|
What is the first name of the author with last name "Ueno"?
|
SELECT fname FROM authors WHERE lname = "Ueno"
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"the",
"author",
"with",
"last",
"name",
"\"",
"Ueno",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "authors"
},
{
"id": 1,
"type": "column",
"value": "fname"
},
{
"id": 2,
"type": "column",
"value": "lname"
},
{
"id": 3,
"type": "column",
"value": "Ueno"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
2,951
|
simpson_episodes
|
bird:train.json:4237
|
How many nominations have Billy Kimball received in 2010 for The simpson 20s: Season 20?
|
SELECT COUNT(award_id) FROM Award WHERE person = 'Billy Kimball' AND SUBSTR(year, 1, 4) = '2010' AND result = 'Nominee';
|
[
"How",
"many",
"nominations",
"have",
"Billy",
"Kimball",
"received",
"in",
"2010",
"for",
"The",
"simpson",
"20s",
":",
"Season",
"20",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Billy Kimball"
},
{
"id": 1,
"type": "column",
"value": "award_id"
},
{
"id": 6,
"type": "value",
"value": "Nominee"
},
{
"id": 2,
"type": "column",
"value": "person"
},
{
"id": 5,
"type": "column",
"value": "result"
},
{
"id": 0,
"type": "table",
"value": "award"
},
{
"id": 4,
"type": "value",
"value": "2010"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"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",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,952
|
inn_1
|
spider:train_spider.json:2572
|
Find the names of all modern rooms with a base price below $160 and two beds.
|
SELECT roomName FROM Rooms WHERE basePrice < 160 AND beds = 2 AND decor = 'modern';
|
[
"Find",
"the",
"names",
"of",
"all",
"modern",
"rooms",
"with",
"a",
"base",
"price",
"below",
"$",
"160",
"and",
"two",
"beds",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "baseprice"
},
{
"id": 1,
"type": "column",
"value": "roomname"
},
{
"id": 7,
"type": "value",
"value": "modern"
},
{
"id": 0,
"type": "table",
"value": "rooms"
},
{
"id": 6,
"type": "column",
"value": "decor"
},
{
"id": 4,
"type": "column",
"value": "beds"
},
{
"id": 3,
"type": "value",
"value": "160"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
2,953
|
bike_1
|
spider:train_spider.json:136
|
What is the id of the bike that traveled the most in 94002?
|
SELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"bike",
"that",
"traveled",
"the",
"most",
"in",
"94002",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "zip_code"
},
{
"id": 1,
"type": "column",
"value": "bike_id"
},
{
"id": 3,
"type": "value",
"value": "94002"
},
{
"id": 0,
"type": "table",
"value": "trip"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,954
|
disney
|
bird:train.json:4723
|
Which actor voices Akela from The Jungle Book?
|
SELECT `voice-actor` FROM `voice-actors` WHERE character = 'Akela'
|
[
"Which",
"actor",
"voices",
"Akela",
"from",
"The",
"Jungle",
"Book",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "voice-actors"
},
{
"id": 1,
"type": "column",
"value": "voice-actor"
},
{
"id": 2,
"type": "column",
"value": "character"
},
{
"id": 3,
"type": "value",
"value": "Akela"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0,
1
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
2,955
|
planet_1
|
bird:test.json:1862
|
What is the salary and position of the employee named Turanga Leela?
|
SELECT Salary , POSITION FROM Employee WHERE Name = "Turanga Leela";
|
[
"What",
"is",
"the",
"salary",
"and",
"position",
"of",
"the",
"employee",
"named",
"Turanga",
"Leela",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "Turanga Leela"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "column",
"value": "position"
},
{
"id": 1,
"type": "column",
"value": "salary"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,956
|
e_learning
|
spider:train_spider.json:3848
|
Find the common personal name of course authors and students.
|
SELECT personal_name FROM Course_Authors_and_Tutors INTERSECT SELECT personal_name FROM Students
|
[
"Find",
"the",
"common",
"personal",
"name",
"of",
"course",
"authors",
"and",
"students",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 2,
"type": "column",
"value": "personal_name"
},
{
"id": 1,
"type": "table",
"value": "students"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-TABLE",
"O"
] |
2,957
|
company_office
|
spider:train_spider.json:4551
|
What are the average profits of companies?
|
SELECT avg(Profits_billion) FROM Companies
|
[
"What",
"are",
"the",
"average",
"profits",
"of",
"companies",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "profits_billion"
},
{
"id": 0,
"type": "table",
"value": "companies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
2,958
|
hr_1
|
spider:train_spider.json:3451
|
Find the ids of the departments where any manager is managing 4 or more employees.
|
SELECT DISTINCT department_id FROM employees GROUP BY department_id , manager_id HAVING COUNT(employee_id) >= 4
|
[
"Find",
"the",
"ids",
"of",
"the",
"departments",
"where",
"any",
"manager",
"is",
"managing",
"4",
"or",
"more",
"employees",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 4,
"type": "column",
"value": "employee_id"
},
{
"id": 2,
"type": "column",
"value": "manager_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
2,959
|
cs_semester
|
bird:train.json:871
|
What is the average satisfying degree of the course Machine Learning Theory?
|
SELECT CAST(SUM(T1.sat) AS REAL) / COUNT(T1.student_id) FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T2.name = 'Machine Learning Theory'
|
[
"What",
"is",
"the",
"average",
"satisfying",
"degree",
"of",
"the",
"course",
"Machine",
"Learning",
"Theory",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Machine Learning Theory"
},
{
"id": 0,
"type": "table",
"value": "registration"
},
{
"id": 5,
"type": "column",
"value": "student_id"
},
{
"id": 4,
"type": "column",
"value": "course_id"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "sat"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,960
|
professional_basketball
|
bird:train.json:2816
|
in which year costela01 obtained the best balance of games won as a coach?
|
SELECT year FROM coaches WHERE coachID = 'costela01' ORDER BY CAST(won AS REAL) / (won + lost) DESC LIMIT 1
|
[
"in",
"which",
"year",
"costela01",
"obtained",
"the",
"best",
"balance",
"of",
"games",
"won",
"as",
"a",
"coach",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "costela01"
},
{
"id": 0,
"type": "table",
"value": "coaches"
},
{
"id": 2,
"type": "column",
"value": "coachid"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "column",
"value": "lost"
},
{
"id": 4,
"type": "column",
"value": "won"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
2,961
|
ship_1
|
spider:train_spider.json:6222
|
How many captains are in each rank?
|
SELECT count(*) , rank FROM captain GROUP BY rank
|
[
"How",
"many",
"captains",
"are",
"in",
"each",
"rank",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "captain"
},
{
"id": 1,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,962
|
scientist_1
|
spider:train_spider.json:6490
|
What are the names of projects that require between 100 and 300 hours?
|
SELECT name FROM projects WHERE hours BETWEEN 100 AND 300
|
[
"What",
"are",
"the",
"names",
"of",
"projects",
"that",
"require",
"between",
"100",
"and",
"300",
"hours",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "projects"
},
{
"id": 2,
"type": "column",
"value": "hours"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "300"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,963
|
superhero
|
bird:dev.json:771
|
List the name of superheroes with flight power.
|
SELECT T1.superhero_name FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id WHERE T3.power_name = 'Flight'
|
[
"List",
"the",
"name",
"of",
"superheroes",
"with",
"flight",
"power",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "superhero_name"
},
{
"id": 1,
"type": "table",
"value": "superpower"
},
{
"id": 2,
"type": "column",
"value": "power_name"
},
{
"id": 5,
"type": "table",
"value": "hero_power"
},
{
"id": 4,
"type": "table",
"value": "superhero"
},
{
"id": 6,
"type": "column",
"value": "power_id"
},
{
"id": 8,
"type": "column",
"value": "hero_id"
},
{
"id": 3,
"type": "value",
"value": "Flight"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,964
|
university_basketball
|
spider:train_spider.json:993
|
Find the location and all games score of the school that has Clemson as its team name.
|
SELECT t2.All_Games , t1.location FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id WHERE team_name = 'Clemson'
|
[
"Find",
"the",
"location",
"and",
"all",
"games",
"score",
"of",
"the",
"school",
"that",
"has",
"Clemson",
"as",
"its",
"team",
"name",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "basketball_match"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 0,
"type": "column",
"value": "all_games"
},
{
"id": 4,
"type": "column",
"value": "team_name"
},
{
"id": 6,
"type": "column",
"value": "school_id"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 5,
"type": "value",
"value": "Clemson"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,965
|
public_review_platform
|
bird:train.json:4098
|
Sum up the number of business with "ambience_romantic" attribute.
|
SELECT COUNT(T2.business_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.attribute_name = 'ambience_romantic' AND T2.attribute_value = 'true'
|
[
"Sum",
"up",
"the",
"number",
"of",
"business",
"with",
"\"",
"ambience_romantic",
"\"",
"attribute",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "business_attributes"
},
{
"id": 5,
"type": "value",
"value": "ambience_romantic"
},
{
"id": 6,
"type": "column",
"value": "attribute_value"
},
{
"id": 4,
"type": "column",
"value": "attribute_name"
},
{
"id": 3,
"type": "column",
"value": "attribute_id"
},
{
"id": 2,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "attributes"
},
{
"id": 7,
"type": "value",
"value": "true"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"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": [
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,966
|
election
|
spider:train_spider.json:2751
|
Count the number of distinct governors.
|
SELECT count(DISTINCT Governor) FROM party
|
[
"Count",
"the",
"number",
"of",
"distinct",
"governors",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "governor"
},
{
"id": 0,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,967
|
wrestler
|
spider:train_spider.json:1868
|
Show the reign and days held of wrestlers.
|
SELECT Reign , Days_held FROM wrestler
|
[
"Show",
"the",
"reign",
"and",
"days",
"held",
"of",
"wrestlers",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "days_held"
},
{
"id": 0,
"type": "table",
"value": "wrestler"
},
{
"id": 1,
"type": "column",
"value": "reign"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O"
] |
2,968
|
pilot_1
|
bird:test.json:1102
|
What is all the information about pilots who are younger than 30 ?
|
select * from pilotskills where age < 30
|
[
"What",
"is",
"all",
"the",
"information",
"about",
"pilots",
"who",
"are",
"younger",
"than",
"30",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,969
|
works_cycles
|
bird:train.json:7109
|
Please list the departments that are part of the Executive General and Administration group.
|
SELECT Name FROM Department WHERE GroupName = 'Executive General and Administration'
|
[
"Please",
"list",
"the",
"departments",
"that",
"are",
"part",
"of",
"the",
"Executive",
"General",
"and",
"Administration",
"group",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Executive General and Administration"
},
{
"id": 0,
"type": "table",
"value": "department"
},
{
"id": 2,
"type": "column",
"value": "groupname"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
9,
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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
2,970
|
local_govt_and_lot
|
spider:train_spider.json:4853
|
How many different status codes of things are there?
|
SELECT count(DISTINCT Status_of_Thing_Code) FROM Timed_Status_of_Things
|
[
"How",
"many",
"different",
"status",
"codes",
"of",
"things",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "timed_status_of_things"
},
{
"id": 1,
"type": "column",
"value": "status_of_thing_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
2,971
|
planet_1
|
bird:test.json:1895
|
List all shipment ids for the planet Mars.
|
SELECT T1.ShipmentID FROM Shipment AS T1 JOIN Planet AS T2 ON T1.Planet = T2.PlanetID WHERE T2.Name = "Mars";
|
[
"List",
"all",
"shipment",
"ids",
"for",
"the",
"planet",
"Mars",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "shipmentid"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 6,
"type": "column",
"value": "planetid"
},
{
"id": 2,
"type": "table",
"value": "planet"
},
{
"id": 5,
"type": "column",
"value": "planet"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "Mars"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,972
|
food_inspection
|
bird:train.json:8836
|
List the eateries' names and addresses which had reinspection on 2nd February, 2015.
|
SELECT T2.name, T2.address FROM inspections AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.`date` = '2015-02-02' AND T1.type = 'Reinspection/Followup'
|
[
"List",
"the",
"eateries",
"'",
"names",
"and",
"addresses",
"which",
"had",
"reinspection",
"on",
"2nd",
"February",
",",
"2015",
"."
] |
[
{
"id": 8,
"type": "value",
"value": "Reinspection/Followup"
},
{
"id": 2,
"type": "table",
"value": "inspections"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 3,
"type": "table",
"value": "businesses"
},
{
"id": 6,
"type": "value",
"value": "2015-02-02"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "column",
"value": "type"
}
] |
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6
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9
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,973
|
college_2
|
spider:train_spider.json:1358
|
Find the name and budget of departments whose budgets are more than the average budget.
|
SELECT dept_name , budget FROM department WHERE budget > (SELECT avg(budget) FROM department)
|
[
"Find",
"the",
"name",
"and",
"budget",
"of",
"departments",
"whose",
"budgets",
"are",
"more",
"than",
"the",
"average",
"budget",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "department"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 2,
"type": "column",
"value": "budget"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
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14
]
},
{
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,974
|
movielens
|
bird:train.json:2288
|
What is the highest average rating for action movies made in the USA?
|
SELECT AVG(T2.rating) FROM movies AS T1 INNER JOIN u2base AS T2 ON T1.movieid = T2.movieid INNER JOIN movies2directors AS T3 ON T1.movieid = T3.movieid WHERE T1.country = 'USA' AND T3.genre = 'Action' GROUP BY T1.movieid ORDER BY AVG(T2.rating) DESC LIMIT 1
|
[
"What",
"is",
"the",
"highest",
"average",
"rating",
"for",
"action",
"movies",
"made",
"in",
"the",
"USA",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "movies2directors"
},
{
"id": 0,
"type": "column",
"value": "movieid"
},
{
"id": 5,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 3,
"type": "table",
"value": "movies"
},
{
"id": 4,
"type": "table",
"value": "u2base"
},
{
"id": 8,
"type": "value",
"value": "Action"
},
{
"id": 7,
"type": "column",
"value": "genre"
},
{
"id": 6,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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9
]
},
{
"entity_id": 2,
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5
]
},
{
"entity_id": 3,
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8
]
},
{
"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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7
]
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{
"entity_id": 9,
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{
"entity_id": 10,
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"entity_id": 11,
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},
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"entity_id": 12,
"token_idxs": []
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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",
"B-VALUE",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,976
|
language_corpus
|
bird:train.json:5721
|
Indicate which is the word that is repeated the most times.
|
SELECT word FROM words WHERE occurrences = ( SELECT MAX(occurrences) FROM words )
|
[
"Indicate",
"which",
"is",
"the",
"word",
"that",
"is",
"repeated",
"the",
"most",
"times",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "occurrences"
},
{
"id": 0,
"type": "table",
"value": "words"
},
{
"id": 1,
"type": "column",
"value": "word"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
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},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,978
|
theme_gallery
|
spider:train_spider.json:1658
|
Count the number of artists who are older than 46 and joined after 1990.
|
SELECT count(*) FROM artist WHERE age > 46 AND year_join > 1990
|
[
"Count",
"the",
"number",
"of",
"artists",
"who",
"are",
"older",
"than",
"46",
"and",
"joined",
"after",
"1990",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "year_join"
},
{
"id": 0,
"type": "table",
"value": "artist"
},
{
"id": 4,
"type": "value",
"value": "1990"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "46"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"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",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,979
|
hr_1
|
spider:train_spider.json:3454
|
What is the average salary of employees who have a commission percentage that is not null?
|
SELECT department_id , AVG(salary) FROM employees WHERE commission_pct != "null" GROUP BY department_id
|
[
"What",
"is",
"the",
"average",
"salary",
"of",
"employees",
"who",
"have",
"a",
"commission",
"percentage",
"that",
"is",
"not",
"null",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "commission_pct"
},
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 4,
"type": "column",
"value": "salary"
},
{
"id": 3,
"type": "column",
"value": "null"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,980
|
formula_1
|
bird:dev.json:961
|
Which race has the shortest actual finishing time? Please give the name and year.
|
SELECT T1.name, T1.year FROM races AS T1 INNER JOIN results AS T2 on T1.raceId = T2.raceId WHERE T2.milliseconds IS NOT NULL ORDER BY T2.milliseconds LIMIT 1
|
[
"Which",
"race",
"has",
"the",
"shortest",
"actual",
"finishing",
"time",
"?",
"Please",
"give",
"the",
"name",
"and",
"year",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "milliseconds"
},
{
"id": 3,
"type": "table",
"value": "results"
},
{
"id": 5,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,981
|
shakespeare
|
bird:train.json:3025
|
Provide the character name, paragraph number, and plain text of "cousin to the king" description.
|
SELECT T1.CharName, T2.ParagraphNum, T2.PlainText FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T1.Description = 'cousin to the king'
|
[
"Provide",
"the",
"character",
"name",
",",
"paragraph",
"number",
",",
"and",
"plain",
"text",
"of",
"\"",
"cousin",
"to",
"the",
"king",
"\"",
"description",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "cousin to the king"
},
{
"id": 1,
"type": "column",
"value": "paragraphnum"
},
{
"id": 8,
"type": "column",
"value": "character_id"
},
{
"id": 5,
"type": "column",
"value": "description"
},
{
"id": 3,
"type": "table",
"value": "characters"
},
{
"id": 4,
"type": "table",
"value": "paragraphs"
},
{
"id": 2,
"type": "column",
"value": "plaintext"
},
{
"id": 0,
"type": "column",
"value": "charname"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
13,
14,
15,
16
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O"
] |
2,982
|
public_review_platform
|
bird:train.json:4057
|
What are the categories of businesses that have opening time on Sunday?
|
SELECT DISTINCT T1.category_name FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T2.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T4.day_of_week = 'Sunday' AND T3.opening_time <> ''
|
[
"What",
"are",
"the",
"categories",
"of",
"businesses",
"that",
"have",
"opening",
"time",
"on",
"Sunday",
"?"
] |
[
{
"id": 8,
"type": "table",
"value": "business_categories"
},
{
"id": 2,
"type": "table",
"value": "business_hours"
},
{
"id": 0,
"type": "column",
"value": "category_name"
},
{
"id": 6,
"type": "column",
"value": "opening_time"
},
{
"id": 4,
"type": "column",
"value": "day_of_week"
},
{
"id": 9,
"type": "column",
"value": "business_id"
},
{
"id": 10,
"type": "column",
"value": "category_id"
},
{
"id": 7,
"type": "table",
"value": "categories"
},
{
"id": 3,
"type": "column",
"value": "day_id"
},
{
"id": 5,
"type": "value",
"value": "Sunday"
},
{
"id": 1,
"type": "table",
"value": "days"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"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": [
8,
9
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"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",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O"
] |
2,983
|
european_football_2
|
bird:dev.json:1146
|
Please provide the full name of the away team that scored the most goals.
|
SELECT t2.team_long_name FROM Match AS t1 INNER JOIN Team AS t2 ON t1.away_team_api_id = t2.team_api_id ORDER BY t1.away_team_goal DESC LIMIT 1
|
[
"Please",
"provide",
"the",
"full",
"name",
"of",
"the",
"away",
"team",
"that",
"scored",
"the",
"most",
"goals",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "away_team_api_id"
},
{
"id": 0,
"type": "column",
"value": "team_long_name"
},
{
"id": 3,
"type": "column",
"value": "away_team_goal"
},
{
"id": 5,
"type": "column",
"value": "team_api_id"
},
{
"id": 1,
"type": "table",
"value": "match"
},
{
"id": 2,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,984
|
european_football_2
|
bird:dev.json:1068
|
From 2010 to 2015, what was the average overall rating of players who are higher than 170?
|
SELECT CAST(SUM(t2.overall_rating) AS REAL) / COUNT(t2.id) FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t1.height > 170 AND STRFTIME('%Y',t2.`date`) >= '2010' AND STRFTIME('%Y',t2.`date`) <= '2015'
|
[
"From",
"2010",
"to",
"2015",
",",
"what",
"was",
"the",
"average",
"overall",
"rating",
"of",
"players",
"who",
"are",
"higher",
"than",
"170",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "player_attributes"
},
{
"id": 10,
"type": "column",
"value": "overall_rating"
},
{
"id": 2,
"type": "column",
"value": "player_api_id"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "column",
"value": "height"
},
{
"id": 5,
"type": "value",
"value": "2010"
},
{
"id": 6,
"type": "value",
"value": "2015"
},
{
"id": 9,
"type": "column",
"value": "date"
},
{
"id": 4,
"type": "value",
"value": "170"
},
{
"id": 7,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": [
1
]
},
{
"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": [
9,
10
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,985
|
cs_semester
|
bird:train.json:891
|
How many students have the highest intelligence among those taking a bachelor's degree?
|
SELECT COUNT(student_id) FROM student WHERE type = 'UG' AND intelligence = ( SELECT MAX(intelligence) FROM student )
|
[
"How",
"many",
"students",
"have",
"the",
"highest",
"intelligence",
"among",
"those",
"taking",
"a",
"bachelor",
"'s",
"degree",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "intelligence"
},
{
"id": 1,
"type": "column",
"value": "student_id"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "type"
},
{
"id": 3,
"type": "value",
"value": "UG"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,986
|
retail_complains
|
bird:train.json:275
|
List all the states in the South region.
|
SELECT state FROM state WHERE Region = 'South'
|
[
"List",
"all",
"the",
"states",
"in",
"the",
"South",
"region",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "region"
},
{
"id": 0,
"type": "table",
"value": "state"
},
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "value",
"value": "South"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,987
|
company_employee
|
spider:train_spider.json:4098
|
What are the headquarters and industries of all companies?
|
SELECT Headquarters , Industry FROM company
|
[
"What",
"are",
"the",
"headquarters",
"and",
"industries",
"of",
"all",
"companies",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "headquarters"
},
{
"id": 2,
"type": "column",
"value": "industry"
},
{
"id": 0,
"type": "table",
"value": "company"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,988
|
authors
|
bird:train.json:3576
|
What is the affiliation of the author writing in the journal 'A combined search for the standard model Higgs boson at s = 1.96 Â TeV'?
|
SELECT T1.Affiliation FROM PaperAuthor AS T1 INNER JOIN Paper AS T2 ON T1.PaperId = T2.Id WHERE T2.Title = 'A combined search for the standard model Higgs boson at s = 1.96 Â TeV'
|
[
"What",
"is",
"the",
"affiliation",
"of",
"the",
"author",
"writing",
"in",
"the",
"journal",
"'",
"A",
"combined",
"search",
"for",
"the",
"standard",
"model",
"Higgs",
"boson",
"at",
"s",
"=",
"1.96",
"Â",
"TeV",
"'",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "A combined search for the standard model Higgs boson at s = 1.96 Â TeV"
},
{
"id": 0,
"type": "column",
"value": "affiliation"
},
{
"id": 1,
"type": "table",
"value": "paperauthor"
},
{
"id": 5,
"type": "column",
"value": "paperid"
},
{
"id": 2,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,989
|
restaurant_1
|
spider:train_spider.json:2821
|
What is the address of the restaurant Subway?
|
SELECT Address FROM Restaurant WHERE ResName = "Subway";
|
[
"What",
"is",
"the",
"address",
"of",
"the",
"restaurant",
"Subway",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "restaurant"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 2,
"type": "column",
"value": "resname"
},
{
"id": 3,
"type": "column",
"value": "Subway"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
2,990
|
soccer_2
|
spider:train_spider.json:4945
|
How many students are enrolled in college?
|
SELECT sum(enr) FROM College
|
[
"How",
"many",
"students",
"are",
"enrolled",
"in",
"college",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "college"
},
{
"id": 1,
"type": "column",
"value": "enr"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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"
] |
2,991
|
menu
|
bird:train.json:5516
|
How much is the price of menu with image ID 4000009194?
|
SELECT T3.price FROM Menu AS T1 INNER JOIN MenuPage AS T2 ON T1.id = T2.menu_id INNER JOIN MenuItem AS T3 ON T2.id = T3.menu_page_id WHERE T2.image_id = 4000009194
|
[
"How",
"much",
"is",
"the",
"price",
"of",
"menu",
"with",
"image",
"ID",
"4000009194",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "menu_page_id"
},
{
"id": 3,
"type": "value",
"value": "4000009194"
},
{
"id": 1,
"type": "table",
"value": "menuitem"
},
{
"id": 2,
"type": "column",
"value": "image_id"
},
{
"id": 5,
"type": "table",
"value": "menupage"
},
{
"id": 8,
"type": "column",
"value": "menu_id"
},
{
"id": 0,
"type": "column",
"value": "price"
},
{
"id": 4,
"type": "table",
"value": "menu"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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"token_idxs": []
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{
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"token_idxs": []
},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,992
|
airline
|
bird:train.json:5910
|
List the air carrier's description with arrival time lower than the 40% of the average arrival time of flights that flew to Phoenix.
|
SELECT T1.Description FROM `Air Carriers` AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.OP_CARRIER_AIRLINE_ID WHERE T2.DEST = 'PHX' AND T2.ARR_TIME < ( SELECT AVG(ARR_TIME) * 0.4 FROM Airlines ) GROUP BY T1.Description
|
[
"List",
"the",
"air",
"carrier",
"'s",
"description",
"with",
"arrival",
"time",
"lower",
"than",
"the",
"40",
"%",
"of",
"the",
"average",
"arrival",
"time",
"of",
"flights",
"that",
"flew",
"to",
"Phoenix",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 1,
"type": "table",
"value": "Air Carriers"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "airlines"
},
{
"id": 7,
"type": "column",
"value": "arr_time"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "dest"
},
{
"id": 6,
"type": "value",
"value": "PHX"
},
{
"id": 8,
"type": "value",
"value": "0.4"
}
] |
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"entity_id": 0,
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3,
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] |
[
"O",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,993
|
authors
|
bird:train.json:3678
|
State the year and title of papers written by Barrasa.
|
SELECT T1.Year, T1.Title FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name = 'Barrasa'
|
[
"State",
"the",
"year",
"and",
"title",
"of",
"papers",
"written",
"by",
"Barrasa",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "paperauthor"
},
{
"id": 5,
"type": "value",
"value": "Barrasa"
},
{
"id": 7,
"type": "column",
"value": "paperid"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "paper"
},
{
"id": 0,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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4
]
},
{
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6
]
},
{
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},
{
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},
{
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9
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},
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},
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},
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},
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"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,994
|
shipping
|
bird:train.json:5681
|
Among the shipments to a customer from Texas, what percentage of the shipments shipped in 2017?
|
SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', T1.ship_date) = '2017' THEN 1 ELSE 0 END) AS REAL ) * 100 / COUNT(*) FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id WHERE T2.state = 'TX'
|
[
"Among",
"the",
"shipments",
"to",
"a",
"customer",
"from",
"Texas",
",",
"what",
"percentage",
"of",
"the",
"shipments",
"shipped",
"in",
"2017",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "ship_date"
},
{
"id": 0,
"type": "table",
"value": "shipment"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 4,
"type": "column",
"value": "cust_id"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 8,
"type": "value",
"value": "2017"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "TX"
},
{
"id": 9,
"type": "value",
"value": "%Y"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
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2
]
},
{
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5
]
},
{
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},
{
"entity_id": 3,
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},
{
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},
{
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},
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"entity_id": 14,
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},
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"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,995
|
inn_1
|
spider:train_spider.json:2610
|
Find the number of rooms for each bed type.
|
SELECT bedType , count(*) FROM Rooms GROUP BY bedType;
|
[
"Find",
"the",
"number",
"of",
"rooms",
"for",
"each",
"bed",
"type",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "bedtype"
},
{
"id": 0,
"type": "table",
"value": "rooms"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,996
|
bbc_channels
|
bird:test.json:135
|
Find the id and name of the channel that is not directed by Hank Baskett.
|
SELECT t1.name , t1.channel_id FROM channel AS t1 JOIN director_admin AS t2 ON t1.channel_id = t2.channel_id JOIN director AS t3 ON t2.director_id = t3.director_id WHERE t3.name != "Hank Baskett"
|
[
"Find",
"the",
"i",
"d",
"and",
"name",
"of",
"the",
"channel",
"that",
"is",
"not",
"directed",
"by",
"Hank",
"Baskett",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "director_admin"
},
{
"id": 3,
"type": "column",
"value": "Hank Baskett"
},
{
"id": 6,
"type": "column",
"value": "director_id"
},
{
"id": 1,
"type": "column",
"value": "channel_id"
},
{
"id": 2,
"type": "table",
"value": "director"
},
{
"id": 4,
"type": "table",
"value": "channel"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
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{
"entity_id": 0,
"token_idxs": [
5
]
},
{
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},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
14,
15
]
},
{
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8
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},
{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
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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",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,997
|
e_commerce
|
bird:test.json:42
|
For the orders with any produts, how many products does each orders contain ? List the order id, status and the number.
|
SELECT T1.order_id , T1.order_status_code , count(*) FROM Orders AS T1 JOIN Order_items AS T2 ON T1.order_id = T2.order_id GROUP BY T1.order_id
|
[
"For",
"the",
"orders",
"with",
"any",
"produts",
",",
"how",
"many",
"products",
"does",
"each",
"orders",
"contain",
"?",
"List",
"the",
"order",
"i",
"d",
",",
"status",
"and",
"the",
"number",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "order_status_code"
},
{
"id": 3,
"type": "table",
"value": "order_items"
},
{
"id": 0,
"type": "column",
"value": "order_id"
},
{
"id": 2,
"type": "table",
"value": "orders"
}
] |
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{
"entity_id": 0,
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17,
18,
19
]
},
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"entity_id": 1,
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20,
21
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},
{
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2
]
},
{
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},
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
2,998
|
codebase_community
|
bird:dev.json:566
|
For the owner user of post No. 65041, what is his/her reputation points?
|
SELECT T1.Reputation FROM users AS T1 INNER JOIN posts AS T2 ON T1.Id = T2.OwnerUserId WHERE T2.Id = 65041
|
[
"For",
"the",
"owner",
"user",
"of",
"post",
"No",
".",
"65041",
",",
"what",
"is",
"his",
"/",
"her",
"reputation",
"points",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "owneruserid"
},
{
"id": 0,
"type": "column",
"value": "reputation"
},
{
"id": 1,
"type": "table",
"value": "users"
},
{
"id": 2,
"type": "table",
"value": "posts"
},
{
"id": 4,
"type": "value",
"value": "65041"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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{
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15
]
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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5
]
},
{
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},
{
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8
]
},
{
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2
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},
{
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},
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"token_idxs": []
},
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},
{
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"token_idxs": []
},
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
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