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13,902
|
pilot_1
|
bird:test.json:1138
|
What are the different plane names, ordered alphabetically?
|
SELECT DISTINCT plane_name FROM pilotskills ORDER BY plane_name
|
[
"What",
"are",
"the",
"different",
"plane",
"names",
",",
"ordered",
"alphabetically",
"?"
] |
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{
"id": 0,
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{
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[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
13,903
|
world
|
bird:train.json:7909
|
List down the cities belongs to the country that has surface area greater than 7000000.
|
SELECT T2.Name, T1.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code WHERE T2.SurfaceArea > 7000000
|
[
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"the",
"country",
"that",
"has",
"surface",
"area",
"greater",
"than",
"7000000",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "surfacearea"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "7000000"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "code"
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"O",
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"O",
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"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,904
|
boat_1
|
bird:test.json:881
|
what is the name and id of every sailor who has a rating greater than 2 and reserved a boat.
|
SELECT DISTINCT T1.name , T1.sid FROM Sailors AS T1 JOIN Reserves AS T2 ON T1.sid = T2.sid WHERE T1.rating > 2
|
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"rating",
"greater",
"than",
"2",
"and",
"reserved",
"a",
"boat",
"."
] |
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"id": 2,
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"value": "rating"
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{
"id": 0,
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"value": "name"
},
{
"id": 1,
"type": "column",
"value": "sid"
},
{
"id": 5,
"type": "value",
"value": "2"
}
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"O",
"O",
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"B-COLUMN",
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"I-COLUMN",
"O",
"O",
"B-TABLE",
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"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
13,906
|
computer_student
|
bird:train.json:1013
|
List the advisor IDs for students with eighth year of program and position status in faculty of those professors.
|
SELECT T1.p_id_dummy, T2.hasPosition FROM advisedBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.yearsInProgram = 'Year_8'
|
[
"List",
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"with",
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"year",
"of",
"program",
"and",
"position",
"status",
"in",
"faculty",
"of",
"those",
"professors",
"."
] |
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{
"id": 4,
"type": "column",
"value": "yearsinprogram"
},
{
"id": 1,
"type": "column",
"value": "hasposition"
},
{
"id": 0,
"type": "column",
"value": "p_id_dummy"
},
{
"id": 2,
"type": "table",
"value": "advisedby"
},
{
"id": 3,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "value",
"value": "Year_8"
},
{
"id": 6,
"type": "column",
"value": "p_id"
}
] |
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] |
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"O",
"O",
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"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,907
|
hospital_1
|
spider:train_spider.json:3909
|
What is the id of the appointment that started most recently?
|
SELECT appointmentid FROM appointment ORDER BY START DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"appointment",
"that",
"started",
"most",
"recently",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "appointmentid"
},
{
"id": 0,
"type": "table",
"value": "appointment"
},
{
"id": 2,
"type": "column",
"value": "start"
}
] |
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] |
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
13,908
|
movie_3
|
bird:train.json:9235
|
In the film with an inventory ID between 20 to 60, how many of the films have a G rating?
|
SELECT COUNT(T1.film_id) FROM film AS T1 INNER JOIN inventory AS T2 ON T1.film_id = T2.film_id WHERE T2.inventory_id BETWEEN 20 AND 60 AND T1.rating = 'G'
|
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"to",
"60",
",",
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"films",
"have",
"a",
"G",
"rating",
"?"
] |
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{
"id": 3,
"type": "column",
"value": "inventory_id"
},
{
"id": 1,
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"value": "inventory"
},
{
"id": 2,
"type": "column",
"value": "film_id"
},
{
"id": 6,
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"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 4,
"type": "value",
"value": "20"
},
{
"id": 5,
"type": "value",
"value": "60"
},
{
"id": 7,
"type": "value",
"value": "G"
}
] |
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"O",
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"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
13,909
|
beer_factory
|
bird:train.json:5251
|
Among all the root beers sold in 2014, what is the percentage of the root beers produced by the brewery AJ Stephans Beverages?
|
SELECT CAST(COUNT(CASE WHEN T3.BreweryName = 'AJ Stephans Beverages' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T1.BrandID) FROM rootbeer AS T1 INNER JOIN `transaction` AS T2 ON T1.RootBeerID = T2.RootBeerID INNER JOIN rootbeerbrand AS T3 ON T1.BrandID = T3.BrandID WHERE T2.TransactionDate LIKE '2014%'
|
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"?"
] |
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{
"id": 1,
"type": "column",
"value": "transactiondate"
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{
"id": 0,
"type": "table",
"value": "rootbeerbrand"
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{
"id": 4,
"type": "table",
"value": "transaction"
},
{
"id": 9,
"type": "column",
"value": "breweryname"
},
{
"id": 7,
"type": "column",
"value": "rootbeerid"
},
{
"id": 3,
"type": "table",
"value": "rootbeer"
},
{
"id": 5,
"type": "column",
"value": "brandid"
},
{
"id": 2,
"type": "value",
"value": "2014%"
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{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "1"
}
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[
"O",
"O",
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"B-TABLE",
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"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
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"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,910
|
financial
|
bird:dev.json:168
|
What percentage of clients who opened their accounts in the district with an average salary of over 10000 are women?
|
SELECT CAST(SUM(T2.gender = 'F') AS REAL) * 100 / COUNT(T2.client_id) FROM district AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id WHERE T1.A11 > 10000
|
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"?"
] |
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{
"id": 4,
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{
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{
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"value": "client"
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"value": "gender"
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{
"id": 3,
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"value": "10000"
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{
"id": 2,
"type": "column",
"value": "a11"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "F"
}
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
13,911
|
world_development_indicators
|
bird:train.json:2179
|
How much is the total urban population of middle income countries in 1960?
|
SELECT SUM(T2.Value) FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.IncomeGroup LIKE '%middle income' AND T2.Year = 1960 AND T2.IndicatorName = 'Urban population'
|
[
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"is",
"the",
"total",
"urban",
"population",
"of",
"middle",
"income",
"countries",
"in",
"1960",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "Urban population"
},
{
"id": 5,
"type": "value",
"value": "%middle income"
},
{
"id": 8,
"type": "column",
"value": "indicatorname"
},
{
"id": 3,
"type": "column",
"value": "countrycode"
},
{
"id": 4,
"type": "column",
"value": "incomegroup"
},
{
"id": 1,
"type": "table",
"value": "indicators"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "value"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "1960"
}
] |
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]
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"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
13,912
|
customers_and_addresses
|
spider:train_spider.json:6119
|
How many orders have detail "Second time"?
|
SELECT count(*) FROM customer_orders WHERE order_details = "Second time"
|
[
"How",
"many",
"orders",
"have",
"detail",
"\"",
"Second",
"time",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "order_details"
},
{
"id": 2,
"type": "column",
"value": "Second time"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
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},
{
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{
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{
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,913
|
wine_1
|
spider:train_spider.json:6546
|
What is the maximum price of wines from the appelation in the Central Coast area, which was produced before 2005?
|
SELECT max(T2.Price) FROM APPELLATIONS AS T1 JOIN WINE AS T2 ON T1.Appelation = T2.Appelation WHERE T1.Area = "Central Coast" AND T2.year < 2005
|
[
"What",
"is",
"the",
"maximum",
"price",
"of",
"wines",
"from",
"the",
"appelation",
"in",
"the",
"Central",
"Coast",
"area",
",",
"which",
"was",
"produced",
"before",
"2005",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Central Coast"
},
{
"id": 0,
"type": "table",
"value": "appellations"
},
{
"id": 3,
"type": "column",
"value": "appelation"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "wine"
},
{
"id": 4,
"type": "column",
"value": "area"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2005"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
12,
13
]
},
{
"entity_id": 6,
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},
{
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{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,914
|
climbing
|
spider:train_spider.json:1125
|
Return the name of the mountain with the greatest height.
|
SELECT Name FROM mountain ORDER BY Height DESC LIMIT 1
|
[
"Return",
"the",
"name",
"of",
"the",
"mountain",
"with",
"the",
"greatest",
"height",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "mountain"
},
{
"id": 2,
"type": "column",
"value": "height"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
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2
]
},
{
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9
]
},
{
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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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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,915
|
address
|
bird:train.json:5110
|
What party does the area with the zip code 91701 belong to?
|
SELECT T1.party FROM congress AS T1 INNER JOIN state AS T2 ON T1.abbreviation = T2.abbreviation INNER JOIN zip_data AS T3 ON T2.abbreviation = T3.state WHERE T3.zip_code = 91701 GROUP BY T1.party
|
[
"What",
"party",
"does",
"the",
"area",
"with",
"the",
"zip",
"code",
"91701",
"belong",
"to",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "abbreviation"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 2,
"type": "column",
"value": "zip_code"
},
{
"id": 4,
"type": "table",
"value": "congress"
},
{
"id": 0,
"type": "column",
"value": "party"
},
{
"id": 3,
"type": "value",
"value": "91701"
},
{
"id": 5,
"type": "table",
"value": "state"
},
{
"id": 7,
"type": "column",
"value": "state"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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},
{
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},
{
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"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",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O"
] |
13,916
|
restaurant
|
bird:train.json:1778
|
In the Bay Area, what is the most common type of food served by restaurants?
|
SELECT T2.food_type FROM geographic AS T1 INNER JOIN generalinfo AS T2 ON T1.city = T2.city WHERE T1.region = 'bay area' GROUP BY T2.food_type ORDER BY COUNT(T2.food_type) DESC LIMIT 1
|
[
"In",
"the",
"Bay",
"Area",
",",
"what",
"is",
"the",
"most",
"common",
"type",
"of",
"food",
"served",
"by",
"restaurants",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "generalinfo"
},
{
"id": 1,
"type": "table",
"value": "geographic"
},
{
"id": 0,
"type": "column",
"value": "food_type"
},
{
"id": 4,
"type": "value",
"value": "bay area"
},
{
"id": 3,
"type": "column",
"value": "region"
},
{
"id": 5,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2,
3
]
},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
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},
{
"entity_id": 8,
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},
{
"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",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,917
|
e_commerce
|
bird:test.json:53
|
What are the ids, names, and prices of all products that are ordered most frequently?
|
SELECT T1.product_id , T1.product_name , T1.product_price FROM Products AS T1 JOIN Order_items AS T2 ON T1.product_id = T2.product_id GROUP BY T1.product_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"are",
"the",
"ids",
",",
"names",
",",
"and",
"prices",
"of",
"all",
"products",
"that",
"are",
"ordered",
"most",
"frequently",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_price"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 4,
"type": "table",
"value": "order_items"
},
{
"id": 0,
"type": "column",
"value": "product_id"
},
{
"id": 3,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
14,
15
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
13,918
|
network_2
|
spider:train_spider.json:4417
|
What is the name of the person whose age is below 30?
|
SELECT name FROM Person WHERE age < 30
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"person",
"whose",
"age",
"is",
"below",
"30",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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,
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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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
13,919
|
image_and_language
|
bird:train.json:7604
|
Write the object classes of image ID 22 alongside the object's width and height.
|
SELECT T1.W, T1.H, T2.OBJ_CLASS FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 22
|
[
"Write",
"the",
"object",
"classes",
"of",
"image",
"ID",
"22",
"alongside",
"the",
"object",
"'s",
"width",
"and",
"height",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "obj_class_id"
},
{
"id": 4,
"type": "table",
"value": "obj_classes"
},
{
"id": 2,
"type": "column",
"value": "obj_class"
},
{
"id": 3,
"type": "table",
"value": "img_obj"
},
{
"id": 5,
"type": "column",
"value": "img_id"
},
{
"id": 6,
"type": "value",
"value": "22"
},
{
"id": 0,
"type": "column",
"value": "w"
},
{
"id": 1,
"type": "column",
"value": "h"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2,
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5,
6
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,920
|
sakila_1
|
spider:train_spider.json:2982
|
How many kinds of different ratings are listed?
|
SELECT count(DISTINCT rating) FROM film
|
[
"How",
"many",
"kinds",
"of",
"different",
"ratings",
"are",
"listed",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"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",
"O",
"O"
] |
13,921
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6459
|
Show ids for all documents in type CV without expense budgets.
|
SELECT document_id FROM Documents WHERE document_type_code = "CV" EXCEPT SELECT document_id FROM Documents_with_expenses
|
[
"Show",
"ids",
"for",
"all",
"documents",
"in",
"type",
"CV",
"without",
"expense",
"budgets",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "documents_with_expenses"
},
{
"id": 3,
"type": "column",
"value": "document_type_code"
},
{
"id": 2,
"type": "column",
"value": "document_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
},
{
"id": 4,
"type": "column",
"value": "CV"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,923
|
advertising_agencies
|
bird:test.json:2091
|
What are client ids for clients with at least 2 invoices.
|
SELECT client_id FROM Invoices GROUP BY client_id HAVING count(*) >= 2
|
[
"What",
"are",
"client",
"ids",
"for",
"clients",
"with",
"at",
"least",
"2",
"invoices",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "table",
"value": "invoices"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
13,924
|
european_football_2
|
bird:dev.json:1045
|
What is the attacking work rate of the football playerr Franco Zennaro?
|
SELECT DISTINCT t2.attacking_work_rate FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t1.player_name = 'Franco Zennaro'
|
[
"What",
"is",
"the",
"attacking",
"work",
"rate",
"of",
"the",
"football",
"playerr",
"Franco",
"Zennaro",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "attacking_work_rate"
},
{
"id": 2,
"type": "table",
"value": "player_attributes"
},
{
"id": 4,
"type": "value",
"value": "Franco Zennaro"
},
{
"id": 5,
"type": "column",
"value": "player_api_id"
},
{
"id": 3,
"type": "column",
"value": "player_name"
},
{
"id": 1,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
13,925
|
hospital_1
|
spider:train_spider.json:3971
|
What are the three most costly procedures?
|
SELECT name FROM procedures ORDER BY cost LIMIT 3
|
[
"What",
"are",
"the",
"three",
"most",
"costly",
"procedures",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "procedures"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "cost"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
13,926
|
address
|
bird:train.json:5132
|
Which district has the largest land area in Wisconsin? Write the full name of the congress representative and include the postal codes.
|
SELECT T2.zip_code, T1.first_name, T1.last_name FROM congress AS T1 INNER JOIN zip_congress AS T2 ON T1.cognress_rep_id = T2.district WHERE T1.state = 'Wisconsin' ORDER BY T1.land_area DESC LIMIT 1
|
[
"Which",
"district",
"has",
"the",
"largest",
"land",
"area",
"in",
"Wisconsin",
"?",
"Write",
"the",
"full",
"name",
"of",
"the",
"congress",
"representative",
"and",
"include",
"the",
"postal",
"codes",
"."
] |
[
{
"id": 8,
"type": "column",
"value": "cognress_rep_id"
},
{
"id": 4,
"type": "table",
"value": "zip_congress"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 6,
"type": "value",
"value": "Wisconsin"
},
{
"id": 7,
"type": "column",
"value": "land_area"
},
{
"id": 0,
"type": "column",
"value": "zip_code"
},
{
"id": 3,
"type": "table",
"value": "congress"
},
{
"id": 9,
"type": "column",
"value": "district"
},
{
"id": 5,
"type": "column",
"value": "state"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
22
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": [
5,
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
1
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,927
|
world_development_indicators
|
bird:train.json:2159
|
List out the name and indicator code of high income: nonOECD countries
|
SELECT DISTINCT T1.CountryCode, T2.CountryName FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.IncomeGroup = 'High income: nonOECD'
|
[
"List",
"out",
"the",
"name",
"and",
"indicator",
"code",
"of",
"high",
"income",
":",
"nonOECD",
"countries"
] |
[
{
"id": 5,
"type": "value",
"value": "High income: nonOECD"
},
{
"id": 0,
"type": "column",
"value": "countrycode"
},
{
"id": 1,
"type": "column",
"value": "countryname"
},
{
"id": 4,
"type": "column",
"value": "incomegroup"
},
{
"id": 3,
"type": "table",
"value": "indicators"
},
{
"id": 2,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
8,
10,
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"B-TABLE"
] |
13,928
|
flight_1
|
spider:train_spider.json:367
|
How many employees have salary between 100000 and 200000?
|
SELECT count(*) FROM Employee WHERE salary BETWEEN 100000 AND 200000
|
[
"How",
"many",
"employees",
"have",
"salary",
"between",
"100000",
"and",
"200000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "column",
"value": "salary"
},
{
"id": 2,
"type": "value",
"value": "100000"
},
{
"id": 3,
"type": "value",
"value": "200000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,929
|
loan_1
|
spider:train_spider.json:3080
|
Find the total amount of loans provided by bank branches in the state of New York.
|
SELECT sum(T2.amount) FROM bank AS T1 JOIN loan AS T2 ON T1.branch_id = T2.branch_id WHERE T1.state = 'New York'
|
[
"Find",
"the",
"total",
"amount",
"of",
"loans",
"provided",
"by",
"bank",
"branches",
"in",
"the",
"state",
"of",
"New",
"York",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "branch_id"
},
{
"id": 3,
"type": "value",
"value": "New York"
},
{
"id": 4,
"type": "column",
"value": "amount"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "bank"
},
{
"id": 1,
"type": "table",
"value": "loan"
}
] |
[
{
"entity_id": 0,
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8
]
},
{
"entity_id": 1,
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5
]
},
{
"entity_id": 2,
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12
]
},
{
"entity_id": 3,
"token_idxs": [
14,
15
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,930
|
music_1
|
spider:train_spider.json:3604
|
What is the shortest and most poorly rated song for each genre, ordered alphabetically by genre?
|
SELECT min(T1.duration) , min(T2.rating) , T2.genre_is FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id GROUP BY T2.genre_is ORDER BY T2.genre_is
|
[
"What",
"is",
"the",
"shortest",
"and",
"most",
"poorly",
"rated",
"song",
"for",
"each",
"genre",
",",
"ordered",
"alphabetically",
"by",
"genre",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "genre_is"
},
{
"id": 3,
"type": "column",
"value": "duration"
},
{
"id": 4,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "table",
"value": "files"
},
{
"id": 2,
"type": "table",
"value": "song"
},
{
"id": 5,
"type": "column",
"value": "f_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
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"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,931
|
retail_world
|
bird:train.json:6445
|
List the first names of the employees who take the orders that ship to the city of "Reims".
|
SELECT DISTINCT T1.FirstName FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE T2.ShipCity = 'Reims'
|
[
"List",
"the",
"first",
"names",
"of",
"the",
"employees",
"who",
"take",
"the",
"orders",
"that",
"ship",
"to",
"the",
"city",
"of",
"\"",
"Reims",
"\"",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "shipcity"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 4,
"type": "value",
"value": "Reims"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,932
|
public_review_platform
|
bird:train.json:3967
|
What is the percentage for the Yelp businesses in "Pets" category of all businesses?
|
SELECT CAST(SUM(CASE WHEN T2.category_name = 'Pets' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.category_name) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id
|
[
"What",
"is",
"the",
"percentage",
"for",
"the",
"Yelp",
"businesses",
"in",
"\"",
"Pets",
"\"",
"category",
"of",
"all",
"businesses",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "business_categories"
},
{
"id": 4,
"type": "column",
"value": "category_name"
},
{
"id": 2,
"type": "column",
"value": "category_id"
},
{
"id": 1,
"type": "table",
"value": "categories"
},
{
"id": 7,
"type": "value",
"value": "Pets"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
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12
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O"
] |
13,933
|
synthea
|
bird:train.json:1428
|
Describe the care plans received by the patient with secondary malignant neoplasm of the colon.
|
SELECT DISTINCT T1.DESCRIPTION FROM careplans AS T1 INNER JOIN conditions AS T2 ON T1.patient = T2.PATIENT WHERE T2.DESCRIPTION = 'Secondary malignant neoplasm of colon'
|
[
"Describe",
"the",
"care",
"plans",
"received",
"by",
"the",
"patient",
"with",
"secondary",
"malignant",
"neoplasm",
"of",
"the",
"colon",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Secondary malignant neoplasm of colon"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "conditions"
},
{
"id": 1,
"type": "table",
"value": "careplans"
},
{
"id": 4,
"type": "column",
"value": "patient"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11,
12,
13,
14
]
},
{
"entity_id": 4,
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7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,934
|
cars
|
bird:train.json:3081
|
Which is the origin country of the $44274.40748 car?
|
SELECT T3.country FROM price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country WHERE T1.price = 44274.40748
|
[
"Which",
"is",
"the",
"origin",
"country",
"of",
"the",
"$",
"44274.40748",
"car",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "44274.40748"
},
{
"id": 5,
"type": "table",
"value": "production"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "origin"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 4,
"type": "table",
"value": "price"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
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"token_idxs": []
},
{
"entity_id": 1,
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4
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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8
]
},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
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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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},
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
13,935
|
app_store
|
bird:train.json:2520
|
What are the top 5 installed free apps?
|
SELECT App FROM playstore WHERE Price = 0 ORDER BY CAST(REPLACE(REPLACE(Installs, ',', ''), '+', '') AS INTEGER) DESC LIMIT 5
|
[
"What",
"are",
"the",
"top",
"5",
"installed",
"free",
"apps",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "playstore"
},
{
"id": 5,
"type": "column",
"value": "installs"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "column",
"value": "app"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "+"
},
{
"id": 6,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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7
]
},
{
"entity_id": 2,
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},
{
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{
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{
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5
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},
{
"entity_id": 7,
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{
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{
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
13,936
|
coffee_shop
|
spider:train_spider.json:792
|
Find the ids and names of members who are under age 30 or with black membership card.
|
SELECT name , member_id FROM member WHERE Membership_card = 'Black' OR age < 30
|
[
"Find",
"the",
"ids",
"and",
"names",
"of",
"members",
"who",
"are",
"under",
"age",
"30",
"or",
"with",
"black",
"membership",
"card",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "membership_card"
},
{
"id": 2,
"type": "column",
"value": "member_id"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 4,
"type": "value",
"value": "Black"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "age"
},
{
"id": 6,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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4
]
},
{
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},
{
"entity_id": 3,
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15,
16
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
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},
{
"entity_id": 15,
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},
{
"entity_id": 16,
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},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,937
|
codebase_community
|
bird:dev.json:619
|
How many adults who obtained the badge Supporter?
|
SELECT COUNT(T1.Id) FROM users AS T1 INNER JOIN badges AS T2 ON T1.Id = T2.UserId WHERE T2.Name = 'Supporter' AND T1.Age BETWEEN 19 AND 65
|
[
"How",
"many",
"adults",
"who",
"obtained",
"the",
"badge",
"Supporter",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Supporter"
},
{
"id": 1,
"type": "table",
"value": "badges"
},
{
"id": 3,
"type": "column",
"value": "userid"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "19"
},
{
"id": 8,
"type": "value",
"value": "65"
}
] |
[
{
"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": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,938
|
customers_and_orders
|
bird:test.json:240
|
What are the ids, type codes, and names for all products?
|
SELECT product_id , product_type_code , product_name FROM Products
|
[
"What",
"are",
"the",
"ids",
",",
"type",
"codes",
",",
"and",
"names",
"for",
"all",
"products",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "product_type_code"
},
{
"id": 3,
"type": "column",
"value": "product_name"
},
{
"id": 1,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,939
|
books
|
bird:train.json:6019
|
List all the titles of the Spanish books published by Alfaguara.
|
SELECT T2.title FROM book_language AS T1 INNER JOIN book AS T2 ON T2.language_id = T1.language_id INNER JOIN publisher AS T3 ON T3.publisher_id = T2.publisher_id WHERE T1.language_name = 'Spanish' AND T3.publisher_name = 'Alfaguara' GROUP BY T2.title
|
[
"List",
"all",
"the",
"titles",
"of",
"the",
"Spanish",
"books",
"published",
"by",
"Alfaguara",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "publisher_name"
},
{
"id": 2,
"type": "table",
"value": "book_language"
},
{
"id": 5,
"type": "column",
"value": "language_name"
},
{
"id": 4,
"type": "column",
"value": "publisher_id"
},
{
"id": 9,
"type": "column",
"value": "language_id"
},
{
"id": 1,
"type": "table",
"value": "publisher"
},
{
"id": 8,
"type": "value",
"value": "Alfaguara"
},
{
"id": 6,
"type": "value",
"value": "Spanish"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
13,940
|
tracking_share_transactions
|
spider:train_spider.json:5870
|
Show the average amount of transactions for different investors.
|
SELECT investor_id , avg(amount_of_transaction) FROM TRANSACTIONS GROUP BY investor_id
|
[
"Show",
"the",
"average",
"amount",
"of",
"transactions",
"for",
"different",
"investors",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "amount_of_transaction"
},
{
"id": 0,
"type": "table",
"value": "transactions"
},
{
"id": 1,
"type": "column",
"value": "investor_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
13,941
|
cre_Theme_park
|
spider:train_spider.json:5936
|
What is the average price range of hotels for each each star rating code?
|
SELECT star_rating_code , avg(price_range) FROM HOTELS GROUP BY star_rating_code
|
[
"What",
"is",
"the",
"average",
"price",
"range",
"of",
"hotels",
"for",
"each",
"each",
"star",
"rating",
"code",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "star_rating_code"
},
{
"id": 2,
"type": "column",
"value": "price_range"
},
{
"id": 0,
"type": "table",
"value": "hotels"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
11,
12,
13
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
13,942
|
college_completion
|
bird:train.json:3727
|
Give the total number of all graduated students from a 2-year public schools in Alabama in 2011.
|
SELECT SUM(T2.grad_cohort) FROM state_sector_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.stateid = T1.stateid WHERE T1.state = 'Alabama' AND T2.year = 2011 AND T1.level = '2-year' AND T1.control = 'Public' AND T2.race = 'X'
|
[
"Give",
"the",
"total",
"number",
"of",
"all",
"graduated",
"students",
"from",
"a",
"2",
"-",
"year",
"public",
"schools",
"in",
"Alabama",
"in",
"2011",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "state_sector_details"
},
{
"id": 1,
"type": "table",
"value": "state_sector_grads"
},
{
"id": 2,
"type": "column",
"value": "grad_cohort"
},
{
"id": 3,
"type": "column",
"value": "stateid"
},
{
"id": 5,
"type": "value",
"value": "Alabama"
},
{
"id": 10,
"type": "column",
"value": "control"
},
{
"id": 9,
"type": "value",
"value": "2-year"
},
{
"id": 11,
"type": "value",
"value": "Public"
},
{
"id": 4,
"type": "column",
"value": "state"
},
{
"id": 8,
"type": "column",
"value": "level"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2011"
},
{
"id": 12,
"type": "column",
"value": "race"
},
{
"id": 13,
"type": "value",
"value": "X"
}
] |
[
{
"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": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
18
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
10,
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
13
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-VALUE",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,943
|
software_company
|
bird:train.json:8553
|
How many teenagers are working as Machine-op-inspct?
|
SELECT COUNT(ID) teenager_number FROM Customers WHERE OCCUPATION = 'Machine-op-inspct' AND age >= 13 AND age <= 19
|
[
"How",
"many",
"teenagers",
"are",
"working",
"as",
"Machine",
"-",
"op",
"-",
"inspct",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Machine-op-inspct"
},
{
"id": 2,
"type": "column",
"value": "occupation"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "13"
},
{
"id": 6,
"type": "value",
"value": "19"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"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",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
13,944
|
conference
|
bird:test.json:1092
|
What are the names of the conferences that have the top 2 most people attending?
|
SELECT T1.conference_name FROM Conference AS T1 JOIN Conference_participation AS T2 ON T1.conference_id = T2.conference_id GROUP BY T2.conference_id ORDER BY count(*) DESC LIMIT 2
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"conferences",
"that",
"have",
"the",
"top",
"2",
"most",
"people",
"attending",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "conference_participation"
},
{
"id": 1,
"type": "column",
"value": "conference_name"
},
{
"id": 0,
"type": "column",
"value": "conference_id"
},
{
"id": 2,
"type": "table",
"value": "conference"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,945
|
california_schools
|
bird:dev.json:68
|
Which county reported the most number of school closure in the 1980s with school wonership code belonging to Youth Authority Facilities (CEA)?
|
SELECT County FROM schools WHERE strftime('%Y', ClosedDate) BETWEEN '1980' AND '1989' AND StatusType = 'Closed' AND SOC = 11 GROUP BY County ORDER BY COUNT(School) DESC LIMIT 1
|
[
"Which",
"county",
"reported",
"the",
"most",
"number",
"of",
"school",
"closure",
"in",
"the",
"1980s",
"with",
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"wonership",
"code",
"belonging",
"to",
"Youth",
"Authority",
"Facilities",
"(",
"CEA",
")",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "statustype"
},
{
"id": 10,
"type": "column",
"value": "closeddate"
},
{
"id": 0,
"type": "table",
"value": "schools"
},
{
"id": 1,
"type": "column",
"value": "county"
},
{
"id": 5,
"type": "value",
"value": "Closed"
},
{
"id": 8,
"type": "column",
"value": "school"
},
{
"id": 2,
"type": "value",
"value": "1980"
},
{
"id": 3,
"type": "value",
"value": "1989"
},
{
"id": 6,
"type": "column",
"value": "soc"
},
{
"id": 7,
"type": "value",
"value": "11"
},
{
"id": 9,
"type": "value",
"value": "%Y"
}
] |
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1
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{
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"O",
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"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,946
|
coinmarketcap
|
bird:train.json:6251
|
List the price for Zetacoin on 13/11/1 and the next 7 consecutive days. What is the average price for these 7 days?
|
SELECT T2.price FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Zetacoin' AND T2.date BETWEEN '2013-11-01' AND '2013-11-07' UNION ALL SELECT AVG(T2.PRICE) FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T1.name = 'Zetacoin' AND T2.date BETWEEN '2013-11-01' AND '2013-11-07'
|
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"the",
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"for",
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"?"
] |
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{
"id": 8,
"type": "value",
"value": "2013-11-01"
},
{
"id": 9,
"type": "value",
"value": "2013-11-07"
},
{
"id": 6,
"type": "value",
"value": "Zetacoin"
},
{
"id": 4,
"type": "column",
"value": "coin_id"
},
{
"id": 0,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,947
|
books
|
bird:train.json:5926
|
How much money on average does Lucas Wyldbore spend on book orders?
|
SELECT SUM(T1.price) / COUNT(*) FROM order_line AS T1 INNER JOIN cust_order AS T2 ON T2.order_id = T1.order_id INNER JOIN customer AS T3 ON T3.customer_id = T2.customer_id WHERE T3.first_name = 'Lucas' AND T3.last_name = 'Wyldbore'
|
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"spend",
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"?"
] |
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{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "table",
"value": "order_line"
},
{
"id": 2,
"type": "table",
"value": "cust_order"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 7,
"type": "value",
"value": "Wyldbore"
},
{
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"type": "column",
"value": "order_id"
},
{
"id": 5,
"type": "value",
"value": "Lucas"
},
{
"id": 8,
"type": "column",
"value": "price"
}
] |
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[
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"O",
"B-VALUE",
"B-VALUE",
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"O",
"O",
"B-COLUMN",
"O"
] |
13,949
|
cookbook
|
bird:train.json:8894
|
What are the names of the top 5 recipes that are best for wound healing?
|
SELECT T1.title FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id ORDER BY T2.vitamin_c DESC LIMIT 5
|
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"?"
] |
[
{
"id": 2,
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{
"id": 3,
"type": "column",
"value": "vitamin_c"
},
{
"id": 4,
"type": "column",
"value": "recipe_id"
},
{
"id": 1,
"type": "table",
"value": "recipe"
},
{
"id": 0,
"type": "column",
"value": "title"
}
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{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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] |
[
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"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,950
|
chicago_crime
|
bird:train.json:8706
|
In which ward of more than 55,000 inhabitants are there more crimes of intimidation with extortion?
|
SELECT T3.ward_no FROM IUCR AS T1 INNER JOIN Crime AS T2 ON T2.iucr_no = T1.iucr_no INNER JOIN Ward AS T3 ON T3.ward_no = T2.ward_no WHERE T1.primary_description = 'INTIMIDATION' AND T1.secondary_description = 'EXTORTION' AND T3.Population > 55000 GROUP BY T3.ward_no ORDER BY COUNT(T3.ward_no) DESC LIMIT 1
|
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"with",
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"?"
] |
[
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"type": "column",
"value": "secondary_description"
},
{
"id": 4,
"type": "column",
"value": "primary_description"
},
{
"id": 5,
"type": "value",
"value": "INTIMIDATION"
},
{
"id": 8,
"type": "column",
"value": "population"
},
{
"id": 7,
"type": "value",
"value": "EXTORTION"
},
{
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"type": "column",
"value": "ward_no"
},
{
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"type": "column",
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{
"id": 3,
"type": "table",
"value": "crime"
},
{
"id": 9,
"type": "value",
"value": "55000"
},
{
"id": 1,
"type": "table",
"value": "ward"
},
{
"id": 2,
"type": "table",
"value": "iucr"
}
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[
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"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
13,951
|
synthea
|
bird:train.json:1376
|
What is the prevalence percentage of condition no. 64859006?
|
SELECT DISTINCT T1."PREVALENCE PERCENTAGE" FROM all_prevalences AS T1 INNER JOIN conditions AS T2 ON lower(T1.ITEM) = lower(T2.DESCRIPTION) WHERE T2.code = '64859006'
|
[
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"64859006",
"?"
] |
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{
"id": 0,
"type": "column",
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{
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"type": "table",
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{
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"type": "column",
"value": "description"
},
{
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"type": "table",
"value": "conditions"
},
{
"id": 4,
"type": "value",
"value": "64859006"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "column",
"value": "item"
}
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"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
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13,952
|
restaurant
|
bird:train.json:1724
|
Which county is El Cerrito from?
|
SELECT county FROM geographic WHERE city = 'el cerrito'
|
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"from",
"?"
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{
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"type": "value",
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{
"id": 1,
"type": "column",
"value": "county"
},
{
"id": 2,
"type": "column",
"value": "city"
}
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{
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] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
13,953
|
college_completion
|
bird:train.json:3754
|
What is the name of the school with the highest number of first-time, full-time, degree-seeking female students in the cohort being tracked, minus any exclusions who were seeking another type of degree or certificate at a 4-year institution?
|
SELECT T1.chronname FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T2.gender = 'F' AND T2.cohort = '4y other' ORDER BY T2.grad_cohort DESC LIMIT 1
|
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"type": "column",
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{
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"type": "column",
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{
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},
{
"entity_id": 2,
"token_idxs": [
48
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
27
]
},
{
"entity_id": 8,
"token_idxs": [
37
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,954
|
european_football_2
|
bird:dev.json:1089
|
How many matches in the 2008/2009 season were held in Belgium?
|
SELECT COUNT(t2.id) FROM Country AS t1 INNER JOIN Match AS t2 ON t1.id = t2.country_id WHERE t1.name = 'Belgium' AND t2.season = '2008/2009'
|
[
"How",
"many",
"matches",
"in",
"the",
"2008/2009",
"season",
"were",
"held",
"in",
"Belgium",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "country_id"
},
{
"id": 7,
"type": "value",
"value": "2008/2009"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "value",
"value": "Belgium"
},
{
"id": 6,
"type": "column",
"value": "season"
},
{
"id": 1,
"type": "table",
"value": "match"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"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-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,955
|
pilot_1
|
bird:test.json:1178
|
How many pilots are older than the youngest pilot who has Piper Cub?
|
SELECT count(pilot_name) FROM pilotskills WHERE age > (SELECT min(age) FROM pilotskills WHERE plane_name = 'Piper Cub')
|
[
"How",
"many",
"pilots",
"are",
"older",
"than",
"the",
"youngest",
"pilot",
"who",
"has",
"Piper",
"Cub",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 2,
"type": "column",
"value": "pilot_name"
},
{
"id": 3,
"type": "column",
"value": "plane_name"
},
{
"id": 4,
"type": "value",
"value": "Piper Cub"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,956
|
public_review_platform
|
bird:train.json:4082
|
Among the elite users of 10 consecutive year from 2005 to 2014, list down the user ID and their number of compliment on photos.
|
SELECT T2.user_id, T2.number_of_compliments FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id INNER JOIN Elite AS T3 ON T2.user_id = T3.user_id WHERE T3.year_id BETWEEN 2005 AND 2014 AND T1.compliment_type = 'photos'
|
[
"Among",
"the",
"elite",
"users",
"of",
"10",
"consecutive",
"year",
"from",
"2005",
"to",
"2014",
",",
"list",
"down",
"the",
"user",
"ID",
"and",
"their",
"number",
"of",
"compliment",
"on",
"photos",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "number_of_compliments"
},
{
"id": 4,
"type": "table",
"value": "users_compliments"
},
{
"id": 8,
"type": "column",
"value": "compliment_type"
},
{
"id": 10,
"type": "column",
"value": "compliment_id"
},
{
"id": 3,
"type": "table",
"value": "compliments"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 5,
"type": "column",
"value": "year_id"
},
{
"id": 9,
"type": "value",
"value": "photos"
},
{
"id": 2,
"type": "table",
"value": "elite"
},
{
"id": 6,
"type": "value",
"value": "2005"
},
{
"id": 7,
"type": "value",
"value": "2014"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16,
17
]
},
{
"entity_id": 1,
"token_idxs": [
20,
21
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
22
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
24
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
13,957
|
insurance_fnol
|
spider:train_spider.json:908
|
Count the total number of policies used by the customer named "Dayana Robel".
|
SELECT count(*) FROM customers AS t1 JOIN customers_policies AS t2 ON t1.customer_id = t2.customer_id WHERE t1.customer_name = "Dayana Robel"
|
[
"Count",
"the",
"total",
"number",
"of",
"policies",
"used",
"by",
"the",
"customer",
"named",
"\"",
"Dayana",
"Robel",
"\"",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "customers_policies"
},
{
"id": 2,
"type": "column",
"value": "customer_name"
},
{
"id": 3,
"type": "column",
"value": "Dayana Robel"
},
{
"id": 4,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,958
|
book_1
|
bird:test.json:572
|
Give the average sale price of books authored by George Orwell.
|
SELECT avg(saleprice) FROM Book AS T1 JOIN Author_book AS T2 ON T1.isbn = T2.isbn JOIN Author AS T3 ON T2.Author = T3.idAuthor WHERE T3.name = "George Orwell"
|
[
"Give",
"the",
"average",
"sale",
"price",
"of",
"books",
"authored",
"by",
"George",
"Orwell",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "George Orwell"
},
{
"id": 5,
"type": "table",
"value": "author_book"
},
{
"id": 3,
"type": "column",
"value": "saleprice"
},
{
"id": 7,
"type": "column",
"value": "idauthor"
},
{
"id": 0,
"type": "table",
"value": "author"
},
{
"id": 6,
"type": "column",
"value": "author"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "table",
"value": "book"
},
{
"id": 8,
"type": "column",
"value": "isbn"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
3,
4
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,959
|
insurance_and_eClaims
|
spider:train_spider.json:1538
|
For each policy type, return its type code and its count in the record.
|
SELECT policy_type_code , count(*) FROM policies GROUP BY policy_type_code
|
[
"For",
"each",
"policy",
"type",
",",
"return",
"its",
"type",
"code",
"and",
"its",
"count",
"in",
"the",
"record",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "policy_type_code"
},
{
"id": 0,
"type": "table",
"value": "policies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
13,960
|
pilot_record
|
spider:train_spider.json:2095
|
Show the names of pilots and the number of records they have.
|
SELECT T2.Pilot_name , COUNT(*) FROM pilot_record AS T1 JOIN pilot AS T2 ON T1.pilot_ID = T2.pilot_ID GROUP BY T2.Pilot_name
|
[
"Show",
"the",
"names",
"of",
"pilots",
"and",
"the",
"number",
"of",
"records",
"they",
"have",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "pilot_record"
},
{
"id": 0,
"type": "column",
"value": "pilot_name"
},
{
"id": 3,
"type": "column",
"value": "pilot_id"
},
{
"id": 2,
"type": "table",
"value": "pilot"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
13,961
|
music_2
|
spider:train_spider.json:5178
|
Find all the stage positions of the musicians with first name "Solveig"
|
SELECT DISTINCT T1.stageposition FROM Performance AS T1 JOIN Band AS T2 ON T1.bandmate = T2.id WHERE Firstname = "Solveig"
|
[
"Find",
"all",
"the",
"stage",
"positions",
"of",
"the",
"musicians",
"with",
"first",
"name",
"\"",
"Solveig",
"\""
] |
[
{
"id": 0,
"type": "column",
"value": "stageposition"
},
{
"id": 1,
"type": "table",
"value": "performance"
},
{
"id": 3,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 4,
"type": "column",
"value": "Solveig"
},
{
"id": 2,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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},
{
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"token_idxs": []
},
{
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9,
10
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},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
0
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{
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{
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{
"entity_id": 12,
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"entity_id": 13,
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{
"entity_id": 14,
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},
{
"entity_id": 15,
"token_idxs": []
},
{
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O"
] |
13,962
|
student_club
|
bird:dev.json:1345
|
How many majors are there in "College of Humanities and Social Sciences"?
|
SELECT COUNT(major_name) FROM major WHERE college = 'College of Humanities and Social Sciences'
|
[
"How",
"many",
"majors",
"are",
"there",
"in",
"\"",
"College",
"of",
"Humanities",
"and",
"Social",
"Sciences",
"\"",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "College of Humanities and Social Sciences"
},
{
"id": 3,
"type": "column",
"value": "major_name"
},
{
"id": 1,
"type": "column",
"value": "college"
},
{
"id": 0,
"type": "table",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
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{
"entity_id": 1,
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7
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{
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8,
9,
10,
11,
12
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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": 9,
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},
{
"entity_id": 10,
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{
"entity_id": 11,
"token_idxs": []
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{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,963
|
card_games
|
bird:dev.json:523
|
What is the annual average number of sets that were released between 1/1/2012 to 12/31/2015? Indicate the common langugage of the card.
|
SELECT (CAST(SUM(T1.id) AS REAL) / COUNT(T1.id)) / 4, T2.language FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.id = T2.id WHERE T1.releaseDate BETWEEN '2012-01-01' AND '2015-12-31' GROUP BY T1.releaseDate ORDER BY COUNT(T2.language) DESC LIMIT 1
|
[
"What",
"is",
"the",
"annual",
"average",
"number",
"of",
"sets",
"that",
"were",
"released",
"between",
"1/1/2012",
"to",
"12/31/2015",
"?",
"Indicate",
"the",
"common",
"langugage",
"of",
"the",
"card",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "set_translations"
},
{
"id": 0,
"type": "column",
"value": "releasedate"
},
{
"id": 4,
"type": "value",
"value": "2012-01-01"
},
{
"id": 5,
"type": "value",
"value": "2015-12-31"
},
{
"id": 1,
"type": "column",
"value": "language"
},
{
"id": 2,
"type": "table",
"value": "sets"
},
{
"id": 7,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
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19
]
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{
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7
]
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{
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{
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},
{
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},
{
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{
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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",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
13,964
|
music_1
|
spider:train_spider.json:3609
|
Find the names and number of works of the three artists who have produced the most songs.
|
SELECT T1.artist_name , count(*) FROM artist AS T1 JOIN song AS T2 ON T1.artist_name = T2.artist_name GROUP BY T2.artist_name ORDER BY count(*) DESC LIMIT 3
|
[
"Find",
"the",
"names",
"and",
"number",
"of",
"works",
"of",
"the",
"three",
"artists",
"who",
"have",
"produced",
"the",
"most",
"songs",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "artist_name"
},
{
"id": 1,
"type": "table",
"value": "artist"
},
{
"id": 2,
"type": "table",
"value": "song"
}
] |
[
{
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"token_idxs": []
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{
"entity_id": 1,
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10
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
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"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
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{
"entity_id": 6,
"token_idxs": []
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{
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{
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{
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"token_idxs": []
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{
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"entity_id": 11,
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,965
|
customers_and_addresses
|
spider:train_spider.json:6068
|
Find the name of the customers who use the most frequently used payment method.
|
SELECT customer_name FROM customers WHERE payment_method = (SELECT payment_method FROM customers GROUP BY payment_method ORDER BY count(*) DESC LIMIT 1)
|
[
"Find",
"the",
"name",
"of",
"the",
"customers",
"who",
"use",
"the",
"most",
"frequently",
"used",
"payment",
"method",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "payment_method"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12,
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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
13,966
|
planet_1
|
bird:test.json:1856
|
What is the name of the client who received the heaviest package?
|
SELECT T2.Name FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Recipient = T2.AccountNumber ORDER BY T1.Weight DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"client",
"who",
"received",
"the",
"heaviest",
"package",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "accountnumber"
},
{
"id": 4,
"type": "column",
"value": "recipient"
},
{
"id": 1,
"type": "table",
"value": "package"
},
{
"id": 2,
"type": "table",
"value": "client"
},
{
"id": 3,
"type": "column",
"value": "weight"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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11
]
},
{
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"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
0
]
},
{
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},
{
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},
{
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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": []
}
] |
[
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,967
|
college_1
|
spider:train_spider.json:3253
|
What is the name of the department that has the largest number of students enrolled?
|
SELECT T4.dept_name FROM CLASS AS T1 JOIN enroll AS T2 ON T1.class_code = T2.class_code JOIN course AS T3 ON T1.crs_code = T3.crs_code JOIN department AS T4 ON T3.dept_code = T4.dept_code GROUP BY T3.dept_code ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"department",
"that",
"has",
"the",
"largest",
"number",
"of",
"students",
"enrolled",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 7,
"type": "column",
"value": "class_code"
},
{
"id": 0,
"type": "column",
"value": "dept_code"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 6,
"type": "column",
"value": "crs_code"
},
{
"id": 3,
"type": "table",
"value": "course"
},
{
"id": 5,
"type": "table",
"value": "enroll"
},
{
"id": 4,
"type": "table",
"value": "class"
}
] |
[
{
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"token_idxs": []
},
{
"entity_id": 1,
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6
]
},
{
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},
{
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},
{
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{
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{
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{
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{
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{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,968
|
soccer_2
|
spider:train_spider.json:5035
|
What are the names of all the states with college students playing in the mid position but no goalies?
|
SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'mid' EXCEPT SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'goalie'
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"the",
"states",
"with",
"college",
"students",
"playing",
"in",
"the",
"mid",
"position",
"but",
"no",
"goalies",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "college"
},
{
"id": 2,
"type": "table",
"value": "tryout"
},
{
"id": 5,
"type": "value",
"value": "goalie"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "cname"
},
{
"id": 3,
"type": "column",
"value": "ppos"
},
{
"id": 4,
"type": "value",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
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9
]
},
{
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},
{
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},
{
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14
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
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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": []
},
{
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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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,969
|
works_cycles
|
bird:train.json:7165
|
What's Kevin A Wright's email address?
|
SELECT T2.EmailAddress FROM Person AS T1 INNER JOIN EmailAddress AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.FirstName = 'Kevin' AND T1.MiddleName = 'A' AND T1.LastName = 'Wright'
|
[
"What",
"'s",
"Kevin",
"A",
"Wright",
"'s",
"email",
"address",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "column",
"value": "emailaddress"
},
{
"id": 2,
"type": "table",
"value": "emailaddress"
},
{
"id": 6,
"type": "column",
"value": "middlename"
},
{
"id": 4,
"type": "column",
"value": "firstname"
},
{
"id": 8,
"type": "column",
"value": "lastname"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 9,
"type": "value",
"value": "Wright"
},
{
"id": 5,
"type": "value",
"value": "Kevin"
},
{
"id": 7,
"type": "value",
"value": "A"
}
] |
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"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
4
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-VALUE",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
13,971
|
book_2
|
spider:train_spider.json:220
|
List the publisher of the publication with the highest price.
|
SELECT Publisher FROM publication ORDER BY Price DESC LIMIT 1
|
[
"List",
"the",
"publisher",
"of",
"the",
"publication",
"with",
"the",
"highest",
"price",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "publication"
},
{
"id": 1,
"type": "column",
"value": "publisher"
},
{
"id": 2,
"type": "column",
"value": "price"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,972
|
bakery_1
|
bird:test.json:1581
|
What are the flavors available for Cake but not for Tart?
|
SELECT DISTINCT flavor FROM goods WHERE food = "Cake" EXCEPT SELECT DISTINCT flavor FROM goods WHERE food = "Tart"
|
[
"What",
"are",
"the",
"flavors",
"available",
"for",
"Cake",
"but",
"not",
"for",
"Tart",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "flavor"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 2,
"type": "column",
"value": "food"
},
{
"id": 3,
"type": "column",
"value": "Cake"
},
{
"id": 4,
"type": "column",
"value": "Tart"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,973
|
legislator
|
bird:train.json:4875
|
List the official full names of all the legislators who have facebook, instagram, twitter and youtube accounts.
|
SELECT T1.official_full_name FROM current AS T1 INNER JOIN `social-media` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.facebook IS NOT NULL AND T2.instagram IS NOT NULL AND T2.twitter IS NOT NULL AND T2.youtube IS NOT NULL
|
[
"List",
"the",
"official",
"full",
"names",
"of",
"all",
"the",
"legislators",
"who",
"have",
"facebook",
",",
"instagram",
",",
"twitter",
"and",
"youtube",
"accounts",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "official_full_name"
},
{
"id": 2,
"type": "table",
"value": "social-media"
},
{
"id": 3,
"type": "column",
"value": "bioguide_id"
},
{
"id": 6,
"type": "column",
"value": "instagram"
},
{
"id": 4,
"type": "column",
"value": "bioguide"
},
{
"id": 5,
"type": "column",
"value": "facebook"
},
{
"id": 1,
"type": "table",
"value": "current"
},
{
"id": 7,
"type": "column",
"value": "twitter"
},
{
"id": 8,
"type": "column",
"value": "youtube"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": [
17
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
13,975
|
cre_Doc_and_collections
|
bird:test.json:735
|
List all name of collections that are related to collection named Best.
|
SELECT DISTINCT T4.Collection_Name FROM Collection_Subset_Members AS T1 JOIN Collection_Subset_Members AS T2 ON T1.Related_Collection_ID = T2.Collection_ID JOIN Collections AS T3 ON T1.Collection_ID = T3.Collection_ID JOIN Collections AS T4 ON T2.Collection_ID = T4.Collection_ID WHERE T3.Collection_Name = "Best";
|
[
"List",
"all",
"name",
"of",
"collections",
"that",
"are",
"related",
"to",
"collection",
"named",
"Best",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "collection_subset_members"
},
{
"id": 5,
"type": "column",
"value": "related_collection_id"
},
{
"id": 0,
"type": "column",
"value": "collection_name"
},
{
"id": 3,
"type": "column",
"value": "collection_id"
},
{
"id": 1,
"type": "table",
"value": "collections"
},
{
"id": 2,
"type": "column",
"value": "Best"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7,
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O"
] |
13,976
|
soccer_2
|
spider:train_spider.json:5028
|
Find the names of states that have some college students playing in goalie and mid positions.
|
SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'goalie' INTERSECT SELECT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.pPos = 'mid'
|
[
"Find",
"the",
"names",
"of",
"states",
"that",
"have",
"some",
"college",
"students",
"playing",
"in",
"goalie",
"and",
"mid",
"positions",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "college"
},
{
"id": 2,
"type": "table",
"value": "tryout"
},
{
"id": 4,
"type": "value",
"value": "goalie"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "cname"
},
{
"id": 3,
"type": "column",
"value": "ppos"
},
{
"id": 5,
"type": "value",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O"
] |
13,977
|
soccer_1
|
spider:train_spider.json:1296
|
What is the maximum and minimum height of all players?
|
SELECT max(weight) , min(weight) FROM Player
|
[
"What",
"is",
"the",
"maximum",
"and",
"minimum",
"height",
"of",
"all",
"players",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "column",
"value": "weight"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
13,978
|
codebase_comments
|
bird:train.json:685
|
Provide the github address with the summary of method "A test for Decompose
".
|
SELECT T1.Url FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId INNER JOIN Method AS T3 ON T2.Id = T3.SolutionId WHERE T3.Summary = 'A test for Decompose'
|
[
"Provide",
"the",
"github",
"address",
"with",
"the",
"summary",
"of",
"method",
"\"",
"A",
"test",
"for",
"Decompose",
"\n",
"\"",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "A test for Decompose"
},
{
"id": 7,
"type": "column",
"value": "solutionid"
},
{
"id": 5,
"type": "table",
"value": "solution"
},
{
"id": 2,
"type": "column",
"value": "summary"
},
{
"id": 1,
"type": "table",
"value": "method"
},
{
"id": 8,
"type": "column",
"value": "repoid"
},
{
"id": 4,
"type": "table",
"value": "repo"
},
{
"id": 0,
"type": "column",
"value": "url"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
13,979
|
allergy_1
|
spider:train_spider.json:473
|
How many students are age 18?
|
SELECT count(*) FROM Student WHERE age = 18
|
[
"How",
"many",
"students",
"are",
"age",
"18",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "18"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
13,980
|
book_1
|
bird:test.json:583
|
How many orders do we have for "Pride and Prejudice"?
|
SELECT count(*) FROM Book AS T1 JOIN Books_Order AS T2 ON T1.isbn = T2.isbn WHERE T1.title = "Pride and Prejudice"
|
[
"How",
"many",
"orders",
"do",
"we",
"have",
"for",
"\"",
"Pride",
"and",
"Prejudice",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Pride and Prejudice"
},
{
"id": 1,
"type": "table",
"value": "books_order"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "book"
},
{
"id": 4,
"type": "column",
"value": "isbn"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
13,981
|
college_1
|
spider:train_spider.json:3329
|
Find the first names of professors who are teaching more than one class.
|
SELECT T2.emp_fname FROM CLASS AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num GROUP BY T1.prof_num HAVING count(*) > 1
|
[
"Find",
"the",
"first",
"names",
"of",
"professors",
"who",
"are",
"teaching",
"more",
"than",
"one",
"class",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "emp_fname"
},
{
"id": 0,
"type": "column",
"value": "prof_num"
},
{
"id": 3,
"type": "table",
"value": "employee"
},
{
"id": 5,
"type": "column",
"value": "emp_num"
},
{
"id": 2,
"type": "table",
"value": "class"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,983
|
performance_attendance
|
spider:train_spider.json:1313
|
Show different locations and the number of performances at each location.
|
SELECT LOCATION , COUNT(*) FROM performance GROUP BY LOCATION
|
[
"Show",
"different",
"locations",
"and",
"the",
"number",
"of",
"performances",
"at",
"each",
"location",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "performance"
},
{
"id": 1,
"type": "column",
"value": "location"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
13,984
|
insurance_fnol
|
spider:train_spider.json:927
|
What are the maximum and minimum settlement amount on record?
|
SELECT max(settlement_amount) , min(settlement_amount) FROM settlements
|
[
"What",
"are",
"the",
"maximum",
"and",
"minimum",
"settlement",
"amount",
"on",
"record",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "settlement_amount"
},
{
"id": 0,
"type": "table",
"value": "settlements"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O"
] |
13,986
|
shop_membership
|
spider:train_spider.json:5415
|
What are the different membership levels?
|
SELECT count(DISTINCT LEVEL) FROM member
|
[
"What",
"are",
"the",
"different",
"membership",
"levels",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 1,
"type": "column",
"value": "level"
}
] |
[
{
"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"
] |
13,987
|
books
|
bird:train.json:5946
|
How many orders in 2022 have Iran as their destinations?
|
SELECT COUNT(*) FROM country AS T1 INNER JOIN address AS T2 ON T1.country_id = T2.country_id INNER JOIN cust_order AS T3 ON T3.dest_address_id = T2.address_id WHERE T1.country_name = 'Iran' AND STRFTIME('%Y', T3.order_date) = '2022'
|
[
"How",
"many",
"orders",
"in",
"2022",
"have",
"Iran",
"as",
"their",
"destinations",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "dest_address_id"
},
{
"id": 5,
"type": "column",
"value": "country_name"
},
{
"id": 0,
"type": "table",
"value": "cust_order"
},
{
"id": 4,
"type": "column",
"value": "address_id"
},
{
"id": 8,
"type": "column",
"value": "country_id"
},
{
"id": 10,
"type": "column",
"value": "order_date"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "address"
},
{
"id": 6,
"type": "value",
"value": "Iran"
},
{
"id": 7,
"type": "value",
"value": "2022"
},
{
"id": 9,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
2
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
13,988
|
mental_health_survey
|
bird:train.json:4583
|
What is the oldest age of the users in 2014's survey?
|
SELECT T2.AnswerText FROM Question AS T1 INNER JOIN Answer AS T2 ON T1.questionid = T2.QuestionID WHERE T1.questiontext = 'What is your age?' AND T2.SurveyID = 2014 ORDER BY T2.AnswerText DESC LIMIT 1
|
[
"What",
"is",
"the",
"oldest",
"age",
"of",
"the",
"users",
"in",
"2014",
"'s",
"survey",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "What is your age?"
},
{
"id": 4,
"type": "column",
"value": "questiontext"
},
{
"id": 0,
"type": "column",
"value": "answertext"
},
{
"id": 3,
"type": "column",
"value": "questionid"
},
{
"id": 1,
"type": "table",
"value": "question"
},
{
"id": 6,
"type": "column",
"value": "surveyid"
},
{
"id": 2,
"type": "table",
"value": "answer"
},
{
"id": 7,
"type": "value",
"value": "2014"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7,
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
0,
1,
2,
3,
4
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
13,989
|
apartment_rentals
|
spider:train_spider.json:1270
|
Show the apartment numbers of apartments with bookings that have status code both "Provisional" and "Confirmed"
|
SELECT T2.apt_number FROM Apartment_Bookings AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id WHERE T1.booking_status_code = "Confirmed" INTERSECT SELECT T2.apt_number FROM Apartment_Bookings AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id WHERE T1.booking_status_code = "Provisional"
|
[
"Show",
"the",
"apartment",
"numbers",
"of",
"apartments",
"with",
"bookings",
"that",
"have",
"status",
"code",
"both",
"\"",
"Provisional",
"\"",
"and",
"\"",
"Confirmed",
"\""
] |
[
{
"id": 3,
"type": "column",
"value": "booking_status_code"
},
{
"id": 1,
"type": "table",
"value": "apartment_bookings"
},
{
"id": 5,
"type": "column",
"value": "Provisional"
},
{
"id": 0,
"type": "column",
"value": "apt_number"
},
{
"id": 2,
"type": "table",
"value": "apartments"
},
{
"id": 4,
"type": "column",
"value": "Confirmed"
},
{
"id": 6,
"type": "column",
"value": "apt_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"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-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
13,990
|
cre_Doc_Control_Systems
|
spider:train_spider.json:2108
|
List all document ids and receipt dates of documents.
|
SELECT document_id , receipt_date FROM Documents;
|
[
"List",
"all",
"document",
"ids",
"and",
"receipt",
"dates",
"of",
"documents",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "receipt_date"
},
{
"id": 1,
"type": "column",
"value": "document_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O"
] |
13,991
|
cre_Theme_park
|
spider:train_spider.json:5943
|
Show the details and star ratings of the 3 least expensive hotels.
|
SELECT other_hotel_details , star_rating_code FROM HOTELS ORDER BY price_range ASC LIMIT 3
|
[
"Show",
"the",
"details",
"and",
"star",
"ratings",
"of",
"the",
"3",
"least",
"expensive",
"hotels",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "other_hotel_details"
},
{
"id": 2,
"type": "column",
"value": "star_rating_code"
},
{
"id": 3,
"type": "column",
"value": "price_range"
},
{
"id": 0,
"type": "table",
"value": "hotels"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
13,993
|
public_review_platform
|
bird:train.json:3983
|
For the business with great experience existed in Sun Lakes city, provide the user ID who gave review on it and user followers.
|
SELECT T3.user_id, T3.user_fans FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id INNER JOIN Users AS T3 ON T2.user_id = T3.user_id WHERE T1.city = 'Sun Lakes' AND T1.stars = 5
|
[
"For",
"the",
"business",
"with",
"great",
"experience",
"existed",
"in",
"Sun",
"Lakes",
"city",
",",
"provide",
"the",
"user",
"ID",
"who",
"gave",
"review",
"on",
"it",
"and",
"user",
"followers",
"."
] |
[
{
"id": 9,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "column",
"value": "user_fans"
},
{
"id": 6,
"type": "value",
"value": "Sun Lakes"
},
{
"id": 3,
"type": "table",
"value": "business"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "table",
"value": "reviews"
},
{
"id": 2,
"type": "table",
"value": "users"
},
{
"id": 7,
"type": "column",
"value": "stars"
},
{
"id": 5,
"type": "column",
"value": "city"
},
{
"id": 8,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
22
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
8,
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-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,994
|
mountain_photos
|
spider:train_spider.json:3724
|
List the brands of lenses that took both a picture of mountains with range 'Toubkal Atlas' and a picture of mountains with range 'Lasta Massif'
|
SELECT T3.brand FROM mountain AS T1 JOIN photos AS T2 ON T1.id = T2.mountain_id JOIN camera_lens AS T3 ON T2.camera_lens_id = T3.id WHERE T1.range = 'Toubkal Atlas' INTERSECT SELECT T3.brand FROM mountain AS T1 JOIN photos AS T2 ON T1.id = T2.mountain_id JOIN camera_lens AS T3 ON T2.camera_lens_id = T3.id WHERE T1.range = 'Lasta Massif'
|
[
"List",
"the",
"brands",
"of",
"lenses",
"that",
"took",
"both",
"a",
"picture",
"of",
"mountains",
"with",
"range",
"'",
"Toubkal",
"Atlas",
"'",
"and",
"a",
"picture",
"of",
"mountains",
"with",
"range",
"'",
"Lasta",
"Massif",
"'"
] |
[
{
"id": 7,
"type": "column",
"value": "camera_lens_id"
},
{
"id": 3,
"type": "value",
"value": "Toubkal Atlas"
},
{
"id": 4,
"type": "value",
"value": "Lasta Massif"
},
{
"id": 1,
"type": "table",
"value": "camera_lens"
},
{
"id": 9,
"type": "column",
"value": "mountain_id"
},
{
"id": 5,
"type": "table",
"value": "mountain"
},
{
"id": 6,
"type": "table",
"value": "photos"
},
{
"id": 0,
"type": "column",
"value": "brand"
},
{
"id": 2,
"type": "column",
"value": "range"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
24
]
},
{
"entity_id": 3,
"token_idxs": [
15,
16
]
},
{
"entity_id": 4,
"token_idxs": [
26,
27
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
22
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
13,995
|
retail_world
|
bird:train.json:6303
|
Among the employees working as Sales Representatives, how many of them are located in the UK?
|
SELECT COUNT(Country) FROM Employees WHERE Title = 'Sales Representative' AND Country = 'UK'
|
[
"Among",
"the",
"employees",
"working",
"as",
"Sales",
"Representatives",
",",
"how",
"many",
"of",
"them",
"are",
"located",
"in",
"the",
"UK",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Sales Representative"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "value",
"value": "UK"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5,
6
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
13,996
|
card_games
|
bird:dev.json:480
|
What is the Italian flavor text of the card "Ancestor's Chosen"?
|
SELECT T2.flavorText FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T2.uuid = T1.uuid WHERE T1.name = 'Ancestor''s Chosen' AND T2.language = 'Italian'
|
[
"What",
"is",
"the",
"Italian",
"flavor",
"text",
"of",
"the",
"card",
"\"",
"Ancestor",
"'s",
"Chosen",
"\"",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Ancestor's Chosen"
},
{
"id": 2,
"type": "table",
"value": "foreign_data"
},
{
"id": 0,
"type": "column",
"value": "flavortext"
},
{
"id": 6,
"type": "column",
"value": "language"
},
{
"id": 7,
"type": "value",
"value": "Italian"
},
{
"id": 1,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "column",
"value": "uuid"
},
{
"id": 4,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
13,997
|
social_media
|
bird:train.json:780
|
What is the text of the tweet that got the most `likes`?
|
SELECT text FROM twitter WHERE Likes = ( SELECT MAX( Likes) FROM twitter )
|
[
"What",
"is",
"the",
"text",
"of",
"the",
"tweet",
"that",
"got",
"the",
"most",
"`",
"likes",
"`",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "twitter"
},
{
"id": 2,
"type": "column",
"value": "likes"
},
{
"id": 1,
"type": "column",
"value": "text"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
13,998
|
music_4
|
spider:train_spider.json:6191
|
Show the famous titles of the artists with both volumes that lasted more than 2 weeks on top and volumes that lasted less than 2 weeks on top.
|
SELECT T1.Famous_Title FROM artist AS T1 JOIN volume AS T2 ON T1.Artist_ID = T2.Artist_ID WHERE T2.Weeks_on_Top > 2 INTERSECT SELECT T1.Famous_Title FROM artist AS T1 JOIN volume AS T2 ON T1.Artist_ID = T2.Artist_ID WHERE T2.Weeks_on_Top < 2
|
[
"Show",
"the",
"famous",
"titles",
"of",
"the",
"artists",
"with",
"both",
"volumes",
"that",
"lasted",
"more",
"than",
"2",
"weeks",
"on",
"top",
"and",
"volumes",
"that",
"lasted",
"less",
"than",
"2",
"weeks",
"on",
"top",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "famous_title"
},
{
"id": 3,
"type": "column",
"value": "weeks_on_top"
},
{
"id": 5,
"type": "column",
"value": "artist_id"
},
{
"id": 1,
"type": "table",
"value": "artist"
},
{
"id": 2,
"type": "table",
"value": "volume"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
19
]
},
{
"entity_id": 3,
"token_idxs": [
25,
26,
27
]
},
{
"entity_id": 4,
"token_idxs": [
24
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
13,999
|
books
|
bird:train.json:5978
|
Provide the authors and titles of the books which have more than 3000 pages.
|
SELECT T3.author_name, T1.title FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T1.num_pages > 3000
|
[
"Provide",
"the",
"authors",
"and",
"titles",
"of",
"the",
"books",
"which",
"have",
"more",
"than",
"3000",
"pages",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "author_name"
},
{
"id": 6,
"type": "table",
"value": "book_author"
},
{
"id": 3,
"type": "column",
"value": "num_pages"
},
{
"id": 7,
"type": "column",
"value": "author_id"
},
{
"id": 8,
"type": "column",
"value": "book_id"
},
{
"id": 2,
"type": "table",
"value": "author"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "value",
"value": "3000"
},
{
"id": 5,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,000
|
world_development_indicators
|
bird:train.json:2196
|
How many countries are using the same type of currency? Please list the short names of any 3 countries.
|
SELECT ShortName FROM country WHERE currencyunit = 'U.S. dollar' LIMIT 3
|
[
"How",
"many",
"countries",
"are",
"using",
"the",
"same",
"type",
"of",
"currency",
"?",
"Please",
"list",
"the",
"short",
"names",
"of",
"any",
"3",
"countries",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "currencyunit"
},
{
"id": 3,
"type": "value",
"value": "U.S. dollar"
},
{
"id": 1,
"type": "column",
"value": "shortname"
},
{
"id": 0,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
14,
15
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,001
|
assets_maintenance
|
spider:train_spider.json:3127
|
How many assets does each maintenance contract contain? List the number and the contract id.
|
SELECT count(*) , T1.maintenance_contract_id FROM Maintenance_Contracts AS T1 JOIN Assets AS T2 ON T1.maintenance_contract_id = T2.maintenance_contract_id GROUP BY T1.maintenance_contract_id
|
[
"How",
"many",
"assets",
"does",
"each",
"maintenance",
"contract",
"contain",
"?",
"List",
"the",
"number",
"and",
"the",
"contract",
"i",
"d."
] |
[
{
"id": 0,
"type": "column",
"value": "maintenance_contract_id"
},
{
"id": 1,
"type": "table",
"value": "maintenance_contracts"
},
{
"id": 2,
"type": "table",
"value": "assets"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,002
|
cre_Doc_Workflow
|
bird:test.json:2037
|
Show the number of process status.
|
SELECT count(*) FROM Process_status
|
[
"Show",
"the",
"number",
"of",
"process",
"status",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "process_status"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
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",
"B-TABLE",
"I-TABLE",
"O"
] |
14,003
|
cre_Students_Information_Systems
|
bird:test.json:483
|
How many courses do teachers teach at most? Also find the id of the teacher who teaches the most.
|
SELECT count(*) , teacher_id FROM Classes GROUP BY teacher_id ORDER BY count(*) DESC LIMIT 1
|
[
"How",
"many",
"courses",
"do",
"teachers",
"teach",
"at",
"most",
"?",
"Also",
"find",
"the",
"i",
"d",
"of",
"the",
"teacher",
"who",
"teaches",
"the",
"most",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "teacher_id"
},
{
"id": 0,
"type": "table",
"value": "classes"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
14,004
|
card_games
|
bird:dev.json:404
|
Indicates the name of all the languages into which the set whose number of cards is 309 is translated.
|
SELECT T2.language FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.code = T2.setCode WHERE T1.baseSetSize = 309
|
[
"Indicates",
"the",
"name",
"of",
"all",
"the",
"languages",
"into",
"which",
"the",
"set",
"whose",
"number",
"of",
"cards",
"is",
"309",
"is",
"translated",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "set_translations"
},
{
"id": 3,
"type": "column",
"value": "basesetsize"
},
{
"id": 0,
"type": "column",
"value": "language"
},
{
"id": 6,
"type": "column",
"value": "setcode"
},
{
"id": 1,
"type": "table",
"value": "sets"
},
{
"id": 5,
"type": "column",
"value": "code"
},
{
"id": 4,
"type": "value",
"value": "309"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O"
] |
14,005
|
ice_hockey_draft
|
bird:train.json:6979
|
List the names of all players from Avangard Omsk who played in the 2000-2001 season of the International league that have no goals in draft year.
|
SELECT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2000-2001' AND T1.LEAGUE = 'International' AND T1.TEAM = 'Czech Republic (all)' AND T1.G = 0
|
[
"List",
"the",
"names",
"of",
"all",
"players",
"from",
"Avangard",
"Omsk",
"who",
"played",
"in",
"the",
"2000",
"-",
"2001",
"season",
"of",
"the",
"International",
"league",
"that",
"have",
"no",
"goals",
"in",
"draft",
"year",
"."
] |
[
{
"id": 9,
"type": "value",
"value": "Czech Republic (all)"
},
{
"id": 7,
"type": "value",
"value": "International"
},
{
"id": 1,
"type": "table",
"value": "seasonstatus"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 2,
"type": "table",
"value": "playerinfo"
},
{
"id": 5,
"type": "value",
"value": "2000-2001"
},
{
"id": 3,
"type": "column",
"value": "eliteid"
},
{
"id": 4,
"type": "column",
"value": "season"
},
{
"id": 6,
"type": "column",
"value": "league"
},
{
"id": 8,
"type": "column",
"value": "team"
},
{
"id": 10,
"type": "column",
"value": "g"
},
{
"id": 11,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"entity_id": 8,
"token_idxs": [
1,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
14,006
|
chinook_1
|
spider:train_spider.json:862
|
What are the addresses of customers living in Germany who have had an invoice?
|
SELECT DISTINCT T1.Address FROM CUSTOMER AS T1 JOIN INVOICE AS T2 ON T1.CustomerId = T2.CustomerId WHERE T1.country = "Germany"
|
[
"What",
"are",
"the",
"addresses",
"of",
"customers",
"living",
"in",
"Germany",
"who",
"have",
"had",
"an",
"invoice",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 2,
"type": "table",
"value": "invoice"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "Germany"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
14,007
|
superstore
|
bird:train.json:2376
|
Which customer ordered 'Global High-Back Leather Tilter, Burgundy' on 10/13/2013 in the East region?
|
SELECT DISTINCT T2.`Customer Name` FROM east_superstore AS T1 INNER JOIN people AS T2 ON T1.`Customer ID` = T2.`Customer ID` INNER JOIN product AS T3 ON T3.`Product ID` = T1.`Product ID` WHERE T3.`Product Name` = 'Global High-Back Leather Tilter, Burgundy' AND T1.`Order Date` = '2013-10-13' AND T1.Region = 'East'
|
[
"Which",
"customer",
"ordered",
"'",
"Global",
"High",
"-",
"Back",
"Leather",
"Tilter",
",",
"Burgundy",
"'",
"on",
"10/13/2013",
"in",
"the",
"East",
"region",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Global High-Back Leather Tilter, Burgundy"
},
{
"id": 2,
"type": "table",
"value": "east_superstore"
},
{
"id": 0,
"type": "column",
"value": "Customer Name"
},
{
"id": 5,
"type": "column",
"value": "Product Name"
},
{
"id": 11,
"type": "column",
"value": "Customer ID"
},
{
"id": 4,
"type": "column",
"value": "Product ID"
},
{
"id": 7,
"type": "column",
"value": "Order Date"
},
{
"id": 8,
"type": "value",
"value": "2013-10-13"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 3,
"type": "table",
"value": "people"
},
{
"id": 9,
"type": "column",
"value": "region"
},
{
"id": 10,
"type": "value",
"value": "East"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4,
5,
6,
7,
8,
9,
10,
11
]
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": [
14
]
},
{
"entity_id": 9,
"token_idxs": [
18
]
},
{
"entity_id": 10,
"token_idxs": [
17
]
},
{
"entity_id": 11,
"token_idxs": [
1
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
14,008
|
driving_school
|
spider:train_spider.json:6668
|
When did customer with first name as Carole and last name as Bernhard became a customer?
|
SELECT date_became_customer FROM Customers WHERE first_name = "Carole" AND last_name = "Bernhard";
|
[
"When",
"did",
"customer",
"with",
"first",
"name",
"as",
"Carole",
"and",
"last",
"name",
"as",
"Bernhard",
"became",
"a",
"customer",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "date_became_customer"
},
{
"id": 2,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "column",
"value": "Bernhard"
},
{
"id": 3,
"type": "column",
"value": "Carole"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
13,
14
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
14,009
|
allergy_1
|
spider:train_spider.json:521
|
What are the allergies and their types that the student with first name Lisa has? And order the result by name of allergies.
|
SELECT T1.Allergy , T1.AllergyType FROM Allergy_type AS T1 JOIN Has_allergy AS T2 ON T1.Allergy = T2.Allergy JOIN Student AS T3 ON T3.StuID = T2.StuID WHERE T3.Fname = "Lisa" ORDER BY T1.Allergy
|
[
"What",
"are",
"the",
"allergies",
"and",
"their",
"types",
"that",
"the",
"student",
"with",
"first",
"name",
"Lisa",
"has",
"?",
"And",
"order",
"the",
"result",
"by",
"name",
"of",
"allergies",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "allergy_type"
},
{
"id": 1,
"type": "column",
"value": "allergytype"
},
{
"id": 6,
"type": "table",
"value": "has_allergy"
},
{
"id": 0,
"type": "column",
"value": "allergy"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 3,
"type": "column",
"value": "fname"
},
{
"id": 7,
"type": "column",
"value": "stuid"
},
{
"id": 4,
"type": "column",
"value": "Lisa"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
23
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
21
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
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