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12,736
|
world
|
bird:train.json:7846
|
Give the cities and district names that belong to the country with Hajastan as its local name.
|
SELECT T2.Name, T2.District FROM Country AS T1 INNER JOIN City AS T2 ON T1.Code = T2.CountryCode WHERE T1.LocalName = 'Hajastan'
|
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"O",
"O",
"B-COLUMN",
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"O"
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12,737
|
game_injury
|
spider:train_spider.json:1291
|
How many games has each stadium held?
|
SELECT T1.id , count(*) FROM stadium AS T1 JOIN game AS T2 ON T1.id = T2.stadium_id GROUP BY T1.id
|
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[
"O",
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"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
12,738
|
shop_membership
|
spider:train_spider.json:5440
|
Find the name of branches where have some members whose hometown is in Louisville, Kentucky and some in Hiram, Georgia.
|
SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Louisville , Kentucky' INTERSECT SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Hiram , Georgia'
|
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"value": "branch"
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"B-VALUE",
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"I-VALUE",
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12,739
|
voter_2
|
spider:train_spider.json:5471
|
List all the distinct president votes and the vice president votes.
|
SELECT DISTINCT President_Vote , VICE_President_Vote FROM VOTING_RECORD
|
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"value": "president_vote"
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{
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"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
12,740
|
cs_semester
|
bird:train.json:887
|
What is the percentage of students who get a "B" in the course "Computer Network"?
|
SELECT CAST(SUM(CASE WHEN T1.grade = 'B' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.student_id) FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T2.name = 'Computer Network'
|
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"value": "100"
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"value": "1"
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"value": "B"
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"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,742
|
ice_hockey_draft
|
bird:train.json:6989
|
Which team has the most Swedish?
|
SELECT T.TEAM FROM ( SELECT T2.TEAM, COUNT(DISTINCT T1.ELITEID) FROM PlayerInfo AS T1 INNER JOIN SeasonStatus AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.nation = 'Sweden' GROUP BY T2.TEAM ORDER BY COUNT(DISTINCT T1.ELITEID) DESC LIMIT 1 ) AS T
|
[
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"value": "eliteid"
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{
"id": 3,
"type": "column",
"value": "nation"
},
{
"id": 4,
"type": "value",
"value": "Sweden"
},
{
"id": 0,
"type": "column",
"value": "team"
}
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[
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,743
|
books
|
bird:train.json:6043
|
What is the average number of pages in the books written by Jennifer Crusie?
|
SELECT AVG(T1.num_pages) FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'Jennifer Crusie'
|
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{
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12,744
|
student_club
|
bird:dev.json:1380
|
What is the total amount of money spent for food?
|
SELECT SUM(spent) FROM budget WHERE category = 'Food'
|
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{
"id": 1,
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{
"id": 3,
"type": "column",
"value": "spent"
},
{
"id": 2,
"type": "value",
"value": "Food"
}
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"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,745
|
synthea
|
bird:train.json:1424
|
How many times did Keven Kuhn receive DTaP immunization?
|
SELECT COUNT(T2.CODE) FROM patients AS T1 INNER JOIN immunizations AS T2 ON T1.patient = T2.PATIENT WHERE T1.first = 'Keven' AND T1.last = 'Kuhn' AND T2.DESCRIPTION = 'DTaP'
|
[
"How",
"many",
"times",
"did",
"Keven",
"Kuhn",
"receive",
"DTaP",
"immunization",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "immunizations"
},
{
"id": 8,
"type": "column",
"value": "description"
},
{
"id": 0,
"type": "table",
"value": "patients"
},
{
"id": 3,
"type": "column",
"value": "patient"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 5,
"type": "value",
"value": "Keven"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 6,
"type": "column",
"value": "last"
},
{
"id": 7,
"type": "value",
"value": "Kuhn"
},
{
"id": 9,
"type": "value",
"value": "DTaP"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
7
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
12,746
|
products_gen_characteristics
|
spider:train_spider.json:5561
|
What are the names and data types of the characteristics of the 'cumin' product?
|
SELECT t3.characteristic_name , t3.characteristic_data_type 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 WHERE t1.product_name = "cumin"
|
[
"What",
"are",
"the",
"names",
"and",
"data",
"types",
"of",
"the",
"characteristics",
"of",
"the",
"'",
"cumin",
"'",
"product",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "characteristic_data_type"
},
{
"id": 6,
"type": "table",
"value": "product_characteristics"
},
{
"id": 0,
"type": "column",
"value": "characteristic_name"
},
{
"id": 7,
"type": "column",
"value": "characteristic_id"
},
{
"id": 2,
"type": "table",
"value": "characteristics"
},
{
"id": 3,
"type": "column",
"value": "product_name"
},
{
"id": 8,
"type": "column",
"value": "product_id"
},
{
"id": 5,
"type": "table",
"value": "products"
},
{
"id": 4,
"type": "column",
"value": "cumin"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
12,747
|
soccer_2
|
spider:train_spider.json:4962
|
How many students got accepted after the tryout?
|
SELECT count(*) FROM tryout WHERE decision = 'yes'
|
[
"How",
"many",
"students",
"got",
"accepted",
"after",
"the",
"tryout",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "decision"
},
{
"id": 0,
"type": "table",
"value": "tryout"
},
{
"id": 2,
"type": "value",
"value": "yes"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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"
] |
12,748
|
movie_platform
|
bird:train.json:112
|
Which year had the most released films?
|
SELECT movie_release_year FROM movies GROUP BY movie_release_year ORDER BY COUNT(movie_id) DESC LIMIT 1
|
[
"Which",
"year",
"had",
"the",
"most",
"released",
"films",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "movie_release_year"
},
{
"id": 2,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O"
] |
12,749
|
sales_in_weather
|
bird:train.json:8160
|
Tell the resultant wind speed of station no.9 on 2014/1/15.
|
SELECT resultspeed FROM weather WHERE `date` = '2014-01-15' AND station_nbr = 9
|
[
"Tell",
"the",
"resultant",
"wind",
"speed",
"of",
"station",
"no.9",
"on",
"2014/1/15",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "resultspeed"
},
{
"id": 4,
"type": "column",
"value": "station_nbr"
},
{
"id": 3,
"type": "value",
"value": "2014-01-15"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 2,
"type": "column",
"value": "date"
},
{
"id": 5,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,750
|
address_1
|
bird:test.json:829
|
What is the name of the city furthest to Boston?
|
SELECT T3.city_name FROM Direct_distance AS T1 JOIN City AS T2 ON T1.city1_code = T2.city_code JOIN City AS T3 ON T1.city2_code = T3.city_code WHERE T2.city_name = "Boston" ORDER BY distance DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"city",
"furthest",
"to",
"Boston",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "direct_distance"
},
{
"id": 5,
"type": "column",
"value": "city2_code"
},
{
"id": 7,
"type": "column",
"value": "city1_code"
},
{
"id": 0,
"type": "column",
"value": "city_name"
},
{
"id": 6,
"type": "column",
"value": "city_code"
},
{
"id": 3,
"type": "column",
"value": "distance"
},
{
"id": 2,
"type": "column",
"value": "Boston"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
12,751
|
music_2
|
spider:train_spider.json:5237
|
What information is there on albums from 2010?
|
SELECT * FROM Albums WHERE YEAR = 2010
|
[
"What",
"information",
"is",
"there",
"on",
"albums",
"from",
"2010",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "albums"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2010"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
12,752
|
student_loan
|
bird:train.json:4559
|
Among the students that have a payment due, how many students are unemployed?
|
SELECT COUNT(T1.name) FROM no_payment_due AS T1 INNER JOIN unemployed AS T2 ON T1.name = T2.name WHERE T1.bool = 'pos'
|
[
"Among",
"the",
"students",
"that",
"have",
"a",
"payment",
"due",
",",
"how",
"many",
"students",
"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"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"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",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,754
|
allergy_1
|
spider:train_spider.json:480
|
Who advises student 1004?
|
SELECT Advisor FROM Student WHERE StuID = 1004
|
[
"Who",
"advises",
"student",
"1004",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "advisor"
},
{
"id": 2,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "value",
"value": "1004"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O"
] |
12,755
|
twitter_1
|
spider:train_spider.json:292
|
List the name and number of followers for each user, and sort the results by the number of followers in descending order.
|
SELECT name , followers FROM user_profiles ORDER BY followers DESC
|
[
"List",
"the",
"name",
"and",
"number",
"of",
"followers",
"for",
"each",
"user",
",",
"and",
"sort",
"the",
"results",
"by",
"the",
"number",
"of",
"followers",
"in",
"descending",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "user_profiles"
},
{
"id": 2,
"type": "column",
"value": "followers"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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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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},
{
"entity_id": 11,
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,756
|
e_commerce
|
bird:test.json:44
|
List the dates of the orders which were placed at the earliest time or have more than 1 items.
|
SELECT min(date_order_placed) FROM Orders UNION SELECT T1.date_order_placed FROM Orders AS T1 JOIN Order_items AS T2 ON T1.order_id = T2.order_id GROUP BY T1.order_id HAVING count(*) > 1
|
[
"List",
"the",
"dates",
"of",
"the",
"orders",
"which",
"were",
"placed",
"at",
"the",
"earliest",
"time",
"or",
"have",
"more",
"than",
"1",
"items",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "date_order_placed"
},
{
"id": 3,
"type": "table",
"value": "order_items"
},
{
"id": 1,
"type": "column",
"value": "order_id"
},
{
"id": 0,
"type": "table",
"value": "orders"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
12,758
|
manufactory_1
|
spider:train_spider.json:5349
|
For each manufacturer name, what are the names and prices of their most expensive product?
|
SELECT T1.Name , max(T1.Price) , T2.name FROM products AS T1 JOIN Manufacturers AS T2 ON T1.manufacturer = T2.code GROUP BY T2.name
|
[
"For",
"each",
"manufacturer",
"name",
",",
"what",
"are",
"the",
"names",
"and",
"prices",
"of",
"their",
"most",
"expensive",
"product",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "manufacturers"
},
{
"id": 4,
"type": "column",
"value": "manufacturer"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
15
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,759
|
student_club
|
bird:dev.json:1330
|
What college offers the major that Tyler Hewitt took?
|
SELECT T2.college FROM member AS T1 INNER JOIN major AS T2 ON T1.link_to_major = T2.major_id WHERE T1.first_name = 'Tyler' AND T1.last_name = 'Hewitt'
|
[
"What",
"college",
"offers",
"the",
"major",
"that",
"Tyler",
"Hewitt",
"took",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "link_to_major"
},
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "column",
"value": "major_id"
},
{
"id": 0,
"type": "column",
"value": "college"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 8,
"type": "value",
"value": "Hewitt"
},
{
"id": 2,
"type": "table",
"value": "major"
},
{
"id": 6,
"type": "value",
"value": "Tyler"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O"
] |
12,760
|
college_completion
|
bird:train.json:3731
|
List down the states in 2011 with a national sector average of 20 and below.
|
SELECT DISTINCT T1.state FROM state_sector_details AS T1 INNER JOIN state_sector_grads AS T2 ON T2.stateid = T1.stateid WHERE T2.year = 2011 AND T1.awards_per_natl_value <= 20
|
[
"List",
"down",
"the",
"states",
"in",
"2011",
"with",
"a",
"national",
"sector",
"average",
"of",
"20",
"and",
"below",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "awards_per_natl_value"
},
{
"id": 1,
"type": "table",
"value": "state_sector_details"
},
{
"id": 2,
"type": "table",
"value": "state_sector_grads"
},
{
"id": 3,
"type": "column",
"value": "stateid"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2011"
},
{
"id": 7,
"type": "value",
"value": "20"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,761
|
pilot_1
|
bird:test.json:1106
|
Return the location of the hangar in which F-14 Fighter is located.
|
SELECT LOCATION FROM hangar WHERE plane_name = 'F-14 Fighter'
|
[
"Return",
"the",
"location",
"of",
"the",
"hangar",
"in",
"which",
"F-14",
"Fighter",
"is",
"located",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "F-14 Fighter"
},
{
"id": 2,
"type": "column",
"value": "plane_name"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "hangar"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
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",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
12,762
|
olympics
|
bird:train.json:4986
|
How many female athletes are from the Philippines?
|
SELECT COUNT(T2.person_id) FROM noc_region AS T1 INNER JOIN person_region AS T2 ON T1.id = T2.region_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T1.region_name = 'Philippines' AND T3.gender = 'F'
|
[
"How",
"many",
"female",
"athletes",
"are",
"from",
"the",
"Philippines",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "person_region"
},
{
"id": 5,
"type": "column",
"value": "region_name"
},
{
"id": 6,
"type": "value",
"value": "Philippines"
},
{
"id": 2,
"type": "table",
"value": "noc_region"
},
{
"id": 1,
"type": "column",
"value": "person_id"
},
{
"id": 9,
"type": "column",
"value": "region_id"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 7,
"type": "column",
"value": "gender"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "F"
}
] |
[
{
"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": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,763
|
european_football_1
|
bird:train.json:2763
|
How many times did Valencia's home team win in the LaLiga division?
|
SELECT COUNT(T1.HomeTeam) FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T2.name = 'LaLiga' AND T1.HomeTeam = 'Valencia' AND T1.FTR = 'H'
|
[
"How",
"many",
"times",
"did",
"Valencia",
"'s",
"home",
"team",
"win",
"in",
"the",
"LaLiga",
"division",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "divisions"
},
{
"id": 2,
"type": "column",
"value": "hometeam"
},
{
"id": 4,
"type": "column",
"value": "division"
},
{
"id": 7,
"type": "value",
"value": "Valencia"
},
{
"id": 0,
"type": "table",
"value": "matchs"
},
{
"id": 6,
"type": "value",
"value": "LaLiga"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "div"
},
{
"id": 8,
"type": "column",
"value": "ftr"
},
{
"id": 9,
"type": "value",
"value": "H"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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6,
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]
},
{
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3
]
},
{
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12
]
},
{
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},
{
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11
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},
{
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4
]
},
{
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},
{
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},
{
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},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,764
|
restaurant_1
|
spider:train_spider.json:2832
|
Which major has least number of students? List the major and the number of students.
|
SELECT Major , count(*) FROM Student GROUP BY Major ORDER BY count(Major) ASC LIMIT 1;
|
[
"Which",
"major",
"has",
"least",
"number",
"of",
"students",
"?",
"List",
"the",
"major",
"and",
"the",
"number",
"of",
"students",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,765
|
cre_Students_Information_Systems
|
bird:test.json:440
|
Compute the average amount of student loans.
|
SELECT avg(amount_of_loan) FROM Student_Loans
|
[
"Compute",
"the",
"average",
"amount",
"of",
"student",
"loans",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "amount_of_loan"
},
{
"id": 0,
"type": "table",
"value": "student_loans"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": [
3,
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",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"I-TABLE",
"O"
] |
12,766
|
soccer_2016
|
bird:train.json:1855
|
How many overs were there in the first innings of match ID "335996"?
|
SELECT COUNT(Over_Id) FROM Ball_by_Ball WHERE Match_Id = 335996 AND Innings_No = 1
|
[
"How",
"many",
"overs",
"were",
"there",
"in",
"the",
"first",
"innings",
"of",
"match",
"ID",
"\"",
"335996",
"\"",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ball_by_ball"
},
{
"id": 4,
"type": "column",
"value": "innings_no"
},
{
"id": 2,
"type": "column",
"value": "match_id"
},
{
"id": 1,
"type": "column",
"value": "over_id"
},
{
"id": 3,
"type": "value",
"value": "335996"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
12,767
|
college_3
|
spider:train_spider.json:4637
|
How many courses have more than 2 credits?
|
SELECT count(*) FROM COURSE WHERE Credits > 2
|
[
"How",
"many",
"courses",
"have",
"more",
"than",
"2",
"credits",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "credits"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,768
|
wrestler
|
spider:train_spider.json:1850
|
What are the distinct reigns of wrestlers whose location is not "Tokyo,Japan" ?
|
SELECT DISTINCT Reign FROM wrestler WHERE LOCATION != "Tokyo , Japan"
|
[
"What",
"are",
"the",
"distinct",
"reigns",
"of",
"wrestlers",
"whose",
"location",
"is",
"not",
"\"",
"Tokyo",
",",
"Japan",
"\"",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Tokyo , Japan"
},
{
"id": 0,
"type": "table",
"value": "wrestler"
},
{
"id": 2,
"type": "column",
"value": "location"
},
{
"id": 1,
"type": "column",
"value": "reign"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
12,769
|
computer_student
|
bird:train.json:999
|
In total, all the students in the 3rd year of their program are advised by how many professors?
|
SELECT COUNT(DISTINCT T1.p_id_dummy) FROM advisedBy AS T1 INNER JOIN person AS T2 ON T1.p_id = T2.p_id WHERE T2.yearsInProgram = 'Year_3'
|
[
"In",
"total",
",",
"all",
"the",
"students",
"in",
"the",
"3rd",
"year",
"of",
"their",
"program",
"are",
"advised",
"by",
"how",
"many",
"professors",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "yearsinprogram"
},
{
"id": 4,
"type": "column",
"value": "p_id_dummy"
},
{
"id": 0,
"type": "table",
"value": "advisedby"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 3,
"type": "value",
"value": "Year_3"
},
{
"id": 5,
"type": "column",
"value": "p_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14,
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O"
] |
12,770
|
retail_complains
|
bird:train.json:389
|
From 2012 to 2015, how many complaints were submitted via email from female clients?
|
SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE strftime('%Y', T2.`Date received`) BETWEEN '2012' AND '2015' AND T2.`Submitted via` = 'Email' AND T1.sex = 'Male'
|
[
"From",
"2012",
"to",
"2015",
",",
"how",
"many",
"complaints",
"were",
"submitted",
"via",
"email",
"from",
"female",
"clients",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "Submitted via"
},
{
"id": 10,
"type": "column",
"value": "Date received"
},
{
"id": 2,
"type": "column",
"value": "client_id"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "events"
},
{
"id": 6,
"type": "value",
"value": "Email"
},
{
"id": 3,
"type": "value",
"value": "2012"
},
{
"id": 4,
"type": "value",
"value": "2015"
},
{
"id": 8,
"type": "value",
"value": "Male"
},
{
"id": 7,
"type": "column",
"value": "sex"
},
{
"id": 9,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": [
9,
10
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
12,771
|
store_1
|
spider:train_spider.json:637
|
List the name of playlist which has number of tracks greater than 100.
|
SELECT T2.name FROM playlist_tracks AS T1 JOIN playlists AS T2 ON T2.id = T1.playlist_id GROUP BY T1.playlist_id HAVING count(T1.track_id) > 100;
|
[
"List",
"the",
"name",
"of",
"playlist",
"which",
"has",
"number",
"of",
"tracks",
"greater",
"than",
"100",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "playlist_tracks"
},
{
"id": 0,
"type": "column",
"value": "playlist_id"
},
{
"id": 3,
"type": "table",
"value": "playlists"
},
{
"id": 6,
"type": "column",
"value": "track_id"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,772
|
retail_world
|
bird:train.json:6426
|
What is the shipping cost for order number 10692 from the company Alfreds Futterkiste?
|
SELECT T2.Freight FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.OrderID = 10692 AND T1.CompanyName = 'Alfreds Futterkiste'
|
[
"What",
"is",
"the",
"shipping",
"cost",
"for",
"order",
"number",
"10692",
"from",
"the",
"company",
"Alfreds",
"Futterkiste",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Alfreds Futterkiste"
},
{
"id": 6,
"type": "column",
"value": "companyname"
},
{
"id": 3,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "column",
"value": "freight"
},
{
"id": 4,
"type": "column",
"value": "orderid"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 5,
"type": "value",
"value": "10692"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
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"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
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8
]
},
{
"entity_id": 6,
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11
]
},
{
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12,
13
]
},
{
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},
{
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},
{
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},
{
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},
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{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
12,773
|
thrombosis_prediction
|
bird:dev.json:1150
|
What is the percentage of female patient were born after 1930?
|
SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Birthday) > '1930' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Patient WHERE SEX = 'F'
|
[
"What",
"is",
"the",
"percentage",
"of",
"female",
"patient",
"were",
"born",
"after",
"1930",
"?"
] |
[
{
"id": 8,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 6,
"type": "value",
"value": "1930"
},
{
"id": 1,
"type": "column",
"value": "sex"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "%Y"
},
{
"id": 2,
"type": "value",
"value": "F"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
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"entity_id": 18,
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] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,774
|
art_1
|
bird:test.json:1302
|
What are the ids of the paintings whose height is longer than the height of all paintings created after 1900?
|
SELECT paintingID FROM paintings WHERE height_mm > (SELECT max(height_mm) FROM paintings WHERE YEAR > 1900)
|
[
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"ids",
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"height",
"of",
"all",
"paintings",
"created",
"after",
"1900",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "paintingid"
},
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 2,
"type": "column",
"value": "height_mm"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "1900"
}
] |
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"entity_id": 0,
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},
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},
{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,775
|
university
|
bird:train.json:8112
|
What is the average score of all universities in 2012?
|
SELECT AVG(score) FROM university_ranking_year WHERE year = 2012
|
[
"What",
"is",
"the",
"average",
"score",
"of",
"all",
"universities",
"in",
"2012",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 3,
"type": "column",
"value": "score"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2012"
}
] |
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{
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"entity_id": 15,
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},
{
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
12,776
|
olympics
|
bird:train.json:4997
|
How many 10-year old athletes participated in the Gymnastics Men's Parallel Bars, Teams event?
|
SELECT COUNT(T2.person_id) FROM competitor_event AS T1 INNER JOIN games_competitor AS T2 ON T1.competitor_id = T2.id INNER JOIN event AS T3 ON T1.event_id = T3.id WHERE T3.event_name LIKE 'Gymnastics Men%s Parallel Bars, Teams' AND T2.age = 10
|
[
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"-",
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"athletes",
"participated",
"in",
"the",
"Gymnastics",
"Men",
"'s",
"Parallel",
"Bars",
",",
"Teams",
"event",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Gymnastics Men%s Parallel Bars, Teams"
},
{
"id": 2,
"type": "table",
"value": "competitor_event"
},
{
"id": 3,
"type": "table",
"value": "games_competitor"
},
{
"id": 10,
"type": "column",
"value": "competitor_id"
},
{
"id": 6,
"type": "column",
"value": "event_name"
},
{
"id": 1,
"type": "column",
"value": "person_id"
},
{
"id": 4,
"type": "column",
"value": "event_id"
},
{
"id": 0,
"type": "table",
"value": "event"
},
{
"id": 8,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "10"
}
] |
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"O"
] |
12,777
|
college_1
|
spider:train_spider.json:3249
|
How many professors do have a Ph.D. degree?
|
SELECT count(*) FROM professor WHERE prof_high_degree = 'Ph.D.'
|
[
"How",
"many",
"professors",
"do",
"have",
"a",
"Ph.D.",
"degree",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "prof_high_degree"
},
{
"id": 0,
"type": "table",
"value": "professor"
},
{
"id": 2,
"type": "value",
"value": "Ph.D."
}
] |
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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",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
12,778
|
car_road_race
|
bird:test.json:1347
|
What are the engine types that are used by two or more drivers?
|
SELECT Engine FROM driver GROUP BY Engine HAVING COUNT(*) >= 2
|
[
"What",
"are",
"the",
"engine",
"types",
"that",
"are",
"used",
"by",
"two",
"or",
"more",
"drivers",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "engine"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
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{
"entity_id": 0,
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},
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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",
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"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,779
|
legislator
|
bird:train.json:4796
|
List the full names, religions, and parties of legislators who have served in Maine.
|
SELECT T1.official_full_name, T2.relation, T2.party FROM current AS T1 INNER JOIN `current-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.state = 'ME' GROUP BY T1.official_full_name, T2.relation, T2.party
|
[
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"names",
",",
"religions",
",",
"and",
"parties",
"of",
"legislators",
"who",
"have",
"served",
"in",
"Maine",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "official_full_name"
},
{
"id": 4,
"type": "table",
"value": "current-terms"
},
{
"id": 7,
"type": "column",
"value": "bioguide_id"
},
{
"id": 1,
"type": "column",
"value": "relation"
},
{
"id": 8,
"type": "column",
"value": "bioguide"
},
{
"id": 3,
"type": "table",
"value": "current"
},
{
"id": 2,
"type": "column",
"value": "party"
},
{
"id": 5,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "value",
"value": "ME"
}
] |
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{
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"token_idxs": []
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{
"entity_id": 19,
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[
"B-COLUMN",
"I-COLUMN",
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"O",
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"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,780
|
legislator
|
bird:train.json:4769
|
List the full name of all past legislators that chose Pro-Administration as their political party in year 1791.
|
SELECT T1.first_name, T1.last_name FROM historical AS T1 INNER JOIN `historical-terms` AS T2 ON T1.bioguide_id = T2.bioguide WHERE T2.party = 'Pro-Administration' AND CAST(T2.start AS DATE) <= 1791 AND CAST(T2.END AS DATE) >= 1791
|
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"-",
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"party",
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"1791",
"."
] |
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{
"id": 7,
"type": "value",
"value": "Pro-Administration"
},
{
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{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 0,
"type": "column",
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},
{
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"type": "table",
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{
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},
{
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},
{
"id": 6,
"type": "column",
"value": "party"
},
{
"id": 9,
"type": "column",
"value": "start"
},
{
"id": 8,
"type": "value",
"value": "1791"
},
{
"id": 10,
"type": "column",
"value": "end"
}
] |
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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",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,782
|
simpson_episodes
|
bird:train.json:4173
|
How many stars on average does the episode Lost Verizon have?
|
SELECT CAST(SUM(T2.votes * T2.stars) AS REAL) / SUM(T2.votes) FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE T1.title = 'Lost Verizon';
|
[
"How",
"many",
"stars",
"on",
"average",
"does",
"the",
"episode",
"Lost",
"Verizon",
"have",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Lost Verizon"
},
{
"id": 4,
"type": "column",
"value": "episode_id"
},
{
"id": 0,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "column",
"value": "votes"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 1,
"type": "table",
"value": "vote"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"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",
"B-COLUMN",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,783
|
bakery_1
|
bird:test.json:1544
|
What are the receipt numbers for which either an apple flavor pie was purchased or the customer with id 12 shopped?
|
SELECT T1.receipt FROM items AS T1 JOIN goods AS T2 ON T1.item = T2.id WHERE T2.flavor = "Apple" AND T2.food = "Pie" UNION SELECT ReceiptNumber FROM receipts WHERE CustomerId = 12
|
[
"What",
"are",
"the",
"receipt",
"numbers",
"for",
"which",
"either",
"an",
"apple",
"flavor",
"pie",
"was",
"purchased",
"or",
"the",
"customer",
"with",
"i",
"d",
"12",
"shopped",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "receiptnumber"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "receipts"
},
{
"id": 1,
"type": "column",
"value": "receipt"
},
{
"id": 9,
"type": "column",
"value": "flavor"
},
{
"id": 2,
"type": "table",
"value": "items"
},
{
"id": 3,
"type": "table",
"value": "goods"
},
{
"id": 10,
"type": "column",
"value": "Apple"
},
{
"id": 7,
"type": "column",
"value": "item"
},
{
"id": 11,
"type": "column",
"value": "food"
},
{
"id": 12,
"type": "column",
"value": "Pie"
},
{
"id": 6,
"type": "value",
"value": "12"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"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": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": [
18,
19
]
},
{
"entity_id": 9,
"token_idxs": [
10
]
},
{
"entity_id": 10,
"token_idxs": [
9
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": [
11
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"O"
] |
12,784
|
soccer_2016
|
bird:train.json:1907
|
List the name and country of the players who got more than average catches in ascending order of the number of catches.
|
SELECT T1.Player_Name, T4.Country_Name FROM Player AS T1 INNER JOIN Wicket_Taken AS T2 ON T1.Player_Id = T2.Fielders INNER JOIN Out_Type AS T3 ON T2.Kind_Out = T3.Out_Id INNER JOIN Country AS T4 ON T1.Country_Name = T4.Country_Id GROUP BY T1.Player_Name ORDER BY COUNT(T3.Out_Name) ASC
|
[
"List",
"the",
"name",
"and",
"country",
"of",
"the",
"players",
"who",
"got",
"more",
"than",
"average",
"catches",
"in",
"ascending",
"order",
"of",
"the",
"number",
"of",
"catches",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "country_name"
},
{
"id": 7,
"type": "table",
"value": "wicket_taken"
},
{
"id": 0,
"type": "column",
"value": "player_name"
},
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 10,
"type": "column",
"value": "player_id"
},
{
"id": 3,
"type": "table",
"value": "out_type"
},
{
"id": 5,
"type": "column",
"value": "out_name"
},
{
"id": 8,
"type": "column",
"value": "kind_out"
},
{
"id": 11,
"type": "column",
"value": "fielders"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "table",
"value": "player"
},
{
"id": 9,
"type": "column",
"value": "out_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,785
|
olympics
|
bird:train.json:4946
|
How many athletes are from Australia?
|
SELECT COUNT(T2.person_id) FROM noc_region AS T1 INNER JOIN person_region AS T2 ON T1.id = T2.region_id WHERE T1.region_name = 'Australia'
|
[
"How",
"many",
"athletes",
"are",
"from",
"Australia",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "person_region"
},
{
"id": 2,
"type": "column",
"value": "region_name"
},
{
"id": 0,
"type": "table",
"value": "noc_region"
},
{
"id": 3,
"type": "value",
"value": "Australia"
},
{
"id": 4,
"type": "column",
"value": "person_id"
},
{
"id": 6,
"type": "column",
"value": "region_id"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,786
|
software_company
|
bird:train.json:8560
|
What is the total number of widowed customers with an age below 50?
|
SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Widowed' AND age < 50
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"widowed",
"customers",
"with",
"an",
"age",
"below",
"50",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "marital_status"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "Widowed"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 5,
"type": "value",
"value": "50"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,787
|
books
|
bird:train.json:6033
|
What is the full name of the customers who live in Baiyin city?
|
SELECT T3.first_name, T3.last_name FROM address AS T1 INNER JOIN customer_address AS T2 ON T1.address_id = T2.address_id INNER JOIN customer AS T3 ON T3.customer_id = T2.customer_id WHERE T1.city = 'Baiyin'
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"customers",
"who",
"live",
"in",
"Baiyin",
"city",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "customer_address"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "address_id"
},
{
"id": 1,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "table",
"value": "customer"
},
{
"id": 5,
"type": "table",
"value": "address"
},
{
"id": 4,
"type": "value",
"value": "Baiyin"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,788
|
hockey
|
bird:train.json:7619
|
Name the goalies who have played more than total of 5000 minutes in the all the season played. State given name of the player and from which country was he born.
|
SELECT DISTINCT T1.nameGiven, T1.birthCountry FROM Master AS T1 INNER JOIN Goalies AS T2 ON T1.playerID = T2.playerID GROUP BY T1.nameGiven, T1.birthCountry HAVING SUM(T2.Min) > 5000
|
[
"Name",
"the",
"goalies",
"who",
"have",
"played",
"more",
"than",
"total",
"of",
"5000",
"minutes",
"in",
"the",
"all",
"the",
"season",
"played",
".",
"State",
"given",
"name",
"of",
"the",
"player",
"and",
"from",
"which",
"country",
"was",
"he",
"born",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "birthcountry"
},
{
"id": 0,
"type": "column",
"value": "namegiven"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 3,
"type": "table",
"value": "goalies"
},
{
"id": 2,
"type": "table",
"value": "master"
},
{
"id": 4,
"type": "value",
"value": "5000"
},
{
"id": 6,
"type": "column",
"value": "min"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": [
28
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
24
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
12,789
|
talkingdata
|
bird:train.json:1151
|
What is the device model used by the most female users over 30?
|
SELECT T.device_model FROM ( SELECT T2.device_model, COUNT(T2.device_model) AS num FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T1.age > 30 AND T1.gender = 'F' GROUP BY T2.device_model ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"What",
"is",
"the",
"device",
"model",
"used",
"by",
"the",
"most",
"female",
"users",
"over",
"30",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 0,
"type": "column",
"value": "device_model"
},
{
"id": 2,
"type": "table",
"value": "gender_age"
},
{
"id": 4,
"type": "column",
"value": "device_id"
},
{
"id": 7,
"type": "column",
"value": "gender"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 5,
"type": "column",
"value": "age"
},
{
"id": 6,
"type": "value",
"value": "30"
},
{
"id": 8,
"type": "value",
"value": "F"
}
] |
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{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,790
|
government_shift
|
bird:test.json:374
|
Count the total number of available customers and services details.
|
SELECT count(DISTINCT customers_and_services_details) FROM customers_and_services
|
[
"Count",
"the",
"total",
"number",
"of",
"available",
"customers",
"and",
"services",
"details",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customers_and_services_details"
},
{
"id": 0,
"type": "table",
"value": "customers_and_services"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8
]
},
{
"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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},
{
"entity_id": 5,
"token_idxs": []
},
{
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{
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},
{
"entity_id": 9,
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},
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"entity_id": 10,
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{
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"token_idxs": []
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-COLUMN",
"O"
] |
12,791
|
toxicology
|
bird:dev.json:261
|
Write down bond id for molecules that are carcinogenic.
|
SELECT DISTINCT T1.bond_id FROM bond AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T2.label = '+'
|
[
"Write",
"down",
"bond",
"i",
"d",
"for",
"molecules",
"that",
"are",
"carcinogenic",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 0,
"type": "column",
"value": "bond_id"
},
{
"id": 3,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "bond"
},
{
"id": 4,
"type": "value",
"value": "+"
}
] |
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{
"entity_id": 0,
"token_idxs": [
3,
4
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},
{
"entity_id": 1,
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2
]
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{
"entity_id": 2,
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6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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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": []
},
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"entity_id": 11,
"token_idxs": []
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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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",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
12,792
|
works_cycles
|
bird:train.json:7106
|
What is the employee of company number 1's full name?
|
SELECT FirstName, MiddleName, LastName FROM Person WHERE BusinessEntityID = 1 AND PersonType = 'EM'
|
[
"What",
"is",
"the",
"employee",
"of",
"company",
"number",
"1",
"'s",
"full",
"name",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "businessentityid"
},
{
"id": 2,
"type": "column",
"value": "middlename"
},
{
"id": 6,
"type": "column",
"value": "persontype"
},
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 3,
"type": "column",
"value": "lastname"
},
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 7,
"type": "value",
"value": "EM"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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7
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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},
{
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},
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},
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
12,793
|
aan_1
|
bird:test.json:998
|
What was the venue and year with the most publications?
|
SELECT venue , YEAR FROM paper GROUP BY venue , YEAR ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"was",
"the",
"venue",
"and",
"year",
"with",
"the",
"most",
"publications",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "venue"
},
{
"id": 2,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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{
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"token_idxs": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,794
|
simpson_episodes
|
bird:train.json:4287
|
What are the episodes Oscar Cervantes is credited with?
|
SELECT episode_id FROM Credit WHERE person = 'Oscar Cervantes' AND credited = 'true';
|
[
"What",
"are",
"the",
"episodes",
"Oscar",
"Cervantes",
"is",
"credited",
"with",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Oscar Cervantes"
},
{
"id": 1,
"type": "column",
"value": "episode_id"
},
{
"id": 4,
"type": "column",
"value": "credited"
},
{
"id": 0,
"type": "table",
"value": "credit"
},
{
"id": 2,
"type": "column",
"value": "person"
},
{
"id": 5,
"type": "value",
"value": "true"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O",
"O"
] |
12,795
|
world_development_indicators
|
bird:train.json:2230
|
What is the average number of passengers carried via air transport per year by Bulgaria between 1970 to 1980? Indicate the country's system of trade.
|
SELECT AVG(T1.Value), T2.SystemOfTrade FROM Indicators AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.IndicatorName = 'Air transport, passengers carried' AND T1.Year >= 1970 AND T1.Year < 1981 AND T1.CountryName = 'Bulgaria'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"passengers",
"carried",
"via",
"air",
"transport",
"per",
"year",
"by",
"Bulgaria",
"between",
"1970",
"to",
"1980",
"?",
"Indicate",
"the",
"country",
"'s",
"system",
"of",
"trade",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Air transport, passengers carried"
},
{
"id": 0,
"type": "column",
"value": "systemoftrade"
},
{
"id": 5,
"type": "column",
"value": "indicatorname"
},
{
"id": 4,
"type": "column",
"value": "countrycode"
},
{
"id": 10,
"type": "column",
"value": "countryname"
},
{
"id": 1,
"type": "table",
"value": "indicators"
},
{
"id": 11,
"type": "value",
"value": "Bulgaria"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "value"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1970"
},
{
"id": 9,
"type": "value",
"value": "1981"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
24,
25,
26
]
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
22
]
},
{
"entity_id": 3,
"token_idxs": []
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{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5,
6,
7
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},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": [
16
]
},
{
"entity_id": 9,
"token_idxs": [
18
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
14
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
12,796
|
book_publishing_company
|
bird:train.json:174
|
State the royalty percentage for the most year to date sale title within the 20000 range.
|
SELECT MAX(T1.ytd_sales) FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.lorange > 20000 AND T2.hirange < 20000
|
[
"State",
"the",
"royalty",
"percentage",
"for",
"the",
"most",
"year",
"to",
"date",
"sale",
"title",
"within",
"the",
"20000",
"range",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "ytd_sales"
},
{
"id": 1,
"type": "table",
"value": "roysched"
},
{
"id": 3,
"type": "column",
"value": "title_id"
},
{
"id": 4,
"type": "column",
"value": "lorange"
},
{
"id": 6,
"type": "column",
"value": "hirange"
},
{
"id": 0,
"type": "table",
"value": "titles"
},
{
"id": 5,
"type": "value",
"value": "20000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,797
|
chicago_crime
|
bird:train.json:8752
|
What is the FBI description of the crime for report number 23778?
|
SELECT T1.description FROM FBI_Code AS T1 INNER JOIN Crime AS T2 ON T1.fbi_code_no = T2.fbi_code_no WHERE T2.report_no = 23843
|
[
"What",
"is",
"the",
"FBI",
"description",
"of",
"the",
"crime",
"for",
"report",
"number",
"23778",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 5,
"type": "column",
"value": "fbi_code_no"
},
{
"id": 3,
"type": "column",
"value": "report_no"
},
{
"id": 1,
"type": "table",
"value": "fbi_code"
},
{
"id": 2,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "value",
"value": "23843"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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7
]
},
{
"entity_id": 3,
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9
]
},
{
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11
]
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{
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{
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{
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},
{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,798
|
video_games
|
bird:train.json:3408
|
Which game has the most sales in Japan?
|
SELECT T5.game_name FROM region AS T1 INNER JOIN region_sales AS T2 ON T1.id = T2.region_id INNER JOIN game_platform AS T3 ON T2.game_platform_id = T3.id INNER JOIN game_publisher AS T4 ON T3.game_publisher_id = T4.id INNER JOIN game AS T5 ON T4.game_id = T5.id WHERE T1.region_name = 'Japan' ORDER BY T2.num_sales DESC LIMIT 1
|
[
"Which",
"game",
"has",
"the",
"most",
"sales",
"in",
"Japan",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "game_publisher_id"
},
{
"id": 12,
"type": "column",
"value": "game_platform_id"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 8,
"type": "table",
"value": "game_platform"
},
{
"id": 11,
"type": "table",
"value": "region_sales"
},
{
"id": 2,
"type": "column",
"value": "region_name"
},
{
"id": 0,
"type": "column",
"value": "game_name"
},
{
"id": 4,
"type": "column",
"value": "num_sales"
},
{
"id": 13,
"type": "column",
"value": "region_id"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 10,
"type": "table",
"value": "region"
},
{
"id": 3,
"type": "value",
"value": "Japan"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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"token_idxs": []
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},
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,800
|
movielens
|
bird:train.json:2292
|
What is the most distinct rated movie with a running time of 0?
|
SELECT DISTINCT T1.movieid FROM movies AS T1 INNER JOIN u2base AS T2 ON T1.movieid = T2.movieid WHERE T1.runningtime = 0 AND T2.rating = ( SELECT MAX(rating) FROM u2base )
|
[
"What",
"is",
"the",
"most",
"distinct",
"rated",
"movie",
"with",
"a",
"running",
"time",
"of",
"0",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "runningtime"
},
{
"id": 0,
"type": "column",
"value": "movieid"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 2,
"type": "table",
"value": "u2base"
},
{
"id": 5,
"type": "column",
"value": "rating"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,801
|
financial
|
bird:dev.json:95
|
List out the account numbers of clients who are youngest and have highest average salary?
|
SELECT T1.account_id FROM account AS T1 INNER JOIN disp AS T2 ON T1.account_id = T2.account_id INNER JOIN client AS T3 ON T2.client_id = T3.client_id INNER JOIN district AS T4 on T4.district_id = T1.district_id WHERE T2.client_id = ( SELECT client_id FROM client ORDER BY birth_date DESC LIMIT 1) GROUP BY T4.A11, T1.account_id
|
[
"List",
"out",
"the",
"account",
"numbers",
"of",
"clients",
"who",
"are",
"youngest",
"and",
"have",
"highest",
"average",
"salary",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "district_id"
},
{
"id": 1,
"type": "column",
"value": "account_id"
},
{
"id": 8,
"type": "column",
"value": "birth_date"
},
{
"id": 3,
"type": "column",
"value": "client_id"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 6,
"type": "table",
"value": "account"
},
{
"id": 4,
"type": "table",
"value": "client"
},
{
"id": 7,
"type": "table",
"value": "disp"
},
{
"id": 0,
"type": "column",
"value": "a11"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,802
|
synthea
|
bird:train.json:1363
|
The highest Systolic Blood Pressure was observed in which patient? Please give his or her full name.
|
SELECT T1.first, T1.last FROM patients AS T1 INNER JOIN observations AS T2 ON T1.patient = T2.PATIENT WHERE T2.VALUE = ( SELECT MAX(VALUE) FROM observations WHERE description = 'Systolic Blood Pressure' ) LIMIT 1
|
[
"The",
"highest",
"Systolic",
"Blood",
"Pressure",
"was",
"observed",
"in",
"which",
"patient",
"?",
"Please",
"give",
"his",
"or",
"her",
"full",
"name",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "Systolic Blood Pressure"
},
{
"id": 3,
"type": "table",
"value": "observations"
},
{
"id": 6,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "patients"
},
{
"id": 5,
"type": "column",
"value": "patient"
},
{
"id": 0,
"type": "column",
"value": "first"
},
{
"id": 4,
"type": "column",
"value": "value"
},
{
"id": 1,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,803
|
simpson_episodes
|
bird:train.json:4357
|
Among the episodes aired in 2008 with votes ranges from 920 to 950, list their percent.
|
SELECT T2.percent FROM Episode AS T1 INNER JOIN Vote AS T2 ON T2.episode_id = T1.episode_id WHERE SUBSTR(T1.air_date, 1, 4) = '2008' AND T1.votes BETWEEN 950 AND 960;
|
[
"Among",
"the",
"episodes",
"aired",
"in",
"2008",
"with",
"votes",
"ranges",
"from",
"920",
"to",
"950",
",",
"list",
"their",
"percent",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 8,
"type": "column",
"value": "air_date"
},
{
"id": 0,
"type": "column",
"value": "percent"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 5,
"type": "column",
"value": "votes"
},
{
"id": 2,
"type": "table",
"value": "vote"
},
{
"id": 4,
"type": "value",
"value": "2008"
},
{
"id": 6,
"type": "value",
"value": "950"
},
{
"id": 7,
"type": "value",
"value": "960"
},
{
"id": 9,
"type": "value",
"value": "1"
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": [
3
]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,804
|
codebase_comments
|
bird:train.json:680
|
How many XML format does the github address "https://github.com/dogeth/vss2git.git" have?
|
SELECT COUNT(T3.CommentIsXml) FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId INNER JOIN Method AS T3 ON T2.Id = T3.SolutionId WHERE T1.Url = 'https://github.com/dogeth/vss2git.git' AND T3.CommentIsXml = 1
|
[
"How",
"many",
"XML",
"format",
"does",
"the",
"github",
"address",
"\"",
"https://github.com/dogeth/vss2git.git",
"\"",
"have",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "https://github.com/dogeth/vss2git.git"
},
{
"id": 1,
"type": "column",
"value": "commentisxml"
},
{
"id": 5,
"type": "column",
"value": "solutionid"
},
{
"id": 3,
"type": "table",
"value": "solution"
},
{
"id": 0,
"type": "table",
"value": "method"
},
{
"id": 9,
"type": "column",
"value": "repoid"
},
{
"id": 2,
"type": "table",
"value": "repo"
},
{
"id": 6,
"type": "column",
"value": "url"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,805
|
pilot_record
|
spider:train_spider.json:2088
|
What is the joined year of the pilot of the highest rank?
|
SELECT Join_Year FROM pilot ORDER BY Rank ASC LIMIT 1
|
[
"What",
"is",
"the",
"joined",
"year",
"of",
"the",
"pilot",
"of",
"the",
"highest",
"rank",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "join_year"
},
{
"id": 0,
"type": "table",
"value": "pilot"
},
{
"id": 2,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,806
|
authors
|
bird:train.json:3664
|
Calculate the average of authors for each paper from the year of 1990 to 2000.
|
SELECT CAST(COUNT(DISTINCT T2.AuthorId) AS REAL) / COUNT(DISTINCT T1.Title) FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Year BETWEEN 1990 AND 2000
|
[
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"the",
"average",
"of",
"authors",
"for",
"each",
"paper",
"from",
"the",
"year",
"of",
"1990",
"to",
"2000",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "paperauthor"
},
{
"id": 8,
"type": "column",
"value": "authorid"
},
{
"id": 6,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 7,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "1990"
},
{
"id": 4,
"type": "value",
"value": "2000"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
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"token_idxs": [
7
]
},
{
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},
{
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10
]
},
{
"entity_id": 3,
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12
]
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{
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"token_idxs": [
14
]
},
{
"entity_id": 5,
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{
"entity_id": 6,
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},
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"token_idxs": []
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"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
12,807
|
movies_4
|
bird:train.json:508
|
What is the language ID of the movie "Walk the Line"?
|
SELECT T2.language_id FROM movie AS T1 INNER JOIN movie_languages AS T2 ON T1.movie_id = T2.movie_id WHERE T1.title = 'Walk the Line'
|
[
"What",
"is",
"the",
"language",
"ID",
"of",
"the",
"movie",
"\"",
"Walk",
"the",
"Line",
"\"",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "movie_languages"
},
{
"id": 4,
"type": "value",
"value": "Walk the Line"
},
{
"id": 0,
"type": "column",
"value": "language_id"
},
{
"id": 5,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "movie"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
11
]
},
{
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},
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},
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},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
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"token_idxs": []
},
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"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
12,808
|
movie_platform
|
bird:train.json:166
|
What are the top 10 oldest movies and what are the average rating score for each movie? Indicate the name of the director and when the movies were released.
|
SELECT T2.movie_id, AVG(T1.rating_score), T2.director_name, T2.movie_release_year FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id ORDER BY T1.rating_timestamp_utc ASC LIMIT 10
|
[
"What",
"are",
"the",
"top",
"10",
"oldest",
"movies",
"and",
"what",
"are",
"the",
"average",
"rating",
"score",
"for",
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"?",
"Indicate",
"the",
"name",
"of",
"the",
"director",
"and",
"when",
"the",
"movies",
"were",
"released",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 2,
"type": "column",
"value": "movie_release_year"
},
{
"id": 1,
"type": "column",
"value": "director_name"
},
{
"id": 6,
"type": "column",
"value": "rating_score"
},
{
"id": 0,
"type": "column",
"value": "movie_id"
},
{
"id": 3,
"type": "table",
"value": "ratings"
},
{
"id": 4,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
23
]
},
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28,
29
]
},
{
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"token_idxs": [
12
]
},
{
"entity_id": 4,
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27
]
},
{
"entity_id": 5,
"token_idxs": []
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{
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"entity_id": 9,
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"token_idxs": []
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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": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
12,809
|
storm_record
|
spider:train_spider.json:2727
|
What are the names of the storms that affected Denmark?
|
SELECT T3.name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.region_name = 'Denmark'
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"storms",
"that",
"affected",
"Denmark",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "affected_region"
},
{
"id": 2,
"type": "column",
"value": "region_name"
},
{
"id": 7,
"type": "column",
"value": "region_id"
},
{
"id": 6,
"type": "column",
"value": "storm_id"
},
{
"id": 3,
"type": "value",
"value": "Denmark"
},
{
"id": 5,
"type": "table",
"value": "region"
},
{
"id": 1,
"type": "table",
"value": "storm"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
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"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
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{
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{
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{
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{
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{
"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"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-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
12,810
|
government_shift
|
bird:test.json:380
|
Which services are both used by the customer "Hardy Kutch" and are rated as "bad" in a customer interaction? Give me the service details.
|
SELECT DISTINCT t3.service_details FROM customers AS t1 JOIN customers_and_services AS t2 ON t1.customer_id = t2.customer_id JOIN services AS t3 ON t2.service_id = t3.service_id JOIN customer_interactions AS t4 ON t3.service_id = t4.service_id WHERE t1.customer_details = "Hardy Kutch" AND t4.services_and_channels_details = "bad"
|
[
"Which",
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"are",
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"used",
"by",
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"customer",
"\"",
"Hardy",
"Kutch",
"\"",
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"rated",
"as",
"\"",
"bad",
"\"",
"in",
"a",
"customer",
"interaction",
"?",
"Give",
"me",
"the",
"service",
"details",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "services_and_channels_details"
},
{
"id": 9,
"type": "table",
"value": "customers_and_services"
},
{
"id": 1,
"type": "table",
"value": "customer_interactions"
},
{
"id": 4,
"type": "column",
"value": "customer_details"
},
{
"id": 0,
"type": "column",
"value": "service_details"
},
{
"id": 5,
"type": "column",
"value": "Hardy Kutch"
},
{
"id": 10,
"type": "column",
"value": "customer_id"
},
{
"id": 3,
"type": "column",
"value": "service_id"
},
{
"id": 8,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "services"
},
{
"id": 7,
"type": "column",
"value": "bad"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
28
]
},
{
"entity_id": 1,
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22
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},
{
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1
]
},
{
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},
{
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{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
12,811
|
soccer_2016
|
bird:train.json:1914
|
How many times has SR Watson been named 'Man of the Match'?
|
SELECT SUM(CASE WHEN T2.Player_Name = 'SR Watson' THEN 1 ELSE 0 END) FROM `Match` AS T1 INNER JOIN Player AS T2 ON T1.Man_of_the_Match = T2.Player_Id
|
[
"How",
"many",
"times",
"has",
"SR",
"Watson",
"been",
"named",
"'",
"Man",
"of",
"the",
"Match",
"'",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "man_of_the_match"
},
{
"id": 6,
"type": "column",
"value": "player_name"
},
{
"id": 3,
"type": "column",
"value": "player_id"
},
{
"id": 7,
"type": "value",
"value": "SR Watson"
},
{
"id": 1,
"type": "table",
"value": "player"
},
{
"id": 0,
"type": "table",
"value": "Match"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11
]
},
{
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},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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4,
5
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{
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{
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{
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O"
] |
12,812
|
works_cycles
|
bird:train.json:7263
|
Jill ranked which medium-quality class product as the highest, and how long will it take the company to manufacture such a product?
|
SELECT T1.DaysToManufacture FROM Product AS T1 INNER JOIN ProductReview AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Rating = 5 AND T1.Class = 'M' ORDER BY T2.Rating LIMIT 1
|
[
"Jill",
"ranked",
"which",
"medium",
"-",
"quality",
"class",
"product",
"as",
"the",
"highest",
",",
"and",
"how",
"long",
"will",
"it",
"take",
"the",
"company",
"to",
"manufacture",
"such",
"a",
"product",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "daystomanufacture"
},
{
"id": 2,
"type": "table",
"value": "productreview"
},
{
"id": 4,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "product"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 6,
"type": "column",
"value": "class"
},
{
"id": 5,
"type": "value",
"value": "5"
},
{
"id": 7,
"type": "value",
"value": "M"
}
] |
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{
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"token_idxs": [
20,
21
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},
{
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24
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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7
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},
{
"entity_id": 5,
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},
{
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6
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},
{
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},
{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
12,813
|
thrombosis_prediction
|
bird:dev.json:1300
|
What is the disease name of the patient who has the highest level of triglyceride within the normal range?
|
SELECT T1.Diagnosis FROM Examination AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.TG < 200 ORDER BY T2.TG DESC LIMIT 1
|
[
"What",
"is",
"the",
"disease",
"name",
"of",
"the",
"patient",
"who",
"has",
"the",
"highest",
"level",
"of",
"triglyceride",
"within",
"the",
"normal",
"range",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "examination"
},
{
"id": 2,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "column",
"value": "diagnosis"
},
{
"id": 4,
"type": "value",
"value": "200"
},
{
"id": 3,
"type": "column",
"value": "tg"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
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},
{
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{
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"token_idxs": []
},
{
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},
{
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},
{
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{
"entity_id": 10,
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{
"entity_id": 11,
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},
{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,814
|
talkingdata
|
bird:train.json:1104
|
What is the age of the youngest female user of the app?
|
SELECT MIN(age) FROM gender_age WHERE gender = 'F'
|
[
"What",
"is",
"the",
"age",
"of",
"the",
"youngest",
"female",
"user",
"of",
"the",
"app",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 3,
"type": "column",
"value": "age"
},
{
"id": 2,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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9
]
},
{
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3
]
},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,815
|
match_season
|
spider:train_spider.json:1105
|
Return the names of teams that have no match season record.
|
SELECT Name FROM team WHERE Team_id NOT IN (SELECT Team FROM match_season)
|
[
"Return",
"the",
"names",
"of",
"teams",
"that",
"have",
"no",
"match",
"season",
"record",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "match_season"
},
{
"id": 2,
"type": "column",
"value": "team_id"
},
{
"id": 0,
"type": "table",
"value": "team"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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2
]
},
{
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},
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8,
9
]
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{
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4
]
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{
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O"
] |
12,816
|
regional_sales
|
bird:train.json:2610
|
List out the product name of order which has unit cost of 781.22.
|
SELECT T FROM ( SELECT DISTINCT IIF(T1.`Unit Cost` = 781.22, T2.`Product Name`, NULL) AS T FROM `Sales Orders` T1 INNER JOIN Products T2 ON T2.ProductID = T1._ProductID ) WHERE T IS NOT NULL
|
[
"List",
"out",
"the",
"product",
"name",
"of",
"order",
"which",
"has",
"unit",
"cost",
"of",
"781.22",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 3,
"type": "column",
"value": "Product Name"
},
{
"id": 5,
"type": "column",
"value": "_productid"
},
{
"id": 4,
"type": "column",
"value": "productid"
},
{
"id": 6,
"type": "column",
"value": "Unit Cost"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "value",
"value": "781.22"
},
{
"id": 0,
"type": "column",
"value": "t"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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5,
6
]
},
{
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3
]
},
{
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4
]
},
{
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{
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},
{
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9,
10
]
},
{
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12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,817
|
card_games
|
bird:dev.json:516
|
How many cards did Volkan Baǵa illustrated whose foreign language is in French?
|
SELECT COUNT(T3.id) FROM ( SELECT T1.id FROM cards AS T1 INNER JOIN foreign_data AS T2 ON T2.uuid = T1.uuid WHERE T1.artist = 'Volkan Baǵa' AND T2.language = 'French' GROUP BY T1.id ) AS T3
|
[
"How",
"many",
"cards",
"did",
"Volkan",
"Baǵa",
"illustrated",
"whose",
"foreign",
"language",
"is",
"in",
"French",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "foreign_data"
},
{
"id": 5,
"type": "value",
"value": "Volkan Baǵa"
},
{
"id": 6,
"type": "column",
"value": "language"
},
{
"id": 4,
"type": "column",
"value": "artist"
},
{
"id": 7,
"type": "value",
"value": "French"
},
{
"id": 1,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "column",
"value": "uuid"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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2
]
},
{
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8
]
},
{
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},
{
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{
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"token_idxs": [
4,
5
]
},
{
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9
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},
{
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12
]
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{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,819
|
wine_1
|
spider:train_spider.json:6557
|
Find the distinct names of all wines that have prices higher than some wines from John Anthony winery.
|
SELECT DISTINCT Name FROM WINE WHERE Price > (SELECT min(Price) FROM wine WHERE Winery = "John Anthony")
|
[
"Find",
"the",
"distinct",
"names",
"of",
"all",
"wines",
"that",
"have",
"prices",
"higher",
"than",
"some",
"wines",
"from",
"John",
"Anthony",
"winery",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "John Anthony"
},
{
"id": 3,
"type": "column",
"value": "winery"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "wine"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
12,820
|
bike_1
|
spider:train_spider.json:146
|
What are the 3 most common cloud covers in the zip code of 94107?
|
SELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3
|
[
"What",
"are",
"the",
"3",
"most",
"common",
"cloud",
"covers",
"in",
"the",
"zip",
"code",
"of",
"94107",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "cloud_cover"
},
{
"id": 2,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 3,
"type": "value",
"value": "94107"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,821
|
bike_1
|
spider:train_spider.json:194
|
What are all the different start station names for a trip that lasted less than 100?
|
SELECT DISTINCT start_station_name FROM trip WHERE duration < 100
|
[
"What",
"are",
"all",
"the",
"different",
"start",
"station",
"names",
"for",
"a",
"trip",
"that",
"lasted",
"less",
"than",
"100",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "start_station_name"
},
{
"id": 2,
"type": "column",
"value": "duration"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 3,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
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10
]
},
{
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5,
7
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{
"entity_id": 2,
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6
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},
{
"entity_id": 3,
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15
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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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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,822
|
movie_platform
|
bird:train.json:152
|
How many movies directed by Felipe Cazals was realeased on 1976?
|
SELECT COUNT(movie_id) FROM movies WHERE movie_release_year = 1976 AND director_name LIKE 'Felipe Cazals'
|
[
"How",
"many",
"movies",
"directed",
"by",
"Felipe",
"Cazals",
"was",
"realeased",
"on",
"1976",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "movie_release_year"
},
{
"id": 4,
"type": "column",
"value": "director_name"
},
{
"id": 5,
"type": "value",
"value": "Felipe Cazals"
},
{
"id": 1,
"type": "column",
"value": "movie_id"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 3,
"type": "value",
"value": "1976"
}
] |
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{
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},
{
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},
{
"entity_id": 3,
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},
{
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3
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5,
6
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,823
|
movie_1
|
spider:train_spider.json:2460
|
Find the names of all reviewers who have ratings with a NULL value for the date.
|
SELECT DISTINCT name FROM Reviewer AS T1 JOIN Rating AS T2 ON T1.rID = T2.rID WHERE ratingDate = "null"
|
[
"Find",
"the",
"names",
"of",
"all",
"reviewers",
"who",
"have",
"ratings",
"with",
"a",
"NULL",
"value",
"for",
"the",
"date",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "ratingdate"
},
{
"id": 1,
"type": "table",
"value": "reviewer"
},
{
"id": 2,
"type": "table",
"value": "rating"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "null"
},
{
"id": 5,
"type": "column",
"value": "rid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,824
|
professional_basketball
|
bird:train.json:2832
|
What is the average weight of the players who have won the award of Rookie of the year?
|
SELECT AVG(T1.weight) FROM players AS T1 INNER JOIN awards_players AS T2 ON T1.playerID = T2.playerID WHERE T2.award = 'Rookie of the Year'
|
[
"What",
"is",
"the",
"average",
"weight",
"of",
"the",
"players",
"who",
"have",
"won",
"the",
"award",
"of",
"Rookie",
"of",
"the",
"year",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Rookie of the Year"
},
{
"id": 1,
"type": "table",
"value": "awards_players"
},
{
"id": 5,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "players"
},
{
"id": 4,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "column",
"value": "award"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
14,
15,
16,
17
]
},
{
"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-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
12,825
|
cre_Doc_Workflow
|
bird:test.json:2045
|
What is the description for staff role code HR?
|
SELECT staff_role_description FROM Ref_staff_roles WHERE staff_role_code = "HR"
|
[
"What",
"is",
"the",
"description",
"for",
"staff",
"role",
"code",
"HR",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "staff_role_description"
},
{
"id": 0,
"type": "table",
"value": "ref_staff_roles"
},
{
"id": 2,
"type": "column",
"value": "staff_role_code"
},
{
"id": 3,
"type": "column",
"value": "HR"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
12,826
|
game_1
|
spider:train_spider.json:5987
|
Which game type has least number of games?
|
SELECT gtype FROM Video_games GROUP BY gtype ORDER BY count(*) LIMIT 1
|
[
"Which",
"game",
"type",
"has",
"least",
"number",
"of",
"games",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "video_games"
},
{
"id": 1,
"type": "column",
"value": "gtype"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"O"
] |
12,827
|
authors
|
bird:train.json:3551
|
List the paper title and journal ID which were published under the conference name of "International Symposium of Robotics Research".
|
SELECT DISTINCT T2.Title, T2.JournalId FROM Conference AS T1 INNER JOIN Paper AS T2 ON T1.Id = T2.ConferenceId WHERE T1.FullName = 'International Symposium of Robotics Research' AND T2.Year = 2003
|
[
"List",
"the",
"paper",
"title",
"and",
"journal",
"ID",
"which",
"were",
"published",
"under",
"the",
"conference",
"name",
"of",
"\"",
"International",
"Symposium",
"of",
"Robotics",
"Research",
"\"",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "International Symposium of Robotics Research"
},
{
"id": 5,
"type": "column",
"value": "conferenceid"
},
{
"id": 2,
"type": "table",
"value": "conference"
},
{
"id": 1,
"type": "column",
"value": "journalid"
},
{
"id": 6,
"type": "column",
"value": "fullname"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "paper"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2003"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
16,
17,
18,
19,
20
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
12,828
|
wine_1
|
spider:train_spider.json:6595
|
Find the average price of wines that are not produced from Sonoma county.
|
SELECT avg(price) FROM wine WHERE Appelation NOT IN (SELECT T1.Appelation FROM APPELLATIONS AS T1 JOIN WINE AS T2 ON T1.Appelation = T2.Appelation WHERE T1.County = 'Sonoma')
|
[
"Find",
"the",
"average",
"price",
"of",
"wines",
"that",
"are",
"not",
"produced",
"from",
"Sonoma",
"county",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "appellations"
},
{
"id": 2,
"type": "column",
"value": "appelation"
},
{
"id": 4,
"type": "column",
"value": "county"
},
{
"id": 5,
"type": "value",
"value": "Sonoma"
},
{
"id": 1,
"type": "column",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "wine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,829
|
cre_Doc_and_collections
|
bird:test.json:680
|
What is the count of documents owned by Marlin?
|
SELECT count(*) FROM Document_Objects WHERE OWNER = "Marlin";
|
[
"What",
"is",
"the",
"count",
"of",
"documents",
"owned",
"by",
"Marlin",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "document_objects"
},
{
"id": 2,
"type": "column",
"value": "Marlin"
},
{
"id": 1,
"type": "column",
"value": "owner"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
12,830
|
customers_and_invoices
|
spider:train_spider.json:1579
|
How many transaction does each account have? Show the number and account id.
|
SELECT count(*) , account_id FROM Financial_transactions
|
[
"How",
"many",
"transaction",
"does",
"each",
"account",
"have",
"?",
"Show",
"the",
"number",
"and",
"account",
"i",
"d."
] |
[
{
"id": 0,
"type": "table",
"value": "financial_transactions"
},
{
"id": 1,
"type": "column",
"value": "account_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": [
12,
13,
14
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
12,831
|
student_loan
|
bird:train.json:4538
|
Provide the names of the students enlisted in the fire department.
|
SELECT name FROM enlist WHERE organ = 'fire_department'
|
[
"Provide",
"the",
"names",
"of",
"the",
"students",
"enlisted",
"in",
"the",
"fire",
"department",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "fire_department"
},
{
"id": 0,
"type": "table",
"value": "enlist"
},
{
"id": 2,
"type": "column",
"value": "organ"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
12,832
|
hr_1
|
spider:train_spider.json:3405
|
Display the first name and department name for each employee.
|
SELECT T1.first_name , T2.department_name FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id
|
[
"Display",
"the",
"first",
"name",
"and",
"department",
"name",
"for",
"each",
"employee",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "department_name"
},
{
"id": 4,
"type": "column",
"value": "department_id"
},
{
"id": 3,
"type": "table",
"value": "departments"
},
{
"id": 0,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "table",
"value": "employees"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
12,833
|
region_building
|
bird:test.json:321
|
What is the maximum number of stories of buildings not completed in 1980?
|
SELECT max(Number_of_Stories) FROM building WHERE Completed_Year != "1980"
|
[
"What",
"is",
"the",
"maximum",
"number",
"of",
"stories",
"of",
"buildings",
"not",
"completed",
"in",
"1980",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "number_of_stories"
},
{
"id": 1,
"type": "column",
"value": "completed_year"
},
{
"id": 0,
"type": "table",
"value": "building"
},
{
"id": 2,
"type": "column",
"value": "1980"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
12,835
|
performance_attendance
|
spider:train_spider.json:1316
|
Show the locations that have both performances with more than 2000 attendees and performances with less than 1000 attendees.
|
SELECT LOCATION FROM performance WHERE Attendance > 2000 INTERSECT SELECT LOCATION FROM performance WHERE Attendance < 1000
|
[
"Show",
"the",
"locations",
"that",
"have",
"both",
"performances",
"with",
"more",
"than",
"2000",
"attendees",
"and",
"performances",
"with",
"less",
"than",
"1000",
"attendees",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "performance"
},
{
"id": 2,
"type": "column",
"value": "attendance"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 4,
"type": "value",
"value": "1000"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,836
|
wine_1
|
spider:train_spider.json:6536
|
What are the distinct names of wines that have appellations in the North Coast area?
|
SELECT DISTINCT T2.Name FROM APPELLATIONs AS T1 JOIN WINE AS T2 ON T1.Appelation = T2.Appelation WHERE T1.Area = "North Coast"
|
[
"What",
"are",
"the",
"distinct",
"names",
"of",
"wines",
"that",
"have",
"appellations",
"in",
"the",
"North",
"Coast",
"area",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "appellations"
},
{
"id": 4,
"type": "column",
"value": "North Coast"
},
{
"id": 5,
"type": "column",
"value": "appelation"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "wine"
},
{
"id": 3,
"type": "column",
"value": "area"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
12,
13
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
12,837
|
film_rank
|
spider:train_spider.json:4126
|
List all countries of markets in ascending alphabetical order.
|
SELECT Country FROM market ORDER BY Country ASC
|
[
"List",
"all",
"countries",
"of",
"markets",
"in",
"ascending",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "market"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
12,838
|
bakery_1
|
bird:test.json:1564
|
Give the customer id of the customer that made the most purchases, as well as the number of purchases made.
|
SELECT CustomerId , count(*) FROM receipts GROUP BY CustomerId ORDER BY count(*) DESC LIMIT 1
|
[
"Give",
"the",
"customer",
"i",
"d",
"of",
"the",
"customer",
"that",
"made",
"the",
"most",
"purchases",
",",
"as",
"well",
"as",
"the",
"number",
"of",
"purchases",
"made",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "receipts"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
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",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,839
|
address
|
bird:train.json:5141
|
What is the longitude and latitude for the district represented by Grayson Alan?
|
SELECT T1.latitude, T1.longitude FROM zip_data AS T1 INNER JOIN zip_congress AS T2 ON T1.zip_code = T2.zip_code INNER JOIN congress AS T3 ON T2.district = T3.cognress_rep_id WHERE T3.first_name = 'Grayson' AND T3.last_name = 'Alan'
|
[
"What",
"is",
"the",
"longitude",
"and",
"latitude",
"for",
"the",
"district",
"represented",
"by",
"Grayson",
"Alan",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "cognress_rep_id"
},
{
"id": 4,
"type": "table",
"value": "zip_congress"
},
{
"id": 7,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "column",
"value": "longitude"
},
{
"id": 9,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "column",
"value": "latitude"
},
{
"id": 2,
"type": "table",
"value": "congress"
},
{
"id": 3,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "district"
},
{
"id": 11,
"type": "column",
"value": "zip_code"
},
{
"id": 8,
"type": "value",
"value": "Grayson"
},
{
"id": 10,
"type": "value",
"value": "Alan"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
12
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
12,840
|
chinook_1
|
spider:train_spider.json:852
|
Find the cities corresponding to employees who help customers with the postal code 70174.
|
SELECT T2.City FROM CUSTOMER AS T1 JOIN EMPLOYEE AS T2 ON T1.SupportRepId = T2.EmployeeId WHERE T1.PostalCode = "70174"
|
[
"Find",
"the",
"cities",
"corresponding",
"to",
"employees",
"who",
"help",
"customers",
"with",
"the",
"postal",
"code",
"70174",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "supportrepid"
},
{
"id": 3,
"type": "column",
"value": "postalcode"
},
{
"id": 6,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 2,
"type": "table",
"value": "employee"
},
{
"id": 4,
"type": "column",
"value": "70174"
},
{
"id": 0,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O"
] |
12,841
|
boat_1
|
bird:test.json:855
|
Return the unique names of sailors who are older than any sailors whose rating is larger than 7.
|
SELECT DISTINCT name FROM Sailors WHERE age > (SELECT min(age) FROM Sailors WHERE rating > 7);
|
[
"Return",
"the",
"unique",
"names",
"of",
"sailors",
"who",
"are",
"older",
"than",
"any",
"sailors",
"whose",
"rating",
"is",
"larger",
"than",
"7",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "sailors"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 4,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
17
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,842
|
video_games
|
bird:train.json:3450
|
Who is the publisher of the game 2002 FIFA World Cup?
|
SELECT T2.publisher_name FROM game_publisher AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id INNER JOIN game AS T3 ON T1.game_id = T3.id WHERE T3.game_name = '2002 FIFA World Cup'
|
[
"Who",
"is",
"the",
"publisher",
"of",
"the",
"game",
"2002",
"FIFA",
"World",
"Cup",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "2002 FIFA World Cup"
},
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 4,
"type": "table",
"value": "game_publisher"
},
{
"id": 8,
"type": "column",
"value": "publisher_id"
},
{
"id": 2,
"type": "column",
"value": "game_name"
},
{
"id": 5,
"type": "table",
"value": "publisher"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"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-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
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