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15,738
|
legislator
|
bird:train.json:4777
|
Which party does Christopher Henderson Clark belong to?
|
SELECT T1.party FROM `historical-terms` AS T1 INNER JOIN historical AS T2 ON T2.bioguide_id = T1.bioguide WHERE T2.first_name OR T2.middle_name OR T2.last_name = 'ChristopherHendersonClark'
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15,739
|
card_games
|
bird:dev.json:479
|
Among the cards with converted mana cost higher than 5 in the set Coldsnap, how many of them have unknown power?
|
SELECT SUM(CASE WHEN T1.power LIKE '*' OR T1.power IS NULL THEN 1 ELSE 0 END) FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T2.name = 'Coldsnap' AND T1.convertedManaCost > 5
|
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"O",
"O",
"O",
"O",
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15,741
|
game_1
|
spider:train_spider.json:5996
|
What are the average, minimum, and max ages for each of the different majors?
|
SELECT major , avg(age) , min(age) , max(age) FROM Student GROUP BY major
|
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"value": "age"
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"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,742
|
social_media
|
bird:train.json:853
|
Tweets posted from which city has a higher number of average likes, Bangkok or Chiang Mai?
|
SELECT SUM(CASE WHEN T2.City = 'Bangkok' THEN Likes ELSE NULL END) / COUNT(CASE WHEN T2.City = 'Bangkok' THEN 1 ELSE 0 END) AS bNum , SUM(CASE WHEN City = 'Chiang Mai' THEN Likes ELSE NULL END) / COUNT(CASE WHEN City = 'Chiang Mai' THEN TweetID ELSE NULL END) AS cNum FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T2.City IN ('Bangkok', 'Chiang Mai')
|
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"type": "value",
"value": "0"
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{
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"value": "1"
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"O",
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"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,743
|
department_management
|
spider:train_spider.json:4
|
What is the average number of employees of the departments whose rank is between 10 and 15?
|
SELECT avg(num_employees) FROM department WHERE ranking BETWEEN 10 AND 15
|
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"value": "10"
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{
"id": 3,
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"value": "15"
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"O",
"O",
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"O",
"B-VALUE",
"O"
] |
15,744
|
formula_1
|
spider:train_spider.json:2159
|
Find the distinct names of all races held between 2014 and 2017?
|
SELECT DISTINCT name FROM races WHERE YEAR BETWEEN 2014 AND 2017
|
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"value": "name"
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{
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"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2014"
},
{
"id": 4,
"type": "value",
"value": "2017"
}
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[
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"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
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15,745
|
movie_1
|
spider:train_spider.json:2441
|
Who directed Avatar?
|
SELECT director FROM Movie WHERE title = 'Avatar'
|
[
"Who",
"directed",
"Avatar",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "director"
},
{
"id": 3,
"type": "value",
"value": "Avatar"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 2,
"type": "column",
"value": "title"
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[
"O",
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"B-VALUE",
"O"
] |
15,746
|
student_club
|
bird:dev.json:1465
|
Which budget category does the expense 'Posters' fall to?
|
SELECT DISTINCT T2.category FROM expense AS T1 INNER JOIN budget AS T2 ON T1.link_to_budget = T2.budget_id WHERE T1.expense_description = 'Posters'
|
[
"Which",
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"category",
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"the",
"expense",
"'",
"Posters",
"'",
"fall",
"to",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "expense_description"
},
{
"id": 5,
"type": "column",
"value": "link_to_budget"
},
{
"id": 6,
"type": "column",
"value": "budget_id"
},
{
"id": 0,
"type": "column",
"value": "category"
},
{
"id": 1,
"type": "table",
"value": "expense"
},
{
"id": 4,
"type": "value",
"value": "Posters"
},
{
"id": 2,
"type": "table",
"value": "budget"
}
] |
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[
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"O",
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"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
15,747
|
student_loan
|
bird:train.json:4495
|
Among the students with payment due, how many of them are unemployed?
|
SELECT COUNT(T1.name) FROM no_payment_due AS T1 INNER JOIN unemployed AS T2 ON T2.name = T1.name WHERE T1.bool = 'pos'
|
[
"Among",
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"students",
"with",
"payment",
"due",
",",
"how",
"many",
"of",
"them",
"are",
"unemployed",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "no_payment_due"
},
{
"id": 1,
"type": "table",
"value": "unemployed"
},
{
"id": 2,
"type": "column",
"value": "bool"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "pos"
}
] |
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{
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"token_idxs": [
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"token_idxs": []
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"token_idxs": []
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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-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,748
|
sales_in_weather
|
bird:train.json:8173
|
How many inches of total precipitation was recorded by the weather station of store no.2 on 2012/12/25?
|
SELECT T1.preciptotal FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr WHERE T1.`date` = '2012-12-25' AND T2.store_nbr = 2
|
[
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"of",
"total",
"precipitation",
"was",
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"station",
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"no.2",
"on",
"2012/12/25",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "preciptotal"
},
{
"id": 3,
"type": "column",
"value": "station_nbr"
},
{
"id": 5,
"type": "value",
"value": "2012-12-25"
},
{
"id": 6,
"type": "column",
"value": "store_nbr"
},
{
"id": 2,
"type": "table",
"value": "relation"
},
{
"id": 1,
"type": "table",
"value": "weather"
},
{
"id": 4,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "2"
}
] |
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}
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[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
15,749
|
retail_world
|
bird:train.json:6655
|
List out the full name of employee who has birth day on "3/4/1955 12:00:00 AM".
|
SELECT FirstName, LastName FROM Employees WHERE BirthDate = '1955-03-04 00:00:00'
|
[
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"full",
"name",
"of",
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"who",
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"birth",
"day",
"on",
"\"",
"3/4/1955",
"12:00:00",
"AM",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "1955-03-04 00:00:00"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 3,
"type": "column",
"value": "birthdate"
},
{
"id": 2,
"type": "column",
"value": "lastname"
}
] |
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4
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},
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},
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},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
15,750
|
match_season
|
spider:train_spider.json:1077
|
Give the different positions of players who play for the country with the capital Dublin.
|
SELECT DISTINCT T2.Position FROM country AS T1 JOIN match_season AS T2 ON T1.Country_id = T2.Country WHERE T1.Capital = "Dublin"
|
[
"Give",
"the",
"different",
"positions",
"of",
"players",
"who",
"play",
"for",
"the",
"country",
"with",
"the",
"capital",
"Dublin",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "match_season"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 0,
"type": "column",
"value": "position"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "capital"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "Dublin"
}
] |
[
{
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3
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{
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{
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{
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13
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14
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{
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},
{
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"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
15,751
|
superstore
|
bird:train.json:2368
|
Name 10 products that were shipped first class from the East region.
|
SELECT T2.`Product Name` FROM east_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T1.`Ship Mode` = 'First Class' AND T2.Region = 'East' LIMIT 10
|
[
"Name",
"10",
"products",
"that",
"were",
"shipped",
"first",
"class",
"from",
"the",
"East",
"region",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "east_superstore"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 5,
"type": "value",
"value": "First Class"
},
{
"id": 3,
"type": "column",
"value": "Product ID"
},
{
"id": 4,
"type": "column",
"value": "Ship Mode"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 6,
"type": "column",
"value": "region"
},
{
"id": 7,
"type": "value",
"value": "East"
}
] |
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{
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2
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{
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5
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6,
7
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10
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"token_idxs": []
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"token_idxs": []
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,752
|
legislator
|
bird:train.json:4780
|
Which historical legislators are members of the National Greenbacker party? Write their first and last names.
|
SELECT T2.first_name, T2.last_name FROM `historical-terms` AS T1 INNER JOIN historical AS T2 ON T2.bioguide_id = T1.bioguide WHERE T1.party = 'National Greenbacker'
|
[
"Which",
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"are",
"members",
"of",
"the",
"National",
"Greenbacker",
"party",
"?",
"Write",
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"first",
"and",
"last",
"names",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "National Greenbacker"
},
{
"id": 2,
"type": "table",
"value": "historical-terms"
},
{
"id": 6,
"type": "column",
"value": "bioguide_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "historical"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 7,
"type": "column",
"value": "bioguide"
},
{
"id": 4,
"type": "column",
"value": "party"
}
] |
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,753
|
college_2
|
spider:train_spider.json:1361
|
Give the name of the lowest earning instructor in the Statistics department.
|
SELECT name FROM instructor WHERE dept_name = 'Statistics' ORDER BY salary LIMIT 1
|
[
"Give",
"the",
"name",
"of",
"the",
"lowest",
"earning",
"instructor",
"in",
"the",
"Statistics",
"department",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "instructor"
},
{
"id": 3,
"type": "value",
"value": "Statistics"
},
{
"id": 2,
"type": "column",
"value": "dept_name"
},
{
"id": 4,
"type": "column",
"value": "salary"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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11
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{
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10
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{
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{
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,754
|
country_language
|
bird:test.json:1372
|
List names of countries in descending order of education_score.
|
SELECT name FROM countries ORDER BY education_score DESC
|
[
"List",
"names",
"of",
"countries",
"in",
"descending",
"order",
"of",
"education_score",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "education_score"
},
{
"id": 0,
"type": "table",
"value": "countries"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 6,
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 10,
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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",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,755
|
chicago_crime
|
bird:train.json:8716
|
Who is the commanding officer in the district with the highest number of reported crimes where no arrest has been made?
|
SELECT T2.commander FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T1.arrest = 'FALSE' GROUP BY T2.commander ORDER BY COUNT(T1.report_no) DESC LIMIT 1
|
[
"Who",
"is",
"the",
"commanding",
"officer",
"in",
"the",
"district",
"with",
"the",
"highest",
"number",
"of",
"reported",
"crimes",
"where",
"no",
"arrest",
"has",
"been",
"made",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "district_no"
},
{
"id": 0,
"type": "column",
"value": "commander"
},
{
"id": 6,
"type": "column",
"value": "report_no"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 3,
"type": "column",
"value": "arrest"
},
{
"id": 1,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "value",
"value": "FALSE"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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7
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},
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},
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,756
|
thrombosis_prediction
|
bird:dev.json:1219
|
For all patients with normal uric acid (UA), what is the average UA index based on their latest laboratory examination result?
|
SELECT AVG(T2.UA) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE (T2.UA < 6.5 AND T1.SEX = 'F') OR (T2.UA < 8.0 AND T1.SEX = 'M') AND T2.Date = ( SELECT MAX(Date) FROM Laboratory )
|
[
"For",
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"patients",
"with",
"normal",
"uric",
"acid",
"(",
"UA",
")",
",",
"what",
"is",
"the",
"average",
"UA",
"index",
"based",
"on",
"their",
"latest",
"laboratory",
"examination",
"result",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 9,
"type": "column",
"value": "date"
},
{
"id": 4,
"type": "value",
"value": "6.5"
},
{
"id": 5,
"type": "column",
"value": "sex"
},
{
"id": 7,
"type": "value",
"value": "8.0"
},
{
"id": 2,
"type": "column",
"value": "ua"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "F"
},
{
"id": 8,
"type": "value",
"value": "M"
}
] |
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2
]
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},
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"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
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"entity_id": 17,
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},
{
"entity_id": 18,
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},
{
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] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O"
] |
15,757
|
customers_and_orders
|
bird:test.json:263
|
Show all product type codes and the average price for each type.
|
SELECT product_type_code , avg(product_price) FROM Products GROUP BY product_type_code
|
[
"Show",
"all",
"product",
"type",
"codes",
"and",
"the",
"average",
"price",
"for",
"each",
"type",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "product_type_code"
},
{
"id": 2,
"type": "column",
"value": "product_price"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
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2
]
},
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]
},
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},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
{
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},
{
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},
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},
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"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",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,758
|
books
|
bird:train.json:5986
|
How many orders were delivered in December 2019?
|
SELECT COUNT(*) FROM order_status AS T1 INNER JOIN order_history AS T2 ON T1.status_id = T2.status_id WHERE T1.status_value = 'Delivered' AND STRFTIME('%Y', T2.status_date) = '2019'
|
[
"How",
"many",
"orders",
"were",
"delivered",
"in",
"December",
"2019",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "order_history"
},
{
"id": 0,
"type": "table",
"value": "order_status"
},
{
"id": 3,
"type": "column",
"value": "status_value"
},
{
"id": 7,
"type": "column",
"value": "status_date"
},
{
"id": 2,
"type": "column",
"value": "status_id"
},
{
"id": 4,
"type": "value",
"value": "Delivered"
},
{
"id": 5,
"type": "value",
"value": "2019"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
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{
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},
{
"entity_id": 3,
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},
{
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4
]
},
{
"entity_id": 5,
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7
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
15,759
|
cre_Theme_park
|
spider:train_spider.json:5959
|
What are the names of the tourist attractions that have parking or shopping as their feature details?
|
SELECT T1.Name FROM Tourist_Attractions AS T1 JOIN Tourist_Attraction_Features AS T2 ON T1.tourist_attraction_id = T2.tourist_attraction_id JOIN Features AS T3 ON T2.Feature_ID = T3.Feature_ID WHERE T3.feature_Details = 'park' UNION SELECT T1.Name FROM Tourist_Attractions AS T1 JOIN Tourist_Attraction_Features AS T2 ON T1.tourist_attraction_id = T2.tourist_attraction_id JOIN Features AS T3 ON T2.Feature_ID = T3.Feature_ID WHERE T3.feature_Details = 'shopping'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"tourist",
"attractions",
"that",
"have",
"parking",
"or",
"shopping",
"as",
"their",
"feature",
"details",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "tourist_attraction_features"
},
{
"id": 8,
"type": "column",
"value": "tourist_attraction_id"
},
{
"id": 5,
"type": "table",
"value": "tourist_attractions"
},
{
"id": 2,
"type": "column",
"value": "feature_details"
},
{
"id": 7,
"type": "column",
"value": "feature_id"
},
{
"id": 1,
"type": "table",
"value": "features"
},
{
"id": 4,
"type": "value",
"value": "shopping"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "park"
}
] |
[
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"token_idxs": [
3
]
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16
]
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"entity_id": 3,
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]
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{
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]
},
{
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7
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{
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},
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"token_idxs": []
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"token_idxs": []
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,760
|
art_1
|
bird:test.json:1228
|
How many paintings did the artist with the longest life make ?
|
select count(*) from artists as t1 join paintings as t2 on t1.artistid = t2.painterid group by t2.painterid order by t1.deathyear - t1.birthyear desc limit 1
|
[
"How",
"many",
"paintings",
"did",
"the",
"artist",
"with",
"the",
"longest",
"life",
"make",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "painterid"
},
{
"id": 2,
"type": "table",
"value": "paintings"
},
{
"id": 4,
"type": "column",
"value": "deathyear"
},
{
"id": 5,
"type": "column",
"value": "birthyear"
},
{
"id": 3,
"type": "column",
"value": "artistid"
},
{
"id": 1,
"type": "table",
"value": "artists"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
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"token_idxs": [
2
]
},
{
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},
{
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,761
|
language_corpus
|
bird:train.json:5801
|
Which word has the most appearances in the Wikipedia page revision ID No. 28278070? Give the word ID.
|
SELECT pid FROM pages_words WHERE pid = ( SELECT pid FROM pages WHERE revision = 28278070 ) ORDER BY occurrences DESC LIMIT 1
|
[
"Which",
"word",
"has",
"the",
"most",
"appearances",
"in",
"the",
"Wikipedia",
"page",
"revision",
"ID",
"No",
".",
"28278070",
"?",
"Give",
"the",
"word",
"ID",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pages_words"
},
{
"id": 2,
"type": "column",
"value": "occurrences"
},
{
"id": 4,
"type": "column",
"value": "revision"
},
{
"id": 5,
"type": "value",
"value": "28278070"
},
{
"id": 3,
"type": "table",
"value": "pages"
},
{
"id": 1,
"type": "column",
"value": "pid"
}
] |
[
{
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"token_idxs": []
},
{
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19
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10
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14
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{
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"token_idxs": []
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"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,762
|
works_cycles
|
bird:train.json:7206
|
How much is the total bonus received by sales person and what is the percentage of it against the projected yearly sales quota in 2013?
|
SELECT SUM(T1.Bonus) , CAST(SUM(T1.Bonus) AS REAL) * 100 / SUM(T1.SalesQuota) FROM SalesPerson AS T1 INNER JOIN SalesPersonQuotaHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE STRFTIME('%Y', T2.QuotaDate) = '2013'
|
[
"How",
"much",
"is",
"the",
"total",
"bonus",
"received",
"by",
"sales",
"person",
"and",
"what",
"is",
"the",
"percentage",
"of",
"it",
"against",
"the",
"projected",
"yearly",
"sales",
"quota",
"in",
"2013",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "salespersonquotahistory"
},
{
"id": 4,
"type": "column",
"value": "businessentityid"
},
{
"id": 0,
"type": "table",
"value": "salesperson"
},
{
"id": 8,
"type": "column",
"value": "salesquota"
},
{
"id": 6,
"type": "column",
"value": "quotadate"
},
{
"id": 3,
"type": "column",
"value": "bonus"
},
{
"id": 2,
"type": "value",
"value": "2013"
},
{
"id": 7,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "%Y"
}
] |
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9
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{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,763
|
works_cycles
|
bird:train.json:7343
|
What is the difference between the actual manufacturing cost of product number 818 and the estimated manufacturing cost?
|
SELECT PlannedCost - ActualCost FROM WorkOrderRouting WHERE ProductID = 818
|
[
"What",
"is",
"the",
"difference",
"between",
"the",
"actual",
"manufacturing",
"cost",
"of",
"product",
"number",
"818",
"and",
"the",
"estimated",
"manufacturing",
"cost",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "workorderrouting"
},
{
"id": 3,
"type": "column",
"value": "plannedcost"
},
{
"id": 4,
"type": "column",
"value": "actualcost"
},
{
"id": 1,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "value",
"value": "818"
}
] |
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{
"entity_id": 0,
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{
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10
]
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{
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12
]
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6
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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",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,764
|
customers_and_invoices
|
spider:train_spider.json:1571
|
Show first name and id for all customers with at least 2 accounts.
|
SELECT T2.customer_first_name , T1.customer_id FROM Accounts AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 2
|
[
"Show",
"first",
"name",
"and",
"i",
"d",
"for",
"all",
"customers",
"with",
"at",
"least",
"2",
"accounts",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customer_first_name"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "accounts"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0,
1,
2
]
},
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"entity_id": 2,
"token_idxs": [
13
]
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8
]
},
{
"entity_id": 4,
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12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
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"entity_id": 8,
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"entity_id": 9,
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"entity_id": 10,
"token_idxs": []
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,765
|
image_and_language
|
bird:train.json:7560
|
Indicating the bounding box of "kitchen" in image id 250.
|
SELECT T1.X, T1.Y, T1.W, T1.H FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 250 AND T2.OBJ_CLASS = 'kitchen'
|
[
"Indicating",
"the",
"bounding",
"box",
"of",
"\"",
"kitchen",
"\"",
"in",
"image",
"i",
"d",
"250",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "obj_class_id"
},
{
"id": 5,
"type": "table",
"value": "obj_classes"
},
{
"id": 9,
"type": "column",
"value": "obj_class"
},
{
"id": 4,
"type": "table",
"value": "img_obj"
},
{
"id": 10,
"type": "value",
"value": "kitchen"
},
{
"id": 7,
"type": "column",
"value": "img_id"
},
{
"id": 8,
"type": "value",
"value": "250"
},
{
"id": 0,
"type": "column",
"value": "x"
},
{
"id": 1,
"type": "column",
"value": "y"
},
{
"id": 2,
"type": "column",
"value": "w"
},
{
"id": 3,
"type": "column",
"value": "h"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
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{
"entity_id": 1,
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},
{
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9,
10,
11
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12
]
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"token_idxs": []
},
{
"entity_id": 10,
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6
]
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"entity_id": 12,
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},
{
"entity_id": 13,
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
15,766
|
university
|
bird:train.json:8096
|
How many students were there in University of Michigan in 2011?
|
SELECT COUNT(*) FROM university AS T1 INNER JOIN university_year AS T2 ON T1.id = T2.university_id WHERE T1.university_name = 'University of Michigan' AND T2.year = 2011
|
[
"How",
"many",
"students",
"were",
"there",
"in",
"University",
"of",
"Michigan",
"in",
"2011",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "University of Michigan"
},
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 4,
"type": "column",
"value": "university_name"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 6,
"type": "column",
"value": "year"
},
{
"id": 7,
"type": "value",
"value": "2011"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
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6
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8
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{
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},
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},
{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
15,767
|
social_media
|
bird:train.json:784
|
Among all the tweets that are reshared, how many of them are posted by a user in Buenos Aires?
|
SELECT COUNT(T1.TweetID) FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T2.City = 'Buenos Aires' AND T1.IsReshare = 'TRUE'
|
[
"Among",
"all",
"the",
"tweets",
"that",
"are",
"reshared",
",",
"how",
"many",
"of",
"them",
"are",
"posted",
"by",
"a",
"user",
"in",
"Buenos",
"Aires",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Buenos Aires"
},
{
"id": 3,
"type": "column",
"value": "locationid"
},
{
"id": 6,
"type": "column",
"value": "isreshare"
},
{
"id": 1,
"type": "table",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "twitter"
},
{
"id": 2,
"type": "column",
"value": "tweetid"
},
{
"id": 4,
"type": "column",
"value": "city"
},
{
"id": 7,
"type": "value",
"value": "TRUE"
}
] |
[
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"entity_id": 0,
"token_idxs": []
},
{
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},
{
"entity_id": 2,
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3
]
},
{
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},
{
"entity_id": 4,
"token_idxs": []
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{
"entity_id": 5,
"token_idxs": [
18,
19
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},
{
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6
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{
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{
"entity_id": 16,
"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,768
|
game_injury
|
spider:train_spider.json:1287
|
How many distinct kinds of injuries happened after season 2010?
|
SELECT count(DISTINCT T1.injury) FROM injury_accident AS T1 JOIN game AS T2 ON T1.game_id = T2.id WHERE T2.season > 2010
|
[
"How",
"many",
"distinct",
"kinds",
"of",
"injuries",
"happened",
"after",
"season",
"2010",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "injury_accident"
},
{
"id": 5,
"type": "column",
"value": "game_id"
},
{
"id": 2,
"type": "column",
"value": "season"
},
{
"id": 4,
"type": "column",
"value": "injury"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 3,
"type": "value",
"value": "2010"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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},
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
15,769
|
synthea
|
bird:train.json:1409
|
What is the total number of Asian patients who are allergic to peanuts?
|
SELECT COUNT(T2.patient) FROM allergies AS T1 INNER JOIN patients AS T2 ON T1.PATIENT = T2.patient WHERE T1.DESCRIPTION = 'Allergy to peanuts' AND T2.race = 'asian'
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"Asian",
"patients",
"who",
"are",
"allergic",
"to",
"peanuts",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Allergy to peanuts"
},
{
"id": 3,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "allergies"
},
{
"id": 1,
"type": "table",
"value": "patients"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 6,
"type": "value",
"value": "asian"
},
{
"id": 5,
"type": "column",
"value": "race"
}
] |
[
{
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10
]
},
{
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{
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7
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11,
12
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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": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O"
] |
15,770
|
thrombosis_prediction
|
bird:dev.json:1301
|
Please list the IDs of the patients with no thrombosis and an abnormal level of creatinine phosphokinase.
|
SELECT DISTINCT T1.ID FROM Laboratory AS T1 INNER JOIN Examination AS T2 ON T1.ID = T2.ID WHERE T2.Thrombosis = 0 AND T1.CPK < 250
|
[
"Please",
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"the",
"IDs",
"of",
"the",
"patients",
"with",
"no",
"thrombosis",
"and",
"an",
"abnormal",
"level",
"of",
"creatinine",
"phosphokinase",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "examination"
},
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 3,
"type": "column",
"value": "thrombosis"
},
{
"id": 5,
"type": "column",
"value": "cpk"
},
{
"id": 6,
"type": "value",
"value": "250"
},
{
"id": 0,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
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},
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},
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,771
|
products_gen_characteristics
|
spider:train_spider.json:5576
|
Count the products that have the color description "white" or have the characteristic name "hot".
|
SELECT count(*) FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id JOIN ref_colors AS t4 ON t1.color_code = t4.color_code WHERE t4.color_description = "white" OR t3.characteristic_name = "hot"
|
[
"Count",
"the",
"products",
"that",
"have",
"the",
"color",
"description",
"\"",
"white",
"\"",
"or",
"have",
"the",
"characteristic",
"name",
"\"",
"hot",
"\"",
"."
] |
[
{
"id": 8,
"type": "table",
"value": "product_characteristics"
},
{
"id": 5,
"type": "column",
"value": "characteristic_name"
},
{
"id": 3,
"type": "column",
"value": "color_description"
},
{
"id": 9,
"type": "column",
"value": "characteristic_id"
},
{
"id": 1,
"type": "table",
"value": "characteristics"
},
{
"id": 0,
"type": "table",
"value": "ref_colors"
},
{
"id": 2,
"type": "column",
"value": "color_code"
},
{
"id": 10,
"type": "column",
"value": "product_id"
},
{
"id": 7,
"type": "table",
"value": "products"
},
{
"id": 4,
"type": "column",
"value": "white"
},
{
"id": 6,
"type": "column",
"value": "hot"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
15,772
|
shakespeare
|
bird:train.json:3009
|
When did Shakespeare create his work that has 154 scenes?
|
SELECT T1.Date, T1.id FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id WHERE T2.Scene = 154
|
[
"When",
"did",
"Shakespeare",
"create",
"his",
"work",
"that",
"has",
"154",
"scenes",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "chapters"
},
{
"id": 6,
"type": "column",
"value": "work_id"
},
{
"id": 2,
"type": "table",
"value": "works"
},
{
"id": 4,
"type": "column",
"value": "scene"
},
{
"id": 0,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "154"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,773
|
e_commerce
|
bird:test.json:108
|
List the order date of the orders who are placed by customers with at least 2 payment methods.
|
SELECT date_order_placed FROM Orders WHERE customer_id IN ( SELECT T1.customer_id FROM Customers AS T1 JOIN Customer_Payment_Methods AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id HAVING count(*) >= 2 )
|
[
"List",
"the",
"order",
"date",
"of",
"the",
"orders",
"who",
"are",
"placed",
"by",
"customers",
"with",
"at",
"least",
"2",
"payment",
"methods",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "customer_payment_methods"
},
{
"id": 1,
"type": "column",
"value": "date_order_placed"
},
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
16,
17
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O"
] |
15,774
|
bike_1
|
spider:train_spider.json:131
|
Return the unique name for stations that have ever had 7 bikes available.
|
SELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7
|
[
"Return",
"the",
"unique",
"name",
"for",
"stations",
"that",
"have",
"ever",
"had",
"7",
"bikes",
"available",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "bikes_available"
},
{
"id": 6,
"type": "column",
"value": "station_id"
},
{
"id": 1,
"type": "table",
"value": "station"
},
{
"id": 2,
"type": "table",
"value": "status"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,775
|
public_review_platform
|
bird:train.json:4014
|
Find the Yelp user with the average 5-star rating of all reviews who has been yelping the longest.
|
SELECT user_id FROM Users WHERE user_average_stars = 5 ORDER BY user_yelping_since_year ASC LIMIT 1
|
[
"Find",
"the",
"Yelp",
"user",
"with",
"the",
"average",
"5",
"-",
"star",
"rating",
"of",
"all",
"reviews",
"who",
"has",
"been",
"yelping",
"the",
"longest",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "user_yelping_since_year"
},
{
"id": 2,
"type": "column",
"value": "user_average_stars"
},
{
"id": 1,
"type": "column",
"value": "user_id"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 3,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,776
|
works_cycles
|
bird:train.json:7455
|
How many days did it take to end the work order "425"?
|
SELECT 365 * (STRFTIME('%Y', ActualEndDate) - STRFTIME('%Y', ActualStartDate)) + 30 * (STRFTIME('%m', ActualEndDate) - STRFTIME('%m', ActualStartDate)) + STRFTIME('%d', ActualEndDate) - STRFTIME('%d', ActualStartDate) FROM WorkOrderRouting WHERE WorkOrderID = 425
|
[
"How",
"many",
"days",
"did",
"it",
"take",
"to",
"end",
"the",
"work",
"order",
"\"",
"425",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "workorderrouting"
},
{
"id": 4,
"type": "column",
"value": "actualstartdate"
},
{
"id": 5,
"type": "column",
"value": "actualenddate"
},
{
"id": 1,
"type": "column",
"value": "workorderid"
},
{
"id": 2,
"type": "value",
"value": "425"
},
{
"id": 6,
"type": "value",
"value": "365"
},
{
"id": 3,
"type": "value",
"value": "%d"
},
{
"id": 7,
"type": "value",
"value": "30"
},
{
"id": 8,
"type": "value",
"value": "%Y"
},
{
"id": 9,
"type": "value",
"value": "%m"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
15,777
|
cinema
|
spider:train_spider.json:1951
|
What are the title and maximum price of each film?
|
SELECT T2.title , max(T1.price) FROM schedule AS T1 JOIN film AS T2 ON T1.film_id = T2.film_id GROUP BY T1.film_id
|
[
"What",
"are",
"the",
"title",
"and",
"maximum",
"price",
"of",
"each",
"film",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "schedule"
},
{
"id": 0,
"type": "column",
"value": "film_id"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
15,778
|
public_review_platform
|
bird:train.json:3863
|
When does Yelp_Business no.1 open on Tuesdays?
|
SELECT T1.opening_time FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id WHERE T2.day_of_week LIKE 'Tuesday' AND T1.business_id = 1
|
[
"When",
"does",
"Yelp_Business",
"no.1",
"open",
"on",
"Tuesdays",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "business_hours"
},
{
"id": 0,
"type": "column",
"value": "opening_time"
},
{
"id": 4,
"type": "column",
"value": "day_of_week"
},
{
"id": 6,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "value",
"value": "Tuesday"
},
{
"id": 3,
"type": "column",
"value": "day_id"
},
{
"id": 2,
"type": "table",
"value": "days"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
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",
"O",
"O",
"B-TABLE",
"O"
] |
15,779
|
pilot_1
|
bird:test.json:1155
|
Find the number of planes for each type.
|
SELECT count(*) , plane_name FROM pilotskills GROUP BY plane_name
|
[
"Find",
"the",
"number",
"of",
"planes",
"for",
"each",
"type",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "plane_name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,780
|
soccer_2016
|
bird:train.json:1895
|
Of the wickets taken in the third overs, how many are without the involvement of fielders?
|
SELECT SUM(CASE WHEN Fielders = '' THEN 1 ELSE 0 END) FROM Wicket_Taken WHERE Over_Id = 3
|
[
"Of",
"the",
"wickets",
"taken",
"in",
"the",
"third",
"overs",
",",
"how",
"many",
"are",
"without",
"the",
"involvement",
"of",
"fielders",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "wicket_taken"
},
{
"id": 5,
"type": "column",
"value": "fielders"
},
{
"id": 1,
"type": "column",
"value": "over_id"
},
{
"id": 2,
"type": "value",
"value": "3"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"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": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,781
|
sales
|
bird:train.json:5442
|
Among the sales ID ranges from 1 to 200, what is the percentage of the products with a price ranging from 200 to 300?
|
SELECT CAST(SUM(IIF(T2.Price BETWEEN 200 AND 300, 1, 0)) AS REAL) * 100 / COUNT(T2.Price) FROM Sales AS T1 INNER JOIN Products AS T2 ON T1.ProductID = T2.ProductID WHERE T1.SalesID BETWEEN 1 AND 200
|
[
"Among",
"the",
"sales",
"ID",
"ranges",
"from",
"1",
"to",
"200",
",",
"what",
"is",
"the",
"percentage",
"of",
"the",
"products",
"with",
"a",
"price",
"ranging",
"from",
"200",
"to",
"300",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 2,
"type": "column",
"value": "salesid"
},
{
"id": 0,
"type": "table",
"value": "sales"
},
{
"id": 7,
"type": "column",
"value": "price"
},
{
"id": 4,
"type": "value",
"value": "200"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 9,
"type": "value",
"value": "300"
},
{
"id": 3,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
19
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,782
|
codebase_comments
|
bird:train.json:569
|
How many followers do the most followed repository on Github have? Give the github address of the repository.
|
SELECT Forks, Url FROM Repo WHERE Forks = ( SELECT MAX(Forks) FROM Repo )
|
[
"How",
"many",
"followers",
"do",
"the",
"most",
"followed",
"repository",
"on",
"Github",
"have",
"?",
"Give",
"the",
"github",
"address",
"of",
"the",
"repository",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "forks"
},
{
"id": 0,
"type": "table",
"value": "repo"
},
{
"id": 2,
"type": "column",
"value": "url"
}
] |
[
{
"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": []
},
{
"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",
"O",
"O",
"O",
"O"
] |
15,783
|
soccer_2016
|
bird:train.json:1816
|
State the name of the city with the most venues.
|
SELECT T1.City_Name FROM City AS T1 INNER JOIN Venue AS T2 ON T1.City_Id = T2.City_Id GROUP BY T1.City_Id ORDER BY COUNT(T2.Venue_Id) DESC LIMIT 1
|
[
"State",
"the",
"name",
"of",
"the",
"city",
"with",
"the",
"most",
"venues",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "city_name"
},
{
"id": 4,
"type": "column",
"value": "venue_id"
},
{
"id": 0,
"type": "column",
"value": "city_id"
},
{
"id": 3,
"type": "table",
"value": "venue"
},
{
"id": 2,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,784
|
movie_2
|
bird:test.json:1816
|
How many different movies are playing?
|
SELECT count(DISTINCT T1.code) FROM movies AS T1 JOIN movietheaters AS T2 ON T1.code = T2.movie
|
[
"How",
"many",
"different",
"movies",
"are",
"playing",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "movietheaters"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 3,
"type": "column",
"value": "movie"
},
{
"id": 2,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
15,785
|
warehouse_1
|
bird:test.json:1749
|
Select the codes of all the boxes located in Chicago.
|
SELECT T1.code FROM boxes AS T1 JOIN Warehouses AS T2 ON T1.warehouse = T2.code WHERE T2.location = 'Chicago'
|
[
"Select",
"the",
"codes",
"of",
"all",
"the",
"boxes",
"located",
"in",
"Chicago",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "warehouses"
},
{
"id": 5,
"type": "column",
"value": "warehouse"
},
{
"id": 3,
"type": "column",
"value": "location"
},
{
"id": 4,
"type": "value",
"value": "Chicago"
},
{
"id": 1,
"type": "table",
"value": "boxes"
},
{
"id": 0,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
15,786
|
advertising_agencies
|
bird:test.json:2128
|
How many meetings are there for each meeting type?
|
SELECT meeting_type , count(*) FROM Meetings GROUP BY meeting_type
|
[
"How",
"many",
"meetings",
"are",
"there",
"for",
"each",
"meeting",
"type",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "meeting_type"
},
{
"id": 0,
"type": "table",
"value": "meetings"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,787
|
books
|
bird:train.json:6102
|
Provide the email of the customers that purchased books with a price range of 3 to 5 dollars.
|
SELECT DISTINCT T3.email 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 T1.price BETWEEN 3 AND 5
|
[
"Provide",
"the",
"email",
"of",
"the",
"customers",
"that",
"purchased",
"books",
"with",
"a",
"price",
"range",
"of",
"3",
"to",
"5",
"dollars",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "table",
"value": "order_line"
},
{
"id": 6,
"type": "table",
"value": "cust_order"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 8,
"type": "column",
"value": "order_id"
},
{
"id": 0,
"type": "column",
"value": "email"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "value",
"value": "3"
},
{
"id": 4,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"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-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O"
] |
15,788
|
shakespeare
|
bird:train.json:2975
|
What is the description for the character mentioned in paragraph No.640171?
|
SELECT T1.Description FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T2.id = '640171'
|
[
"What",
"is",
"the",
"description",
"for",
"the",
"character",
"mentioned",
"in",
"paragraph",
"No.640171",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "character_id"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 2,
"type": "table",
"value": "paragraphs"
},
{
"id": 4,
"type": "value",
"value": "640171"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
15,789
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6402
|
What are the type come, name, and description of the document that has either the name 'Noel CV' or 'King Book'?
|
SELECT document_type_code , document_name , document_description FROM Documents WHERE document_name = 'Noel CV' OR document_name = 'King Book'
|
[
"What",
"are",
"the",
"type",
"come",
",",
"name",
",",
"and",
"description",
"of",
"the",
"document",
"that",
"has",
"either",
"the",
"name",
"'",
"Noel",
"CV",
"'",
"or",
"'",
"King",
"Book",
"'",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "document_description"
},
{
"id": 1,
"type": "column",
"value": "document_type_code"
},
{
"id": 2,
"type": "column",
"value": "document_name"
},
{
"id": 0,
"type": "table",
"value": "documents"
},
{
"id": 5,
"type": "value",
"value": "King Book"
},
{
"id": 4,
"type": "value",
"value": "Noel CV"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
19,
20
]
},
{
"entity_id": 5,
"token_idxs": [
24,
25
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
15,790
|
european_football_2
|
bird:dev.json:1064
|
List out of players whose preferred foot is left.
|
SELECT DISTINCT t1.id, t1.player_name FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t2.preferred_foot = 'left'
|
[
"List",
"out",
"of",
"players",
"whose",
"preferred",
"foot",
"is",
"left",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "player_attributes"
},
{
"id": 4,
"type": "column",
"value": "preferred_foot"
},
{
"id": 6,
"type": "column",
"value": "player_api_id"
},
{
"id": 1,
"type": "column",
"value": "player_name"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 5,
"type": "value",
"value": "left"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,791
|
book_publishing_company
|
bird:train.json:190
|
Name the title with the highest price published by 'Binnet & Hardley'.
|
SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'Binnet & Hardley' ORDER BY T1.price DESC LIMIT 1
|
[
"Name",
"the",
"title",
"with",
"the",
"highest",
"price",
"published",
"by",
"'",
"Binnet",
"&",
"Hardley",
"'",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Binnet & Hardley"
},
{
"id": 2,
"type": "table",
"value": "publishers"
},
{
"id": 3,
"type": "column",
"value": "pub_name"
},
{
"id": 1,
"type": "table",
"value": "titles"
},
{
"id": 6,
"type": "column",
"value": "pub_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "column",
"value": "price"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
0
]
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 5,
"token_idxs": [
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": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
15,792
|
trains
|
bird:train.json:699
|
Among the trains that run in the east direction, how many of them have more than 2 long cars?
|
SELECT SUM(CASE WHEN T2.longCarsNum > 2 THEN 1 ELSE 0 END)as count FROM trains AS T1 INNER JOIN ( SELECT train_id, COUNT(id) AS longCarsNum FROM cars WHERE len = 'long' GROUP BY train_id ) AS T2 ON T1.id = T2.train_id WHERE T1.direction = 'west'
|
[
"Among",
"the",
"trains",
"that",
"run",
"in",
"the",
"east",
"direction",
",",
"how",
"many",
"of",
"them",
"have",
"more",
"than",
"2",
"long",
"cars",
"?"
] |
[
{
"id": 10,
"type": "column",
"value": "longcarsnum"
},
{
"id": 1,
"type": "column",
"value": "direction"
},
{
"id": 4,
"type": "column",
"value": "train_id"
},
{
"id": 0,
"type": "table",
"value": "trains"
},
{
"id": 2,
"type": "value",
"value": "west"
},
{
"id": 6,
"type": "table",
"value": "cars"
},
{
"id": 9,
"type": "value",
"value": "long"
},
{
"id": 8,
"type": "column",
"value": "len"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 11,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
19
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
18
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
17
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-TABLE",
"O"
] |
15,793
|
planet_1
|
bird:test.json:1922
|
What are the names of all employees with clearance on Omega III?
|
SELECT T2.Name FROM Has_Clearance AS T1 JOIN Employee AS T2 ON T1.Employee = T2.EmployeeID JOIN Planet AS T3 ON T1.Planet = T3.PlanetID WHERE T3.Name = "Omega III";
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"employees",
"with",
"clearance",
"on",
"Omega",
"III",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "has_clearance"
},
{
"id": 8,
"type": "column",
"value": "employeeid"
},
{
"id": 2,
"type": "column",
"value": "Omega III"
},
{
"id": 4,
"type": "table",
"value": "employee"
},
{
"id": 6,
"type": "column",
"value": "planetid"
},
{
"id": 7,
"type": "column",
"value": "employee"
},
{
"id": 1,
"type": "table",
"value": "planet"
},
{
"id": 5,
"type": "column",
"value": "planet"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"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": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,794
|
game_1
|
spider:train_spider.json:6028
|
What are the ids of all male students who do not play football?
|
SELECT StuID FROM Student WHERE sex = 'M' EXCEPT SELECT StuID FROM Sportsinfo WHERE sportname = "Football"
|
[
"What",
"are",
"the",
"ids",
"of",
"all",
"male",
"students",
"who",
"do",
"not",
"play",
"football",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "sportsinfo"
},
{
"id": 5,
"type": "column",
"value": "sportname"
},
{
"id": 6,
"type": "column",
"value": "Football"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 4,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,796
|
retail_complains
|
bird:train.json:301
|
How many clients under the age of 35 gave Eagle National Mortgage 1 star?
|
SELECT COUNT(T2.age) FROM reviews AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id WHERE T1.Product = 'Eagle National Mortgage' AND T1.Stars = 1 AND T2.age < 35
|
[
"How",
"many",
"clients",
"under",
"the",
"age",
"of",
"35",
"gave",
"Eagle",
"National",
"Mortgage",
"1",
"star",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Eagle National Mortgage"
},
{
"id": 3,
"type": "column",
"value": "district_id"
},
{
"id": 0,
"type": "table",
"value": "reviews"
},
{
"id": 4,
"type": "column",
"value": "product"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 8,
"type": "value",
"value": "35"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,797
|
video_games
|
bird:train.json:3420
|
How many Sports games did Nintendo publish?
|
SELECT COUNT(T3.id) FROM publisher AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.publisher_id INNER JOIN game AS T3 ON T2.game_id = T3.id INNER JOIN genre AS T4 ON T3.genre_id = T4.id WHERE T4.genre_name = 'Sports' AND T1.publisher_name = 'Nintendo'
|
[
"How",
"many",
"Sports",
"games",
"did",
"Nintendo",
"publish",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "publisher_name"
},
{
"id": 9,
"type": "table",
"value": "game_publisher"
},
{
"id": 11,
"type": "column",
"value": "publisher_id"
},
{
"id": 4,
"type": "column",
"value": "genre_name"
},
{
"id": 8,
"type": "table",
"value": "publisher"
},
{
"id": 3,
"type": "column",
"value": "genre_id"
},
{
"id": 7,
"type": "value",
"value": "Nintendo"
},
{
"id": 10,
"type": "column",
"value": "game_id"
},
{
"id": 5,
"type": "value",
"value": "Sports"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 2,
"type": "table",
"value": "game"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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": [
5
]
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"B-TABLE",
"O"
] |
15,798
|
sing_contest
|
bird:test.json:749
|
What are the ids and names of the participants who have performed at least two songs?
|
SELECT T1.id , T1.Name FROM participants AS T1 JOIN performance_score AS T2 ON T2.participant_id = T1.id GROUP BY T1.id HAVING count(*) >= 2
|
[
"What",
"are",
"the",
"ids",
"and",
"names",
"of",
"the",
"participants",
"who",
"have",
"performed",
"at",
"least",
"two",
"songs",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "performance_score"
},
{
"id": 5,
"type": "column",
"value": "participant_id"
},
{
"id": 2,
"type": "table",
"value": "participants"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
15,799
|
talkingdata
|
bird:train.json:1060
|
How many users used Vivo Xplay3S model?
|
SELECT COUNT(device_id) FROM phone_brand_device_model2 WHERE device_model = 'Xplay3S' AND phone_brand = 'vivo'
|
[
"How",
"many",
"users",
"used",
"Vivo",
"Xplay3S",
"model",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 2,
"type": "column",
"value": "device_model"
},
{
"id": 4,
"type": "column",
"value": "phone_brand"
},
{
"id": 1,
"type": "column",
"value": "device_id"
},
{
"id": 3,
"type": "value",
"value": "Xplay3S"
},
{
"id": 5,
"type": "value",
"value": "vivo"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,801
|
student_club
|
bird:dev.json:1329
|
What county did Sherri Ramsey grew up?
|
SELECT T2.county FROM member AS T1 INNER JOIN zip_code AS T2 ON T1.zip = T2.zip_code WHERE T1.first_name = 'Sherri' AND T1.last_name = 'Ramsey'
|
[
"What",
"county",
"did",
"Sherri",
"Ramsey",
"grew",
"up",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "zip_code"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "column",
"value": "county"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 6,
"type": "value",
"value": "Sherri"
},
{
"id": 8,
"type": "value",
"value": "Ramsey"
},
{
"id": 3,
"type": "column",
"value": "zip"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
4
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O"
] |
15,803
|
scientist_1
|
spider:train_spider.json:6491
|
Find the name of the scientist who worked on both a project named 'Matter of Time' and a project named 'A Puzzling Parallax'.
|
SELECT T3.name FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T2.name = 'Matter of Time' INTERSECT SELECT T3.name FROM assignedto AS T1 JOIN projects AS T2 ON T1.project = T2.code JOIN scientists AS T3 ON T1.scientist = T3.SSN WHERE T2.name = 'A Puzzling Parallax'
|
[
"Find",
"the",
"name",
"of",
"the",
"scientist",
"who",
"worked",
"on",
"both",
"a",
"project",
"named",
"'",
"Matter",
"of",
"Time",
"'",
"and",
"a",
"project",
"named",
"'",
"A",
"Puzzling",
"Parallax",
"'",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "A Puzzling Parallax"
},
{
"id": 2,
"type": "value",
"value": "Matter of Time"
},
{
"id": 1,
"type": "table",
"value": "scientists"
},
{
"id": 4,
"type": "table",
"value": "assignedto"
},
{
"id": 6,
"type": "column",
"value": "scientist"
},
{
"id": 5,
"type": "table",
"value": "projects"
},
{
"id": 8,
"type": "column",
"value": "project"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "code"
},
{
"id": 7,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
14,
15,
16
]
},
{
"entity_id": 3,
"token_idxs": [
23,
24,
25
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
20
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
15,804
|
thrombosis_prediction
|
bird:dev.json:1288
|
Please list the diagnosis of the patients whose total protein is lower than normal.
|
SELECT T1.Diagnosis FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.TP < 6.0
|
[
"Please",
"list",
"the",
"diagnosis",
"of",
"the",
"patients",
"whose",
"total",
"protein",
"is",
"lower",
"than",
"normal",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 1,
"type": "table",
"value": "patient"
},
{
"id": 4,
"type": "value",
"value": "6.0"
},
{
"id": 3,
"type": "column",
"value": "tp"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,805
|
restaurant_bills
|
bird:test.json:627
|
How many customers are associated with each nationality? List the nationality and the number of customers.
|
SELECT Nationality , COUNT(*) FROM customer GROUP BY Nationality
|
[
"How",
"many",
"customers",
"are",
"associated",
"with",
"each",
"nationality",
"?",
"List",
"the",
"nationality",
"and",
"the",
"number",
"of",
"customers",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 0,
"type": "table",
"value": "customer"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,806
|
sales_in_weather
|
bird:train.json:8208
|
What is the sea level and average speed for store number 3 and store number 4?
|
SELECT T1.sealevel, T1.avgspeed FROM weather AS T1 INNER JOIN relation AS T2 ON T1.station_nbr = T2.station_nbr WHERE T2.store_nbr = 3 OR T2.store_nbr = 4
|
[
"What",
"is",
"the",
"sea",
"level",
"and",
"average",
"speed",
"for",
"store",
"number",
"3",
"and",
"store",
"number",
"4",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "station_nbr"
},
{
"id": 5,
"type": "column",
"value": "store_nbr"
},
{
"id": 0,
"type": "column",
"value": "sealevel"
},
{
"id": 1,
"type": "column",
"value": "avgspeed"
},
{
"id": 3,
"type": "table",
"value": "relation"
},
{
"id": 2,
"type": "table",
"value": "weather"
},
{
"id": 6,
"type": "value",
"value": "3"
},
{
"id": 7,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
13,
14
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
15,807
|
hockey
|
bird:train.json:7679
|
Please list the positions of the players who were born in Canada and have won the All-Rookie award.
|
SELECT DISTINCT T1.pos FROM Master AS T1 INNER JOIN AwardsPlayers AS T2 ON T1.playerID = T2.playerID WHERE T1.birthCountry = 'Canada' AND T2.award = 'All-Rookie'
|
[
"Please",
"list",
"the",
"positions",
"of",
"the",
"players",
"who",
"were",
"born",
"in",
"Canada",
"and",
"have",
"won",
"the",
"All",
"-",
"Rookie",
"award",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "awardsplayers"
},
{
"id": 4,
"type": "column",
"value": "birthcountry"
},
{
"id": 7,
"type": "value",
"value": "All-Rookie"
},
{
"id": 3,
"type": "column",
"value": "playerid"
},
{
"id": 1,
"type": "table",
"value": "master"
},
{
"id": 5,
"type": "value",
"value": "Canada"
},
{
"id": 6,
"type": "column",
"value": "award"
},
{
"id": 0,
"type": "column",
"value": "pos"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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11
]
},
{
"entity_id": 6,
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19
]
},
{
"entity_id": 7,
"token_idxs": [
16,
17,
18
]
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
15,808
|
flight_1
|
spider:train_spider.json:350
|
What is the count of aircrafts that have a distance between 1000 and 5000?
|
SELECT count(*) FROM Aircraft WHERE distance BETWEEN 1000 AND 5000
|
[
"What",
"is",
"the",
"count",
"of",
"aircrafts",
"that",
"have",
"a",
"distance",
"between",
"1000",
"and",
"5000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 1,
"type": "column",
"value": "distance"
},
{
"id": 2,
"type": "value",
"value": "1000"
},
{
"id": 3,
"type": "value",
"value": "5000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
15,809
|
disney
|
bird:train.json:4642
|
Who is the voice actor of the hero character from the movie The Little Mermaid?
|
SELECT T2.`voice-actor` FROM characters AS T1 INNER JOIN `voice-actors` AS T2 ON T2.movie = T1.movie_title WHERE T1.movie_title = 'The Little Mermaid' AND T2.character = T1.hero
|
[
"Who",
"is",
"the",
"voice",
"actor",
"of",
"the",
"hero",
"character",
"from",
"the",
"movie",
"The",
"Little",
"Mermaid",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "The Little Mermaid"
},
{
"id": 2,
"type": "table",
"value": "voice-actors"
},
{
"id": 0,
"type": "column",
"value": "voice-actor"
},
{
"id": 4,
"type": "column",
"value": "movie_title"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 6,
"type": "column",
"value": "character"
},
{
"id": 3,
"type": "column",
"value": "movie"
},
{
"id": 7,
"type": "column",
"value": "hero"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
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12,
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]
},
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8
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7
]
},
{
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{
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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",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
15,810
|
phone_market
|
spider:train_spider.json:1984
|
Show different carriers of phones together with the number of phones with each carrier.
|
SELECT Carrier , COUNT(*) FROM phone GROUP BY Carrier
|
[
"Show",
"different",
"carriers",
"of",
"phones",
"together",
"with",
"the",
"number",
"of",
"phones",
"with",
"each",
"carrier",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "carrier"
},
{
"id": 0,
"type": "table",
"value": "phone"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,811
|
bike_share_1
|
bird:train.json:9007
|
On 8/29/2013, who took the longest to arrive in California Ave Caltrain Station from University and Emerson? Indicate the bike id.
|
SELECT bike_id FROM trip WHERE start_date LIKE '8/29/2013%' AND end_date LIKE '8/29/2013%' AND end_station_name = 'California Ave Caltrain Station' AND start_station_name = 'University and Emerson' AND duration = ( SELECT MAX(duration) FROM trip WHERE start_date LIKE '8/29/2013%' AND end_date LIKE '8/29/2013%' AND end_station_name = 'California Ave Caltrain Station' AND start_station_name = 'University and Emerson' )
|
[
"On",
"8/29/2013",
",",
"who",
"took",
"the",
"longest",
"to",
"arrive",
"in",
"California",
"Ave",
"Caltrain",
"Station",
"from",
"University",
"and",
"Emerson",
"?",
"Indicate",
"the",
"bike",
"i",
"d."
] |
[
{
"id": 6,
"type": "value",
"value": "California Ave Caltrain Station"
},
{
"id": 8,
"type": "value",
"value": "University and Emerson"
},
{
"id": 7,
"type": "column",
"value": "start_station_name"
},
{
"id": 5,
"type": "column",
"value": "end_station_name"
},
{
"id": 2,
"type": "column",
"value": "start_date"
},
{
"id": 3,
"type": "value",
"value": "8/29/2013%"
},
{
"id": 4,
"type": "column",
"value": "end_date"
},
{
"id": 9,
"type": "column",
"value": "duration"
},
{
"id": 1,
"type": "column",
"value": "bike_id"
},
{
"id": 0,
"type": "table",
"value": "trip"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
21,
22,
23
]
},
{
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},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
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"token_idxs": [
19
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10,
11,
12
]
},
{
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},
{
"entity_id": 8,
"token_idxs": [
15,
16,
17
]
},
{
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13
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},
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"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
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"entity_id": 15,
"token_idxs": []
},
{
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
15,812
|
university
|
bird:train.json:7996
|
What is the name of the university that has the lowest number of students of all time?
|
SELECT T2.university_name FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id ORDER BY T1.num_students LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"university",
"that",
"has",
"the",
"lowest",
"number",
"of",
"students",
"of",
"all",
"time",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 4,
"type": "column",
"value": "university_id"
},
{
"id": 3,
"type": "column",
"value": "num_students"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
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"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,813
|
shipping
|
bird:train.json:5600
|
For the shipment received by Leszek Kieltyka on 2017/9/25, what was its weight?
|
SELECT T1.weight FROM shipment AS T1 INNER JOIN driver AS T2 ON T1.driver_id = T2.driver_id WHERE T2.first_name = 'Leszek' AND T2.last_name = 'Kieltyka' AND T1.ship_date = '2017-09-25'
|
[
"For",
"the",
"shipment",
"received",
"by",
"Leszek",
"Kieltyka",
"on",
"2017/9/25",
",",
"what",
"was",
"its",
"weight",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 9,
"type": "value",
"value": "2017-09-25"
},
{
"id": 3,
"type": "column",
"value": "driver_id"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 8,
"type": "column",
"value": "ship_date"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 7,
"type": "value",
"value": "Kieltyka"
},
{
"id": 0,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "table",
"value": "driver"
},
{
"id": 5,
"type": "value",
"value": "Leszek"
}
] |
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{
"entity_id": 0,
"token_idxs": [
13
]
},
{
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2
]
},
{
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},
{
"entity_id": 3,
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3
]
},
{
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{
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5
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},
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6
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},
{
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8
]
},
{
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},
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},
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},
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,814
|
movie_3
|
bird:train.json:9151
|
Give the detailed address for store No.2.
|
SELECT T1.address, T1.address2, T1.district FROM address AS T1 INNER JOIN store AS T2 ON T1.address_id = T2.address_id WHERE T2.store_id = 2
|
[
"Give",
"the",
"detailed",
"address",
"for",
"store",
"No.2",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "address_id"
},
{
"id": 1,
"type": "column",
"value": "address2"
},
{
"id": 2,
"type": "column",
"value": "district"
},
{
"id": 5,
"type": "column",
"value": "store_id"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 3,
"type": "table",
"value": "address"
},
{
"id": 4,
"type": "table",
"value": "store"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O"
] |
15,815
|
works_cycles
|
bird:train.json:7022
|
List all products with minimum order quantity of 100 and order them by product name in descending order.
|
SELECT DISTINCT T1.Name FROM Product AS T1 INNER JOIN ProductVendor AS T2 ON T1.ProductID = T2.ProductID WHERE T2.MinOrderQty = 100 ORDER BY T1.Name DESC
|
[
"List",
"all",
"products",
"with",
"minimum",
"order",
"quantity",
"of",
"100",
"and",
"order",
"them",
"by",
"product",
"name",
"in",
"descending",
"order",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "productvendor"
},
{
"id": 3,
"type": "column",
"value": "minorderqty"
},
{
"id": 5,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,816
|
college_3
|
spider:train_spider.json:4674
|
What is the name of the department htat has no students minoring in it?
|
SELECT DName FROM DEPARTMENT EXCEPT SELECT T1.DName FROM DEPARTMENT AS T1 JOIN MINOR_IN AS T2 ON T1.DNO = T2.DNO
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"department",
"htat",
"has",
"no",
"students",
"minoring",
"in",
"it",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "department"
},
{
"id": 2,
"type": "table",
"value": "minor_in"
},
{
"id": 1,
"type": "column",
"value": "dname"
},
{
"id": 3,
"type": "column",
"value": "dno"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
15,817
|
railway
|
spider:train_spider.json:5647
|
Show the locations that have more than one railways.
|
SELECT LOCATION FROM railway GROUP BY LOCATION HAVING COUNT(*) > 1
|
[
"Show",
"the",
"locations",
"that",
"have",
"more",
"than",
"one",
"railways",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "railway"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,818
|
university_rank
|
bird:test.json:1776
|
What are the home conferences with the fewest number of people enrolled?
|
SELECT home_conference FROM University GROUP BY home_conference ORDER BY sum(enrollment) LIMIT 1
|
[
"What",
"are",
"the",
"home",
"conferences",
"with",
"the",
"fewest",
"number",
"of",
"people",
"enrolled",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "home_conference"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "column",
"value": "enrollment"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,820
|
thrombosis_prediction
|
bird:dev.json:1249
|
Please list the disease names of the patients that have a proteinuria level higher than normal.
|
SELECT T1.Diagnosis FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.`U-PRO` >= 30
|
[
"Please",
"list",
"the",
"disease",
"names",
"of",
"the",
"patients",
"that",
"have",
"a",
"proteinuria",
"level",
"higher",
"than",
"normal",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 1,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "U-PRO"
},
{
"id": 4,
"type": "value",
"value": "30"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,821
|
chicago_crime
|
bird:train.json:8754
|
Among the crimes happened in the neighborhood called "Avalon Park", what is the percentage of crimes that happened inside the house?
|
SELECT CAST(SUM(CASE WHEN T2.location_description = 'HOUSE' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.location_description) AS persent FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T1.community_area_no = T2.community_area_no INNER JOIN Neighborhood AS T3 ON T2.community_area_no = T3.community_area_no WHERE T3.neighborhood_name = 'Avalon Park'
|
[
"Among",
"the",
"crimes",
"happened",
"in",
"the",
"neighborhood",
"called",
"\"",
"Avalon",
"Park",
"\"",
",",
"what",
"is",
"the",
"percentage",
"of",
"crimes",
"that",
"happened",
"inside",
"the",
"house",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "location_description"
},
{
"id": 1,
"type": "column",
"value": "neighborhood_name"
},
{
"id": 5,
"type": "column",
"value": "community_area_no"
},
{
"id": 3,
"type": "table",
"value": "community_area"
},
{
"id": 0,
"type": "table",
"value": "neighborhood"
},
{
"id": 2,
"type": "value",
"value": "Avalon Park"
},
{
"id": 4,
"type": "table",
"value": "crime"
},
{
"id": 10,
"type": "value",
"value": "HOUSE"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
23
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,822
|
video_games
|
bird:train.json:3436
|
List the name of all games published in Japan.
|
SELECT T1.game_name FROM game AS T1 INNER JOIN game_publisher AS T2 ON T1.id = T2.game_id INNER JOIN game_platform AS T3 ON T2.id = T3.game_publisher_id INNER JOIN region_sales AS T4 ON T3.id = T4.game_platform_id INNER JOIN region AS T5 ON T4.region_id = T5.id WHERE T5.region_name = 'Japan'
|
[
"List",
"the",
"name",
"of",
"all",
"games",
"published",
"in",
"Japan",
"."
] |
[
{
"id": 11,
"type": "column",
"value": "game_publisher_id"
},
{
"id": 8,
"type": "column",
"value": "game_platform_id"
},
{
"id": 10,
"type": "table",
"value": "game_publisher"
},
{
"id": 7,
"type": "table",
"value": "game_platform"
},
{
"id": 4,
"type": "table",
"value": "region_sales"
},
{
"id": 2,
"type": "column",
"value": "region_name"
},
{
"id": 0,
"type": "column",
"value": "game_name"
},
{
"id": 5,
"type": "column",
"value": "region_id"
},
{
"id": 12,
"type": "column",
"value": "game_id"
},
{
"id": 1,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "value",
"value": "Japan"
},
{
"id": 9,
"type": "table",
"value": "game"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
5
]
},
{
"entity_id": 10,
"token_idxs": [
6
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,823
|
music_1
|
spider:train_spider.json:3603
|
What are the shortest duration and lowest rating of songs grouped by genre and ordered 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",
"are",
"the",
"shortest",
"duration",
"and",
"lowest",
"rating",
"of",
"songs",
"grouped",
"by",
"genre",
"and",
"ordered",
"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": [
12
]
},
{
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9
]
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{
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4
]
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7
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"token_idxs": []
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"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,824
|
hr_1
|
spider:train_spider.json:3411
|
Return all the information for all employees without any department number.
|
SELECT * FROM employees WHERE department_id = "null"
|
[
"Return",
"all",
"the",
"information",
"for",
"all",
"employees",
"without",
"any",
"department",
"number",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "null"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
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{
"entity_id": 1,
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9
]
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{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
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{
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{
"entity_id": 14,
"token_idxs": []
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"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,825
|
e_commerce
|
bird:test.json:115
|
What are the dates and ids of the invoices that are related to at least 2 shipments?
|
SELECT T1.invoice_date , T1.invoice_number FROM Invoices AS T1 JOIN Shipments AS T2 ON T1.invoice_number = T2.invoice_number GROUP BY T1.invoice_number HAVING count(*) >= 2
|
[
"What",
"are",
"the",
"dates",
"and",
"ids",
"of",
"the",
"invoices",
"that",
"are",
"related",
"to",
"at",
"least",
"2",
"shipments",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "invoice_number"
},
{
"id": 1,
"type": "column",
"value": "invoice_date"
},
{
"id": 3,
"type": "table",
"value": "shipments"
},
{
"id": 2,
"type": "table",
"value": "invoices"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
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"entity_id": 1,
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9
]
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{
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8
]
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{
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16
]
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{
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"token_idxs": [
15
]
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{
"entity_id": 5,
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},
{
"entity_id": 6,
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{
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"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
15,826
|
retails
|
bird:train.json:6893
|
How much higher in percentage is the highest supply cost of the part "hot spring dodger dim light" than the lowest supply cost?
|
SELECT CAST((MAX(T1.ps_supplycost) - MIN(T1.ps_supplycost)) AS REAL) * 100 / MIN(T1.ps_supplycost) FROM partsupp AS T1 INNER JOIN supplier AS T2 ON T1.ps_suppkey = T2.s_suppkey INNER JOIN part AS T3 ON T1.ps_partkey = T3.p_partkey WHERE T3.p_name = 'hot spring dodger dim light'
|
[
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"higher",
"in",
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"the",
"highest",
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"cost",
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"\"",
"hot",
"spring",
"dodger",
"dim",
"light",
"\"",
"than",
"the",
"lowest",
"supply",
"cost",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "hot spring dodger dim light"
},
{
"id": 8,
"type": "column",
"value": "ps_supplycost"
},
{
"id": 5,
"type": "column",
"value": "ps_partkey"
},
{
"id": 9,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 6,
"type": "column",
"value": "p_partkey"
},
{
"id": 10,
"type": "column",
"value": "s_suppkey"
},
{
"id": 3,
"type": "table",
"value": "partsupp"
},
{
"id": 4,
"type": "table",
"value": "supplier"
},
{
"id": 1,
"type": "column",
"value": "p_name"
},
{
"id": 0,
"type": "table",
"value": "part"
},
{
"id": 7,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
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12
]
},
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15,
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{
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{
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{
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9
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{
"entity_id": 13,
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"entity_id": 14,
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"entity_id": 15,
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{
"entity_id": 16,
"token_idxs": []
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,827
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6467
|
What are the account details with the largest value or with value having char '5' in it?
|
SELECT max(Account_details) FROM Accounts UNION SELECT Account_details FROM Accounts WHERE Account_details LIKE "%5%"
|
[
"What",
"are",
"the",
"account",
"details",
"with",
"the",
"largest",
"value",
"or",
"with",
"value",
"having",
"char",
"'",
"5",
"'",
"in",
"it",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "account_details"
},
{
"id": 0,
"type": "table",
"value": "accounts"
},
{
"id": 2,
"type": "column",
"value": "%5%"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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4
]
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},
{
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},
{
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},
{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,828
|
planet_1
|
bird:test.json:1868
|
What is the number of all packages that Leo Wong sent?
|
SELECT T1.PackageNumber FROM PACKAGE AS T1 JOIN Client AS T2 ON T1.Sender = T2.AccountNumber WHERE T2.Name = "Leo Wong";
|
[
"What",
"is",
"the",
"number",
"of",
"all",
"packages",
"that",
"Leo",
"Wong",
"sent",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "packagenumber"
},
{
"id": 6,
"type": "column",
"value": "accountnumber"
},
{
"id": 4,
"type": "column",
"value": "Leo Wong"
},
{
"id": 1,
"type": "table",
"value": "package"
},
{
"id": 2,
"type": "table",
"value": "client"
},
{
"id": 5,
"type": "column",
"value": "sender"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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6
]
},
{
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3
]
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8,
9
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},
{
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{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
15,829
|
small_bank_1
|
spider:train_spider.json:1795
|
What are the balances of checking accounts belonging to people with savings balances greater than the average savings balance?
|
SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name IN (SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM savings))
|
[
"What",
"are",
"the",
"balances",
"of",
"checking",
"accounts",
"belonging",
"to",
"people",
"with",
"savings",
"balances",
"greater",
"than",
"the",
"average",
"savings",
"balance",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "accounts"
},
{
"id": 2,
"type": "table",
"value": "checking"
},
{
"id": 0,
"type": "column",
"value": "balance"
},
{
"id": 5,
"type": "table",
"value": "savings"
},
{
"id": 4,
"type": "column",
"value": "custid"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
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},
{
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},
{
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]
},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
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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",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,830
|
university
|
bird:train.json:8050
|
What is the ID of the Publications Rank criteria?
|
SELECT id FROM ranking_criteria WHERE criteria_name = 'Publications Rank'
|
[
"What",
"is",
"the",
"ID",
"of",
"the",
"Publications",
"Rank",
"criteria",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Publications Rank"
},
{
"id": 0,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 2,
"type": "column",
"value": "criteria_name"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"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-VALUE",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,831
|
movie_3
|
bird:train.json:9146
|
State the number of addresses in the Nordrhein-Westfalen district.
|
SELECT COUNT(address_id) FROM address WHERE district = 'Nordrhein-Westfalen'
|
[
"State",
"the",
"number",
"of",
"addresses",
"in",
"the",
"Nordrhein",
"-",
"Westfalen",
"district",
"."
] |
[
{
"id": 2,
"type": "value",
"value": "Nordrhein-Westfalen"
},
{
"id": 3,
"type": "column",
"value": "address_id"
},
{
"id": 1,
"type": "column",
"value": "district"
},
{
"id": 0,
"type": "table",
"value": "address"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8,
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",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
15,832
|
student_loan
|
bird:train.json:4555
|
How many students enlisted in the Navy?
|
SELECT COUNT(name) FROM enlist WHERE organ = 'navy'
|
[
"How",
"many",
"students",
"enlisted",
"in",
"the",
"Navy",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "enlist"
},
{
"id": 1,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "value",
"value": "navy"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
15,833
|
product_catalog
|
spider:train_spider.json:334
|
Which attribute definitions have attribute value 0? Give me the attribute name and attribute ID.
|
SELECT t1.attribute_name , t1.attribute_id FROM Attribute_Definitions AS t1 JOIN Catalog_Contents_Additional_Attributes AS t2 ON t1.attribute_id = t2.attribute_id WHERE t2.attribute_value = 0
|
[
"Which",
"attribute",
"definitions",
"have",
"attribute",
"value",
"0",
"?",
"Give",
"me",
"the",
"attribute",
"name",
"and",
"attribute",
"ID",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "catalog_contents_additional_attributes"
},
{
"id": 2,
"type": "table",
"value": "attribute_definitions"
},
{
"id": 4,
"type": "column",
"value": "attribute_value"
},
{
"id": 0,
"type": "column",
"value": "attribute_name"
},
{
"id": 1,
"type": "column",
"value": "attribute_id"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11,
12
]
},
{
"entity_id": 1,
"token_idxs": [
14,
15
]
},
{
"entity_id": 2,
"token_idxs": [
1,
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,834
|
disney
|
bird:train.json:4735
|
Among all Disney movies directed by Gary Trousdale, determine the percentage that earned over USD100m based on actual grossing.
|
SELECT CAST(COUNT(CASE WHEN CAST(REPLACE(trim(T1.total_gross, '$'), ',', '') AS REAL) > 100000000 THEN T1.movie_title ELSE NULL END) AS REAL) * 100 / COUNT(T1.movie_title) FROM movies_total_gross AS T1 INNER JOIN director AS T2 ON T1.movie_title = T2.name WHERE T2.director = 'Gary Trousdale'
|
[
"Among",
"all",
"Disney",
"movies",
"directed",
"by",
"Gary",
"Trousdale",
",",
"determine",
"the",
"percentage",
"that",
"earned",
"over",
"USD100",
"m",
"based",
"on",
"actual",
"grossing",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "movies_total_gross"
},
{
"id": 3,
"type": "value",
"value": "Gary Trousdale"
},
{
"id": 4,
"type": "column",
"value": "movie_title"
},
{
"id": 9,
"type": "column",
"value": "total_gross"
},
{
"id": 7,
"type": "value",
"value": "100000000"
},
{
"id": 1,
"type": "table",
"value": "director"
},
{
"id": 2,
"type": "column",
"value": "director"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": ","
},
{
"id": 10,
"type": "value",
"value": "$"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": [
19,
20
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,835
|
talkingdata
|
bird:train.json:1218
|
Please list any three events that have the longitude and latitude of 0.
|
SELECT event_id FROM events WHERE longitude = 0 AND latitude = 0 LIMIT 3
|
[
"Please",
"list",
"any",
"three",
"events",
"that",
"have",
"the",
"longitude",
"and",
"latitude",
"of",
"0",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "longitude"
},
{
"id": 1,
"type": "column",
"value": "event_id"
},
{
"id": 4,
"type": "column",
"value": "latitude"
},
{
"id": 0,
"type": "table",
"value": "events"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
15,836
|
movie_1
|
spider:train_spider.json:2484
|
Find the titles of all movies not reviewed by Chris Jackson.
|
SELECT DISTINCT title FROM Movie EXCEPT SELECT T2.title FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID JOIN Reviewer AS T3 ON T1.rID = T3.rID WHERE T3.name = 'Chris Jackson'
|
[
"Find",
"the",
"titles",
"of",
"all",
"movies",
"not",
"reviewed",
"by",
"Chris",
"Jackson",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Chris Jackson"
},
{
"id": 2,
"type": "table",
"value": "reviewer"
},
{
"id": 5,
"type": "table",
"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "rid"
},
{
"id": 7,
"type": "column",
"value": "mid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,837
|
public_review_platform
|
bird:train.json:3987
|
How many 2 stars rated business located in Phoenix, Arizona?
|
SELECT COUNT(business_id) FROM Business WHERE city = 'Phoenix' AND state = 'AZ' AND stars = 2
|
[
"How",
"many",
"2",
"stars",
"rated",
"business",
"located",
"in",
"Phoenix",
",",
"Arizona",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 3,
"type": "value",
"value": "Phoenix"
},
{
"id": 4,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "value",
"value": "AZ"
},
{
"id": 7,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": [
2
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
15,838
|
language_corpus
|
bird:train.json:5699
|
What is the wikipedia page id of Arqueozoologia?
|
SELECT page FROM pages WHERE title = 'Arqueozoologia'
|
[
"What",
"is",
"the",
"wikipedia",
"page",
"i",
"d",
"of",
"Arqueozoologia",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Arqueozoologia"
},
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "column",
"value": "page"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,839
|
loan_1
|
spider:train_spider.json:3030
|
How many distinct types of accounts are there?
|
SELECT count(DISTINCT acc_type) FROM customer
|
[
"How",
"many",
"distinct",
"types",
"of",
"accounts",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 1,
"type": "column",
"value": "acc_type"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
15,841
|
professional_basketball
|
bird:train.json:2869
|
What is the average height of an East conference All-star player?
|
SELECT AVG(DISTINCT height) FROM players AS T1 INNER JOIN player_allstar AS T2 ON T1.playerID = T2.playerID WHERE conference = 'East'
|
[
"What",
"is",
"the",
"average",
"height",
"of",
"an",
"East",
"conference",
"All",
"-",
"star",
"player",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "player_allstar"
},
{
"id": 2,
"type": "column",
"value": "conference"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "players"
},
{
"id": 4,
"type": "column",
"value": "height"
},
{
"id": 3,
"type": "value",
"value": "East"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
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7
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-TABLE",
"O"
] |
15,842
|
university_basketball
|
spider:train_spider.json:1007
|
Find how many different affiliation types there are.
|
SELECT count(DISTINCT affiliation) FROM university
|
[
"Find",
"how",
"many",
"different",
"affiliation",
"types",
"there",
"are",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "affiliation"
},
{
"id": 0,
"type": "table",
"value": "university"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
15,843
|
college_1
|
spider:train_spider.json:3245
|
What is the first name of students enrolled in class ACCT-211 and got grade C?
|
SELECT T3.stu_fname FROM CLASS AS T1 JOIN enroll AS T2 ON T1.class_code = T2.class_code JOIN student AS T3 ON T2.stu_num = T3.stu_num WHERE T1.crs_code = 'ACCT-211' AND T2.enroll_grade = 'C'
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"students",
"enrolled",
"in",
"class",
"ACCT-211",
"and",
"got",
"grade",
"C",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "enroll_grade"
},
{
"id": 9,
"type": "column",
"value": "class_code"
},
{
"id": 0,
"type": "column",
"value": "stu_fname"
},
{
"id": 5,
"type": "column",
"value": "crs_code"
},
{
"id": 6,
"type": "value",
"value": "ACCT-211"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 4,
"type": "column",
"value": "stu_num"
},
{
"id": 3,
"type": "table",
"value": "enroll"
},
{
"id": 2,
"type": "table",
"value": "class"
},
{
"id": 8,
"type": "value",
"value": "C"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
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