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12,524
|
authors
|
bird:train.json:3552
|
Name the title, year and keyword of the paper which were written by the author ID of 661002 with the affiliation of "Scientific Computing and Imaging Institute, University of Utah, UT 84112, USA" organization.
|
SELECT T2.Title, T2.Year, T2.Keyword FROM PaperAuthor AS T1 INNER JOIN Paper AS T2 ON T1.PaperId = T2.Id WHERE T1.AuthorId = 661002 AND T1.Affiliation = 'Scientific Computing and Imaging Institute, University of Utah, UT 84112, USA'
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"value": "id"
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12,525
|
pilot_1
|
bird:test.json:1116
|
Return the name of the youngest pilot to fly Piper Cub.
|
SELECT pilot_name FROM pilotskills WHERE plane_name = 'Piper Cub' ORDER BY age LIMIT 1
|
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"value": "Piper Cub"
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12,526
|
mondial_geo
|
bird:train.json:8328
|
Calculate the percentage of population in Edmonton city to the population of its province.
|
SELECT CAST(T1.Population AS REAL) * 100 / T2.Population FROM city AS T1 INNER JOIN province AS T2 ON T1.Province = T2.Name WHERE T1.Name = 'Edmonton'
|
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"type": "column",
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"type": "value",
"value": "100"
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"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,527
|
shipping
|
bird:train.json:5628
|
Among all shipments placed by Sunguard Window Tinting & Truck Accessories in 2017, identify the percentage of shipments whose weight exceeded 10,000 pounds.
|
SELECT CAST(SUM(CASE WHEN T1.weight >= 10000 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id WHERE T2.cust_name = 'Sunguard Window Tinting & Truck Accessories' AND STRFTIME('%Y', T1.ship_date) = '2017'
|
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"value": "1"
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"O",
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"O",
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"O",
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"O",
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] |
12,528
|
thrombosis_prediction
|
bird:dev.json:1174
|
What is the average age of patients as of year 1999 examined in the laboratory for the October of the year 1991?
|
SELECT AVG('1999' - STRFTIME('%Y', T2.Birthday)) FROM Laboratory AS T1 INNER JOIN Patient AS T2 ON T1.ID = T2.ID WHERE T1.Date BETWEEN '1991-10-01' AND '1991-10-30'
|
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"B-TABLE",
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"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,529
|
student_loan
|
bird:train.json:4507
|
What is the percentage difference between month 0 absence and month 9 absence?
|
SELECT CAST(((SUM(IIF(month = 0, 1, 0)) - SUM(IIF(month = 9, 1, 0)))) AS REAL) * 100 / SUM(IIF(month = 0, 1, 0)) FROM longest_absense_from_school
|
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"type": "value",
"value": "0"
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{
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"value": "9"
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"O",
"O",
"B-VALUE",
"O",
"O"
] |
12,530
|
book_1
|
bird:test.json:576
|
Give the title of book by George Orwell that has the lowest saleprice.
|
SELECT T1.title FROM Book AS T1 JOIN Author_book AS T2 ON T1.isbn = T2.isbn JOIN Author AS T3 ON T2.Author = T3.idAuthor WHERE T3.name = "George Orwell" ORDER BY T1.saleprice LIMIT 1
|
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"type": "column",
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] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,531
|
apartment_rentals
|
spider:train_spider.json:1212
|
What is the average number of rooms of apartments with type code "Studio"?
|
SELECT avg(room_count) FROM Apartments WHERE apt_type_code = "Studio"
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"rooms",
"of",
"apartments",
"with",
"type",
"code",
"\"",
"Studio",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "apt_type_code"
},
{
"id": 0,
"type": "table",
"value": "apartments"
},
{
"id": 3,
"type": "column",
"value": "room_count"
},
{
"id": 2,
"type": "column",
"value": "Studio"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
12,532
|
hr_1
|
spider:train_spider.json:3491
|
display the employee ID and job name for all those jobs in department 80.
|
SELECT T1.employee_id , T2.job_title FROM employees AS T1 JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.department_id = 80
|
[
"display",
"the",
"employee",
"ID",
"and",
"job",
"name",
"for",
"all",
"those",
"jobs",
"in",
"department",
"80",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "column",
"value": "employee_id"
},
{
"id": 1,
"type": "column",
"value": "job_title"
},
{
"id": 2,
"type": "table",
"value": "employees"
},
{
"id": 6,
"type": "column",
"value": "job_id"
},
{
"id": 3,
"type": "table",
"value": "jobs"
},
{
"id": 5,
"type": "value",
"value": "80"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
12,533
|
products_gen_characteristics
|
spider:train_spider.json:5568
|
Find the name of the products that have the color description "red" and have the characteristic name "fast".
|
SELECT product_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id JOIN ref_colors AS t4 ON t1.color_code = t4.color_code WHERE t4.color_description = "red" AND t3.characteristic_name = "fast"
|
[
"Find",
"the",
"name",
"of",
"the",
"products",
"that",
"have",
"the",
"color",
"description",
"\"",
"red",
"\"",
"and",
"have",
"the",
"characteristic",
"name",
"\"",
"fast",
"\"",
"."
] |
[
{
"id": 9,
"type": "table",
"value": "product_characteristics"
},
{
"id": 6,
"type": "column",
"value": "characteristic_name"
},
{
"id": 4,
"type": "column",
"value": "color_description"
},
{
"id": 10,
"type": "column",
"value": "characteristic_id"
},
{
"id": 2,
"type": "table",
"value": "characteristics"
},
{
"id": 0,
"type": "column",
"value": "product_name"
},
{
"id": 1,
"type": "table",
"value": "ref_colors"
},
{
"id": 3,
"type": "column",
"value": "color_code"
},
{
"id": 11,
"type": "column",
"value": "product_id"
},
{
"id": 8,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "column",
"value": "fast"
},
{
"id": 5,
"type": "column",
"value": "red"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
17
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
18
]
},
{
"entity_id": 7,
"token_idxs": [
20
]
},
{
"entity_id": 8,
"token_idxs": [
5
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
12,534
|
film_rank
|
spider:train_spider.json:4131
|
What are the titles of films and corresponding types of market estimations?
|
SELECT T1.Title , T2.Type FROM film AS T1 JOIN film_market_estimation AS T2 ON T1.Film_ID = T2.Film_ID
|
[
"What",
"are",
"the",
"titles",
"of",
"films",
"and",
"corresponding",
"types",
"of",
"market",
"estimations",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "film_market_estimation"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "column",
"value": "type"
},
{
"id": 2,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
12,535
|
e_government
|
spider:train_spider.json:6347
|
What are the last names of individuals who have been contact individuals for an organization?
|
SELECT DISTINCT t1.individual_last_name FROM individuals AS t1 JOIN organization_contact_individuals AS t2 ON t1.individual_id = t2.individual_id
|
[
"What",
"are",
"the",
"last",
"names",
"of",
"individuals",
"who",
"have",
"been",
"contact",
"individuals",
"for",
"an",
"organization",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "organization_contact_individuals"
},
{
"id": 0,
"type": "column",
"value": "individual_last_name"
},
{
"id": 3,
"type": "column",
"value": "individual_id"
},
{
"id": 1,
"type": "table",
"value": "individuals"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
12,536
|
movielens
|
bird:train.json:2294
|
Which directors with the best quality directed the most films?
|
SELECT T1.directorid FROM directors AS T1 INNER JOIN movies2directors AS T2 ON T1.directorid = T2.directorid WHERE T1.d_quality = 5 GROUP BY T1.directorid ORDER BY COUNT(T2.movieid) DESC LIMIT 1
|
[
"Which",
"directors",
"with",
"the",
"best",
"quality",
"directed",
"the",
"most",
"films",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "movies2directors"
},
{
"id": 0,
"type": "column",
"value": "directorid"
},
{
"id": 1,
"type": "table",
"value": "directors"
},
{
"id": 3,
"type": "column",
"value": "d_quality"
},
{
"id": 5,
"type": "column",
"value": "movieid"
},
{
"id": 4,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,537
|
chinook_1
|
spider:train_spider.json:841
|
How many tracks belong to rock genre?
|
SELECT COUNT(*) FROM GENRE AS T1 JOIN TRACK AS T2 ON T1.GenreId = T2.GenreId WHERE T1.Name = "Rock"
|
[
"How",
"many",
"tracks",
"belong",
"to",
"rock",
"genre",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "genreid"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 1,
"type": "table",
"value": "track"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "Rock"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"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",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
12,538
|
book_press
|
bird:test.json:1998
|
Which authors publish books in both "MM" and "LT" series? Give me the author names.
|
SELECT t1.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id WHERE t2.book_series = 'MM' INTERSECT SELECT t1.name FROM author AS t1 JOIN book AS t2 ON t1.author_id = t2.author_id WHERE t2.book_series = 'LT'
|
[
"Which",
"authors",
"publish",
"books",
"in",
"both",
"\"",
"MM",
"\"",
"and",
"\"",
"LT",
"\"",
"series",
"?",
"Give",
"me",
"the",
"author",
"names",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "book_series"
},
{
"id": 6,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "book"
},
{
"id": 4,
"type": "value",
"value": "MM"
},
{
"id": 5,
"type": "value",
"value": "LT"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"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-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
12,539
|
book_1
|
bird:test.json:565
|
List all book titles which have sale prices higher than the average.
|
SELECT title FROM book WHERE saleprice > (SELECT avg(saleprice) FROM book)
|
[
"List",
"all",
"book",
"titles",
"which",
"have",
"sale",
"prices",
"higher",
"than",
"the",
"average",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "saleprice"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,540
|
sports_competition
|
spider:train_spider.json:3356
|
What are the names and players of all the clubs?
|
SELECT T1.name , T2.Player_id FROM club AS T1 JOIN player AS T2 ON T1.Club_ID = T2.Club_ID
|
[
"What",
"are",
"the",
"names",
"and",
"players",
"of",
"all",
"the",
"clubs",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "player_id"
},
{
"id": 4,
"type": "column",
"value": "club_id"
},
{
"id": 3,
"type": "table",
"value": "player"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,541
|
customers_and_addresses
|
spider:train_spider.json:6135
|
Find the name of customers who did not pay with Cash.
|
SELECT customer_name FROM customers WHERE payment_method != 'Cash'
|
[
"Find",
"the",
"name",
"of",
"customers",
"who",
"did",
"not",
"pay",
"with",
"Cash",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "payment_method"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "Cash"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,542
|
chicago_crime
|
bird:train.json:8690
|
List the name and population of the communities where more than average solicit for prostitutes were reported.
|
SELECT T2.community_area_name, T2.population FROM Crime AS T1 INNER JOIN Community_Area AS T2 ON T2.community_area_no = T1.community_area_no INNER JOIN IUCR AS T3 ON T3.iucr_no = T1.iucr_no WHERE T3.iucr_no = ( SELECT iucr_no FROM IUCR WHERE secondary_description = 'SOLICIT FOR PROSTITUTE' GROUP BY iucr_no HAVING COUNT(iucr_no) > ( SELECT SUM(CASE WHEN secondary_description = 'SOLICIT FOR PROSTITUTE' THEN 1.0 ELSE 0 END) / COUNT(iucr_no) AS average FROM IUCR ) )
|
[
"List",
"the",
"name",
"and",
"population",
"of",
"the",
"communities",
"where",
"more",
"than",
"average",
"solicit",
"for",
"prostitutes",
"were",
"reported",
"."
] |
[
{
"id": 8,
"type": "value",
"value": "SOLICIT FOR PROSTITUTE"
},
{
"id": 7,
"type": "column",
"value": "secondary_description"
},
{
"id": 0,
"type": "column",
"value": "community_area_name"
},
{
"id": 6,
"type": "column",
"value": "community_area_no"
},
{
"id": 5,
"type": "table",
"value": "community_area"
},
{
"id": 1,
"type": "column",
"value": "population"
},
{
"id": 3,
"type": "column",
"value": "iucr_no"
},
{
"id": 4,
"type": "table",
"value": "crime"
},
{
"id": 2,
"type": "table",
"value": "iucr"
},
{
"id": 10,
"type": "value",
"value": "1.0"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
12,544
|
disney
|
bird:train.json:4733
|
Name actors who voiced more than five Disney characters.
|
SELECT 'voice-actor' FROM `voice-actors` GROUP BY 'voice-actor' HAVING COUNT(movie) > 5
|
[
"Name",
"actors",
"who",
"voiced",
"more",
"than",
"five",
"Disney",
"characters",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "voice-actors"
},
{
"id": 1,
"type": "value",
"value": "voice-actor"
},
{
"id": 3,
"type": "column",
"value": "movie"
},
{
"id": 2,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,545
|
cookbook
|
bird:train.json:8912
|
Among the recipes from The California Tree Fruit Agreement, calculate the percentage of sodium-free recipes.
|
SELECT CAST(SUM(CASE WHEN T2.sodium < 5 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Recipe AS T1 INNER JOIN Nutrition AS T2 ON T1.recipe_id = T2.recipe_id WHERE T1.source = 'The California Tree Fruit Agreement'
|
[
"Among",
"the",
"recipes",
"from",
"The",
"California",
"Tree",
"Fruit",
"Agreement",
",",
"calculate",
"the",
"percentage",
"of",
"sodium",
"-",
"free",
"recipes",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "The California Tree Fruit Agreement"
},
{
"id": 1,
"type": "table",
"value": "nutrition"
},
{
"id": 4,
"type": "column",
"value": "recipe_id"
},
{
"id": 0,
"type": "table",
"value": "recipe"
},
{
"id": 2,
"type": "column",
"value": "source"
},
{
"id": 8,
"type": "column",
"value": "sodium"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15,
16
]
},
{
"entity_id": 3,
"token_idxs": [
4,
5,
6,
7,
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": [
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
12,546
|
pilot_record
|
spider:train_spider.json:2083
|
How many pilots are there?
|
SELECT count(*) FROM pilot
|
[
"How",
"many",
"pilots",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pilot"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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"
] |
12,548
|
car_road_race
|
bird:test.json:1335
|
What is the age of the driver who raced in the most races?
|
SELECT T1.Age FROM driver AS T1 JOIN race AS T2 ON T1.Driver_ID = T2.Driver_ID GROUP BY T1.Driver_ID ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"age",
"of",
"the",
"driver",
"who",
"raced",
"in",
"the",
"most",
"races",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "driver_id"
},
{
"id": 2,
"type": "table",
"value": "driver"
},
{
"id": 3,
"type": "table",
"value": "race"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
12,549
|
product_catalog
|
spider:train_spider.json:319
|
What is the level name of the cheapest catalog (in USD)?
|
SELECT t2.catalog_level_name FROM catalog_contents AS t1 JOIN catalog_structure AS t2 ON t1.catalog_level_number = t2.catalog_level_number ORDER BY t1.price_in_dollars LIMIT 1
|
[
"What",
"is",
"the",
"level",
"name",
"of",
"the",
"cheapest",
"catalog",
"(",
"in",
"USD",
")",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "catalog_level_number"
},
{
"id": 0,
"type": "column",
"value": "catalog_level_name"
},
{
"id": 2,
"type": "table",
"value": "catalog_structure"
},
{
"id": 1,
"type": "table",
"value": "catalog_contents"
},
{
"id": 3,
"type": "column",
"value": "price_in_dollars"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
12,550
|
hospital_1
|
spider:train_spider.json:3993
|
How many patients are not using Procrastin-X as medication?
|
SELECT count(*) FROM patient WHERE SSN NOT IN ( SELECT T1.patient FROM Prescribes AS T1 JOIN Medication AS T2 ON T1.Medication = T2.Code WHERE T2.name = 'Procrastin-X' )
|
[
"How",
"many",
"patients",
"are",
"not",
"using",
"Procrastin",
"-",
"X",
"as",
"medication",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Procrastin-X"
},
{
"id": 3,
"type": "table",
"value": "prescribes"
},
{
"id": 4,
"type": "table",
"value": "medication"
},
{
"id": 7,
"type": "column",
"value": "medication"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 2,
"type": "column",
"value": "patient"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "code"
},
{
"id": 1,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O"
] |
12,551
|
car_road_race
|
bird:test.json:1337
|
What are the names and ages of drivers who raced in two or more races?
|
SELECT T1.Driver_Name , T1.Age FROM driver AS T1 JOIN race AS T2 ON T1.Driver_ID = T2.Driver_ID GROUP BY T1.Driver_ID HAVING COUNT(*) >= 2
|
[
"What",
"are",
"the",
"names",
"and",
"ages",
"of",
"drivers",
"who",
"raced",
"in",
"two",
"or",
"more",
"races",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "driver_name"
},
{
"id": 0,
"type": "column",
"value": "driver_id"
},
{
"id": 3,
"type": "table",
"value": "driver"
},
{
"id": 4,
"type": "table",
"value": "race"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,552
|
art_1
|
bird:test.json:1250
|
What are the titles of paintings that are created after 1910 and whose medium is oil?
|
SELECT title FROM paintings WHERE YEAR > 1910 AND medium = "oil"
|
[
"What",
"are",
"the",
"titles",
"of",
"paintings",
"that",
"are",
"created",
"after",
"1910",
"and",
"whose",
"medium",
"is",
"oil",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paintings"
},
{
"id": 4,
"type": "column",
"value": "medium"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "1910"
},
{
"id": 5,
"type": "column",
"value": "oil"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
12,553
|
store_1
|
spider:train_spider.json:548
|
What are the top 10 customers' first and last names with the highest gross sales, and also what are the sales?
|
SELECT T1.first_name , T1.last_name , SUM(T2.total) FROM customers AS T1 JOIN invoices AS T2 ON T2.customer_id = T1.id GROUP BY T1.id ORDER BY SUM(T2.total) DESC LIMIT 10;
|
[
"What",
"are",
"the",
"top",
"10",
"customers",
"'",
"first",
"and",
"last",
"names",
"with",
"the",
"highest",
"gross",
"sales",
",",
"and",
"also",
"what",
"are",
"the",
"sales",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "table",
"value": "invoices"
},
{
"id": 5,
"type": "column",
"value": "total"
},
{
"id": 0,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"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-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,554
|
menu
|
bird:train.json:5520
|
What is the highest price of dishes with menu item ID 1 to 5?
|
SELECT T2.price FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id WHERE T2.id BETWEEN 1 AND 5 ORDER BY T2.price DESC LIMIT 1
|
[
"What",
"is",
"the",
"highest",
"price",
"of",
"dishes",
"with",
"menu",
"item",
"ID",
"1",
"to",
"5",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "menuitem"
},
{
"id": 6,
"type": "column",
"value": "dish_id"
},
{
"id": 0,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "dish"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"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-TABLE",
"I-TABLE",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
12,555
|
chinook_1
|
spider:train_spider.json:859
|
Find the first names of all customers that live in Brazil and have an invoice.
|
SELECT DISTINCT T1.FirstName FROM CUSTOMER AS T1 JOIN INVOICE AS T2 ON T1.CustomerId = T2.CustomerId WHERE T1.country = "Brazil"
|
[
"Find",
"the",
"first",
"names",
"of",
"all",
"customers",
"that",
"live",
"in",
"Brazil",
"and",
"have",
"an",
"invoice",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "column",
"value": "firstname"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 2,
"type": "table",
"value": "invoice"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "Brazil"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,556
|
regional_sales
|
bird:train.json:2700
|
How many sales teams are there in the Midwest?
|
SELECT SUM(CASE WHEN Region = 'Midwest' THEN 1 ELSE 0 END) FROM `Sales Team`
|
[
"How",
"many",
"sales",
"teams",
"are",
"there",
"in",
"the",
"Midwest",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "Sales Team"
},
{
"id": 4,
"type": "value",
"value": "Midwest"
},
{
"id": 3,
"type": "column",
"value": "region"
},
{
"id": 1,
"type": "value",
"value": "0"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,557
|
restaurant
|
bird:train.json:1700
|
Please list all of the restaurants that serve European food.
|
SELECT label FROM generalinfo WHERE food_type = 'european'
|
[
"Please",
"list",
"all",
"of",
"the",
"restaurants",
"that",
"serve",
"European",
"food",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "column",
"value": "food_type"
},
{
"id": 3,
"type": "value",
"value": "european"
},
{
"id": 1,
"type": "column",
"value": "label"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,558
|
inn_1
|
spider:train_spider.json:2634
|
Find the name of rooms whose price is higher than the average price.
|
SELECT roomName FROM Rooms WHERE basePrice > ( SELECT avg(basePrice) FROM Rooms );
|
[
"Find",
"the",
"name",
"of",
"rooms",
"whose",
"price",
"is",
"higher",
"than",
"the",
"average",
"price",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "baseprice"
},
{
"id": 1,
"type": "column",
"value": "roomname"
},
{
"id": 0,
"type": "table",
"value": "rooms"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,559
|
ice_hockey_draft
|
bird:train.json:6968
|
How many players were born in 1982 and have a height above 182cm?
|
SELECT COUNT(T2.ELITEID) FROM height_info AS T1 INNER JOIN PlayerInfo AS T2 ON T1.height_id = T2.height WHERE T1.height_in_cm > 182 AND strftime('%Y', T2.birthdate) = '1982'
|
[
"How",
"many",
"players",
"were",
"born",
"in",
"1982",
"and",
"have",
"a",
"height",
"above",
"182",
"cm",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "height_in_cm"
},
{
"id": 0,
"type": "table",
"value": "height_info"
},
{
"id": 1,
"type": "table",
"value": "playerinfo"
},
{
"id": 3,
"type": "column",
"value": "height_id"
},
{
"id": 9,
"type": "column",
"value": "birthdate"
},
{
"id": 2,
"type": "column",
"value": "eliteid"
},
{
"id": 4,
"type": "column",
"value": "height"
},
{
"id": 7,
"type": "value",
"value": "1982"
},
{
"id": 6,
"type": "value",
"value": "182"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
12,560
|
address_1
|
bird:test.json:771
|
Show names for all cities in state PA.
|
SELECT city_name FROM City WHERE state = "PA"
|
[
"Show",
"names",
"for",
"all",
"cities",
"in",
"state",
"PA",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "city_name"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 3,
"type": "column",
"value": "PA"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
12,561
|
tracking_software_problems
|
spider:train_spider.json:5360
|
List the first and last names of all distinct staff members who are assigned to the problem whose id is 1.
|
SELECT DISTINCT staff_first_name , staff_last_name FROM staff AS T1 JOIN problem_log AS T2 ON T1.staff_id = T2.assigned_to_staff_id WHERE T2.problem_id = 1
|
[
"List",
"the",
"first",
"and",
"last",
"names",
"of",
"all",
"distinct",
"staff",
"members",
"who",
"are",
"assigned",
"to",
"the",
"problem",
"whose",
"i",
"d",
"is",
"1",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "assigned_to_staff_id"
},
{
"id": 0,
"type": "column",
"value": "staff_first_name"
},
{
"id": 1,
"type": "column",
"value": "staff_last_name"
},
{
"id": 3,
"type": "table",
"value": "problem_log"
},
{
"id": 4,
"type": "column",
"value": "problem_id"
},
{
"id": 6,
"type": "column",
"value": "staff_id"
},
{
"id": 2,
"type": "table",
"value": "staff"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
21
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13,
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,562
|
food_inspection_2
|
bird:train.json:6219
|
Where does the employee named "Standard Murray" live?
|
SELECT address, city, state FROM employee WHERE first_name = 'Standard' AND last_name = 'Murray'
|
[
"Where",
"does",
"the",
"employee",
"named",
"\"",
"Standard",
"Murray",
"\"",
"live",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 5,
"type": "value",
"value": "Standard"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 7,
"type": "value",
"value": "Murray"
},
{
"id": 3,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"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": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O"
] |
12,563
|
customers_and_addresses
|
spider:train_spider.json:6115
|
What is the total quantity of products purchased by "Rodrick Heaney"?
|
SELECT sum(t3.order_quantity) FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id WHERE t1.customer_name = "Rodrick Heaney"
|
[
"What",
"is",
"the",
"total",
"quantity",
"of",
"products",
"purchased",
"by",
"\"",
"Rodrick",
"Heaney",
"\"",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "customer_orders"
},
{
"id": 2,
"type": "column",
"value": "Rodrick Heaney"
},
{
"id": 3,
"type": "column",
"value": "order_quantity"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "order_items"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "order_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
12,564
|
movie_platform
|
bird:train.json:86
|
Which of the films released in 2006 was the most popular among Mubi users?
|
SELECT movie_title FROM movies WHERE movie_release_year = 2006 ORDER BY movie_popularity DESC LIMIT 1
|
[
"Which",
"of",
"the",
"films",
"released",
"in",
"2006",
"was",
"the",
"most",
"popular",
"among",
"Mubi",
"users",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "movie_release_year"
},
{
"id": 4,
"type": "column",
"value": "movie_popularity"
},
{
"id": 1,
"type": "column",
"value": "movie_title"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 3,
"type": "value",
"value": "2006"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"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": []
},
{
"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",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
12,565
|
customers_and_orders
|
bird:test.json:281
|
What is the payment method and customer number for customer named Jeromy?
|
SELECT payment_method_code , customer_number FROM Customers WHERE customer_name = "Jeromy"
|
[
"What",
"is",
"the",
"payment",
"method",
"and",
"customer",
"number",
"for",
"customer",
"named",
"Jeromy",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "payment_method_code"
},
{
"id": 2,
"type": "column",
"value": "customer_number"
},
{
"id": 3,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "Jeromy"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
12,566
|
bakery_1
|
bird:test.json:1547
|
Find all receipts which either has the earliest date or has a good with price above 10.
|
SELECT T1.Receipt FROM items AS T1 JOIN goods AS T2 ON T1.item = T2.id WHERE T2.price > 10 UNION SELECT ReceiptNumber FROM receipts WHERE date = (SELECT date FROM receipts ORDER BY date LIMIT 1)
|
[
"Find",
"all",
"receipts",
"which",
"either",
"has",
"the",
"earliest",
"date",
"or",
"has",
"a",
"good",
"with",
"price",
"above",
"10",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "receiptnumber"
},
{
"id": 0,
"type": "table",
"value": "receipts"
},
{
"id": 1,
"type": "column",
"value": "receipt"
},
{
"id": 2,
"type": "table",
"value": "items"
},
{
"id": 3,
"type": "table",
"value": "goods"
},
{
"id": 4,
"type": "column",
"value": "price"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 8,
"type": "column",
"value": "item"
},
{
"id": 5,
"type": "value",
"value": "10"
},
{
"id": 9,
"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": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
0
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,567
|
tracking_grants_for_research
|
spider:train_spider.json:4384
|
List the project details of the projects launched by the organisation
|
SELECT project_details FROM Projects WHERE organisation_id IN ( SELECT organisation_id FROM Projects GROUP BY organisation_id ORDER BY count(*) DESC LIMIT 1 )
|
[
"List",
"the",
"project",
"details",
"of",
"the",
"projects",
"launched",
"by",
"the",
"organisation"
] |
[
{
"id": 1,
"type": "column",
"value": "project_details"
},
{
"id": 2,
"type": "column",
"value": "organisation_id"
},
{
"id": 0,
"type": "table",
"value": "projects"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN"
] |
12,568
|
movie_platform
|
bird:train.json:136
|
Give the percentage of subscribers who rated who rated the movie "G.I. Jane".
|
SELECT CAST(SUM(CASE WHEN T3.user_subscriber = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM ratings AS T1 INNER JOIN movies AS T2 ON T1.movie_id = T2.movie_id INNER JOIN lists_users AS T3 ON T1.user_id = T3.user_id WHERE T2.movie_title = 'G.I. Jane'
|
[
"Give",
"the",
"percentage",
"of",
"subscribers",
"who",
"rated",
"who",
"rated",
"the",
"movie",
"\"",
"G.I.",
"Jane",
"\"",
"."
] |
[
{
"id": 10,
"type": "column",
"value": "user_subscriber"
},
{
"id": 0,
"type": "table",
"value": "lists_users"
},
{
"id": 1,
"type": "column",
"value": "movie_title"
},
{
"id": 2,
"type": "value",
"value": "G.I. Jane"
},
{
"id": 7,
"type": "column",
"value": "movie_id"
},
{
"id": 3,
"type": "table",
"value": "ratings"
},
{
"id": 5,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "table",
"value": "movies"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
4
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,569
|
ice_hockey_draft
|
bird:train.json:6972
|
List the names of all players in team Avangard Omsk in season 2000-2001.
|
SELECT DISTINCT T2.PlayerName FROM SeasonStatus AS T1 INNER JOIN PlayerInfo AS T2 ON T1.ELITEID = T2.ELITEID WHERE T1.SEASON = '2000-2001' AND T1.TEAM = 'Avangard Omsk'
|
[
"List",
"the",
"names",
"of",
"all",
"players",
"in",
"team",
"Avangard",
"Omsk",
"in",
"season",
"2000",
"-",
"2001",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "Avangard Omsk"
},
{
"id": 1,
"type": "table",
"value": "seasonstatus"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 2,
"type": "table",
"value": "playerinfo"
},
{
"id": 5,
"type": "value",
"value": "2000-2001"
},
{
"id": 3,
"type": "column",
"value": "eliteid"
},
{
"id": 4,
"type": "column",
"value": "season"
},
{
"id": 6,
"type": "column",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
12,
13,
14
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
8,
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",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
12,570
|
bike_1
|
spider:train_spider.json:125
|
From the trip record, find the number of unique bikes.
|
SELECT count(DISTINCT bike_id) FROM trip
|
[
"From",
"the",
"trip",
"record",
",",
"find",
"the",
"number",
"of",
"unique",
"bikes",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "bike_id"
},
{
"id": 0,
"type": "table",
"value": "trip"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,571
|
department_store
|
spider:train_spider.json:4759
|
Return the name and gender of the staff who was assigned in 2016.
|
SELECT T1.staff_name , T1.staff_gender FROM staff AS T1 JOIN staff_department_assignments AS T2 ON T1.staff_id = T2.staff_id WHERE T2.date_assigned_from LIKE "2016%"
|
[
"Return",
"the",
"name",
"and",
"gender",
"of",
"the",
"staff",
"who",
"was",
"assigned",
"in",
"2016",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "staff_department_assignments"
},
{
"id": 4,
"type": "column",
"value": "date_assigned_from"
},
{
"id": 1,
"type": "column",
"value": "staff_gender"
},
{
"id": 0,
"type": "column",
"value": "staff_name"
},
{
"id": 6,
"type": "column",
"value": "staff_id"
},
{
"id": 2,
"type": "table",
"value": "staff"
},
{
"id": 5,
"type": "column",
"value": "2016%"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
12,572
|
talkingdata
|
bird:train.json:1200
|
Among the users who use SUGAR, calculate the percentage of those who are above 20 years old.
|
SELECT SUM(IIF(T1.age > 20, 1, 0)) / COUNT(T1.device_id) AS per FROM gender_age AS T1 INNER JOIN phone_brand_device_model2 AS T2 ON T1.device_id = T2.device_id WHERE T2.phone_brand = 'SUGAR'
|
[
"Among",
"the",
"users",
"who",
"use",
"SUGAR",
",",
"calculate",
"the",
"percentage",
"of",
"those",
"who",
"are",
"above",
"20",
"years",
"old",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 2,
"type": "column",
"value": "phone_brand"
},
{
"id": 0,
"type": "table",
"value": "gender_age"
},
{
"id": 4,
"type": "column",
"value": "device_id"
},
{
"id": 3,
"type": "value",
"value": "SUGAR"
},
{
"id": 7,
"type": "column",
"value": "age"
},
{
"id": 8,
"type": "value",
"value": "20"
},
{
"id": 5,
"type": "value",
"value": "1"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"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": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,573
|
food_inspection_2
|
bird:train.json:6121
|
After Azha Restaurant Inc. passed the inspection on 2010/1/21, when was the follow-up inspection done?
|
SELECT T1.followup_to FROM inspection AS T1 INNER JOIN establishment AS T2 ON T1.license_no = T2.license_no WHERE T2.dba_name = 'Azha Restaurant Inc.' AND T1.results = 'Pass' AND T1.inspection_date = '2010-01-21'
|
[
"After",
"Azha",
"Restaurant",
"Inc.",
"passed",
"the",
"inspection",
"on",
"2010/1/21",
",",
"when",
"was",
"the",
"follow",
"-",
"up",
"inspection",
"done",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Azha Restaurant Inc."
},
{
"id": 8,
"type": "column",
"value": "inspection_date"
},
{
"id": 2,
"type": "table",
"value": "establishment"
},
{
"id": 0,
"type": "column",
"value": "followup_to"
},
{
"id": 1,
"type": "table",
"value": "inspection"
},
{
"id": 3,
"type": "column",
"value": "license_no"
},
{
"id": 9,
"type": "value",
"value": "2010-01-21"
},
{
"id": 4,
"type": "column",
"value": "dba_name"
},
{
"id": 6,
"type": "column",
"value": "results"
},
{
"id": 7,
"type": "value",
"value": "Pass"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
1,
3
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": [
17
]
},
{
"entity_id": 9,
"token_idxs": [
8
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 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",
"B-COLUMN",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"O"
] |
12,574
|
department_store
|
spider:train_spider.json:4786
|
What are the distinct names of products purchased by at least two different customers?
|
SELECT DISTINCT T3.product_name FROM customer_orders AS T1 JOIN order_items AS T2 ON T1.order_id = T2.order_id JOIN products AS T3 ON T2.product_id = T3.product_id GROUP BY T3.product_id HAVING COUNT (DISTINCT T1.customer_id) >= 2
|
[
"What",
"are",
"the",
"distinct",
"names",
"of",
"products",
"purchased",
"by",
"at",
"least",
"two",
"different",
"customers",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 5,
"type": "table",
"value": "order_items"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "column",
"value": "product_id"
},
{
"id": 2,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "column",
"value": "order_id"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,575
|
body_builder
|
spider:train_spider.json:1165
|
What are the birth places that are shared by at least two people?
|
SELECT Birth_Place FROM people GROUP BY Birth_Place HAVING COUNT(*) >= 2
|
[
"What",
"are",
"the",
"birth",
"places",
"that",
"are",
"shared",
"by",
"at",
"least",
"two",
"people",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "birth_place"
},
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,576
|
activity_1
|
spider:train_spider.json:6739
|
Show all the buildings that have at least 10 professors.
|
SELECT building FROM Faculty WHERE rank = "Professor" GROUP BY building HAVING count(*) >= 10
|
[
"Show",
"all",
"the",
"buildings",
"that",
"have",
"at",
"least",
"10",
"professors",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "Professor"
},
{
"id": 1,
"type": "column",
"value": "building"
},
{
"id": 0,
"type": "table",
"value": "faculty"
},
{
"id": 2,
"type": "column",
"value": "rank"
},
{
"id": 4,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,577
|
station_weather
|
spider:train_spider.json:3163
|
Find the name of the train whose route runs through greatest number of stations.
|
SELECT t1.name FROM train AS t1 JOIN route AS t2 ON t1.id = t2.train_id GROUP BY t2.train_id ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"train",
"whose",
"route",
"runs",
"through",
"greatest",
"number",
"of",
"stations",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "train_id"
},
{
"id": 2,
"type": "table",
"value": "train"
},
{
"id": 3,
"type": "table",
"value": "route"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
0
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,578
|
party_host
|
spider:train_spider.json:2660
|
How many parties are there?
|
SELECT count(*) FROM party
|
[
"How",
"many",
"parties",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "party"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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"
] |
12,579
|
coinmarketcap
|
bird:train.json:6296
|
What's the percentage of coins that is higher than the price 1 hour ago in May 29,2013? List the names of these coins.
|
SELECT T1.NAME FROM coins AS T1 INNER JOIN historical AS T2 ON T1.ID = T2.coin_id WHERE T2.DATE = '2013-05-29' AND T2.percent_change_1h > 0
|
[
"What",
"'s",
"the",
"percentage",
"of",
"coins",
"that",
"is",
"higher",
"than",
"the",
"price",
"1",
"hour",
"ago",
"in",
"May",
"29,2013",
"?",
"List",
"the",
"names",
"of",
"these",
"coins",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "percent_change_1h"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 6,
"type": "value",
"value": "2013-05-29"
},
{
"id": 4,
"type": "column",
"value": "coin_id"
},
{
"id": 1,
"type": "table",
"value": "coins"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
21
]
},
{
"entity_id": 1,
"token_idxs": [
24
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"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": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
12,580
|
public_review_platform
|
bird:train.json:3927
|
What is the closing and opening time of businesses located at Gilbert with highest star rating?
|
SELECT T2.closing_time, T2.opening_time FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T1.city LIKE 'Gilbert' ORDER BY T1.stars DESC LIMIT 1
|
[
"What",
"is",
"the",
"closing",
"and",
"opening",
"time",
"of",
"businesses",
"located",
"at",
"Gilbert",
"with",
"highest",
"star",
"rating",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "business_hours"
},
{
"id": 0,
"type": "column",
"value": "closing_time"
},
{
"id": 1,
"type": "column",
"value": "opening_time"
},
{
"id": 7,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "value",
"value": "Gilbert"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
12,581
|
hr_1
|
spider:train_spider.json:3425
|
What are the full name (first and last name) and salary for all employees who does not have any value for commission?
|
SELECT first_name , last_name , salary FROM employees WHERE commission_pct = "null"
|
[
"What",
"are",
"the",
"full",
"name",
"(",
"first",
"and",
"last",
"name",
")",
"and",
"salary",
"for",
"all",
"employees",
"who",
"does",
"not",
"have",
"any",
"value",
"for",
"commission",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "commission_pct"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 5,
"type": "column",
"value": "null"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
23
]
},
{
"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-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,582
|
aan_1
|
bird:test.json:985
|
Find the titles and paper IDs for papers which have Mckeown but not Rambow in author list.
|
SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Mckeown%" EXCEPT SELECT T1.title , T1.paper_id FROM Paper AS T1 JOIN Author_list AS T2 ON T1.paper_id = T2.paper_id JOIN Author AS T3 ON T2.author_id = T3.author_id WHERE T3.name LIKE "%Rambow%"
|
[
"Find",
"the",
"titles",
"and",
"paper",
"IDs",
"for",
"papers",
"which",
"have",
"Mckeown",
"but",
"not",
"Rambow",
"in",
"author",
"list",
"."
] |
[
{
"id": 7,
"type": "table",
"value": "author_list"
},
{
"id": 4,
"type": "column",
"value": "%Mckeown%"
},
{
"id": 8,
"type": "column",
"value": "author_id"
},
{
"id": 1,
"type": "column",
"value": "paper_id"
},
{
"id": 5,
"type": "column",
"value": "%Rambow%"
},
{
"id": 2,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O"
] |
12,583
|
authors
|
bird:train.json:3606
|
Write the titles of papers published by Adam Jones and the journal name in which it was published from 2005 to 2010.
|
SELECT T1.Title FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Journal AS T3 ON T1.JournalId = T3.Id WHERE T2.Name = 'Adam Jones' AND T1.Year BETWEEN 2005 AND 2010
|
[
"Write",
"the",
"titles",
"of",
"papers",
"published",
"by",
"Adam",
"Jones",
"and",
"the",
"journal",
"name",
"in",
"which",
"it",
"was",
"published",
"from",
"2005",
"to",
"2010",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "paperauthor"
},
{
"id": 7,
"type": "value",
"value": "Adam Jones"
},
{
"id": 4,
"type": "column",
"value": "journalid"
},
{
"id": 1,
"type": "table",
"value": "journal"
},
{
"id": 11,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "paper"
},
{
"id": 6,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2005"
},
{
"id": 10,
"type": "value",
"value": "2010"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"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": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
7,
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
19
]
},
{
"entity_id": 10,
"token_idxs": [
21
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
12,584
|
movielens
|
bird:train.json:2330
|
How many unique directors with an average earnings of 2 and a quality of 3 have not made comedy films? List them.
|
SELECT DISTINCT T1.directorid FROM directors AS T1 INNER JOIN movies2directors AS T2 ON T1.directorid = T2.directorid WHERE T1.d_quality = 3 AND T1.avg_revenue = 2 AND T2.genre != 'Comedy'
|
[
"How",
"many",
"unique",
"directors",
"with",
"an",
"average",
"earnings",
"of",
"2",
"and",
"a",
"quality",
"of",
"3",
"have",
"not",
"made",
"comedy",
"films",
"?",
"List",
"them",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "movies2directors"
},
{
"id": 5,
"type": "column",
"value": "avg_revenue"
},
{
"id": 0,
"type": "column",
"value": "directorid"
},
{
"id": 1,
"type": "table",
"value": "directors"
},
{
"id": 3,
"type": "column",
"value": "d_quality"
},
{
"id": 8,
"type": "value",
"value": "Comedy"
},
{
"id": 7,
"type": "column",
"value": "genre"
},
{
"id": 4,
"type": "value",
"value": "3"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
18
]
},
{
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
12,585
|
customers_card_transactions
|
spider:train_spider.json:745
|
Show the account id and the number of transactions for each account
|
SELECT account_id , count(*) FROM Financial_transactions GROUP BY account_id
|
[
"Show",
"the",
"account",
"i",
"d",
"and",
"the",
"number",
"of",
"transactions",
"for",
"each",
"account"
] |
[
{
"id": 0,
"type": "table",
"value": "financial_transactions"
},
{
"id": 1,
"type": "column",
"value": "account_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O"
] |
12,586
|
world_development_indicators
|
bird:train.json:2187
|
Which country have data classified as official aid?
|
SELECT DISTINCT T1.CountryCode FROM Country AS T1 INNER JOIN FootNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T2.Description = 'Data are classified as official aid.'
|
[
"Which",
"country",
"have",
"data",
"classified",
"as",
"official",
"aid",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Data are classified as official aid."
},
{
"id": 0,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "footnotes"
},
{
"id": 1,
"type": "table",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
3,
4,
5,
6,
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
12,587
|
book_publishing_company
|
bird:train.json:195
|
Name all the authors for 'Sushi, Anyone?'.
|
SELECT T3.au_fname, T3.au_lname FROM titles AS T1 INNER JOIN titleauthor AS T2 ON T1.title_id = T2.title_id INNER JOIN authors AS T3 ON T2.au_id = T3.au_id WHERE T1.title = 'Sushi, Anyone?'
|
[
"Name",
"all",
"the",
"authors",
"for",
"'",
"Sushi",
",",
"Anyone",
"?",
"'",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Sushi, Anyone?"
},
{
"id": 6,
"type": "table",
"value": "titleauthor"
},
{
"id": 0,
"type": "column",
"value": "au_fname"
},
{
"id": 1,
"type": "column",
"value": "au_lname"
},
{
"id": 8,
"type": "column",
"value": "title_id"
},
{
"id": 2,
"type": "table",
"value": "authors"
},
{
"id": 5,
"type": "table",
"value": "titles"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 7,
"type": "column",
"value": "au_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
0
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
12,589
|
soccer_2
|
spider:train_spider.json:4992
|
What is the name of school that has the smallest enrollment in each state?
|
SELECT cName , state , min(enr) FROM college GROUP BY state
|
[
"What",
"is",
"the",
"name",
"of",
"school",
"that",
"has",
"the",
"smallest",
"enrollment",
"in",
"each",
"state",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "college"
},
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 2,
"type": "column",
"value": "cname"
},
{
"id": 3,
"type": "column",
"value": "enr"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,591
|
regional_sales
|
bird:train.json:2668
|
Find the net profit of the floral products which were delivered in 2021.
|
SELECT SUM(REPLACE(T1.`Unit Price`, ',', '') - REPLACE(T1.`Unit Cost`, ',', '')) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID WHERE T1.DeliveryDate LIKE '%/%/21' AND T2.`Product Name` = 'Floral'
|
[
"Find",
"the",
"net",
"profit",
"of",
"the",
"floral",
"products",
"which",
"were",
"delivered",
"in",
"2021",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 4,
"type": "column",
"value": "deliverydate"
},
{
"id": 6,
"type": "column",
"value": "Product Name"
},
{
"id": 3,
"type": "column",
"value": "_productid"
},
{
"id": 8,
"type": "column",
"value": "Unit Price"
},
{
"id": 2,
"type": "column",
"value": "productid"
},
{
"id": 10,
"type": "column",
"value": "Unit Cost"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 5,
"type": "value",
"value": "%/%/21"
},
{
"id": 7,
"type": "value",
"value": "Floral"
},
{
"id": 9,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
6
]
},
{
"entity_id": 8,
"token_idxs": [
2,
3
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
12,593
|
european_football_1
|
bird:train.json:2761
|
Please provide the names of any three away teams that competed in the Italian divisions.
|
SELECT T1.AwayTeam FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div=T2.division WHERE T2.country = 'Italy' LIMIT 3
|
[
"Please",
"provide",
"the",
"names",
"of",
"any",
"three",
"away",
"teams",
"that",
"competed",
"in",
"the",
"Italian",
"divisions",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "divisions"
},
{
"id": 0,
"type": "column",
"value": "awayteam"
},
{
"id": 6,
"type": "column",
"value": "division"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "matchs"
},
{
"id": 4,
"type": "value",
"value": "Italy"
},
{
"id": 5,
"type": "column",
"value": "div"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7,
8
]
},
{
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},
{
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},
{
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{
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13
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},
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},
{
"entity_id": 6,
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},
{
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,594
|
soccer_2016
|
bird:train.json:2032
|
What are the names of players who had been man of the match more than 5 times in season year 2008?
|
SELECT CASE WHEN COUNT(T2.Man_of_the_Match) > 5 THEN T1.Player_Name ELSE 0 END FROM Player AS T1 INNER JOIN Match AS T2 ON T1.Player_Id = T2.Man_of_the_Match INNER JOIN Player_Match AS T3 ON T3.Player_Id = T1.Player_Id INNER JOIN Season AS T4 ON T2.Season_Id = T4.Season_Id WHERE T4.Season_Year = 2008
|
[
"What",
"are",
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"names",
"of",
"players",
"who",
"had",
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"of",
"the",
"match",
"more",
"than",
"5",
"times",
"in",
"season",
"year",
"2008",
"?"
] |
[
{
"id": 11,
"type": "column",
"value": "man_of_the_match"
},
{
"id": 4,
"type": "table",
"value": "player_match"
},
{
"id": 1,
"type": "column",
"value": "season_year"
},
{
"id": 6,
"type": "column",
"value": "player_name"
},
{
"id": 5,
"type": "column",
"value": "season_id"
},
{
"id": 9,
"type": "column",
"value": "player_id"
},
{
"id": 0,
"type": "table",
"value": "season"
},
{
"id": 7,
"type": "table",
"value": "player"
},
{
"id": 8,
"type": "table",
"value": "match"
},
{
"id": 2,
"type": "value",
"value": "2008"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 10,
"type": "value",
"value": "5"
}
] |
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18
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19
]
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{
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{
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{
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5
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15
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10,
11
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},
{
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{
"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
12,595
|
address
|
bird:train.json:5103
|
What are the names of the states whose postal point is not affiliated with any organization?
|
SELECT DISTINCT T2.name FROM zip_data AS T1 INNER JOIN state AS T2 ON T1.state = T2.abbreviation WHERE T1.division IS NULL
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"states",
"whose",
"postal",
"point",
"is",
"not",
"affiliated",
"with",
"any",
"organization",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "abbreviation"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 3,
"type": "column",
"value": "division"
},
{
"id": 2,
"type": "table",
"value": "state"
},
{
"id": 4,
"type": "column",
"value": "state"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
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},
{
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},
{
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},
{
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6
]
},
{
"entity_id": 5,
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15
]
},
{
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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": []
},
{
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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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,596
|
storm_record
|
spider:train_spider.json:2690
|
How many regions do we have?
|
SELECT count(*) FROM region
|
[
"How",
"many",
"regions",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
12,597
|
car_retails
|
bird:train.json:1637
|
What is the amount of customers of 1957 Chevy Pickup by customers in a month?
|
SELECT COUNT(T2.customerNumber) FROM orderdetails AS T1 INNER JOIN orders AS T2 ON T1.orderNumber = T2.orderNumber WHERE T1.productCode IN ( SELECT productCode FROM products WHERE productName = '1957 Chevy Pickup' )
|
[
"What",
"is",
"the",
"amount",
"of",
"customers",
"of",
"1957",
"Chevy",
"Pickup",
"by",
"customers",
"in",
"a",
"month",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "1957 Chevy Pickup"
},
{
"id": 3,
"type": "column",
"value": "customernumber"
},
{
"id": 0,
"type": "table",
"value": "orderdetails"
},
{
"id": 2,
"type": "column",
"value": "productcode"
},
{
"id": 4,
"type": "column",
"value": "ordernumber"
},
{
"id": 6,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "table",
"value": "products"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
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{
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},
{
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},
{
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7,
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9
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},
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{
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},
{
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{
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},
{
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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",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
12,598
|
mondial_geo
|
bird:train.json:8312
|
Of the deserts on the America Continent, which one covers the greatest area?
|
SELECT T5.Name FROM country AS T1 INNER JOIN encompasses AS T2 ON T1.Code = T2.Country INNER JOIN continent AS T3 ON T3.Name = T2.Continent INNER JOIN geo_desert AS T4 ON T4.Country = T1.Code INNER JOIN desert AS T5 ON T5.Name = T4.Desert WHERE T3.Name = 'America' ORDER BY T5.Area DESC LIMIT 1
|
[
"Of",
"the",
"deserts",
"on",
"the",
"America",
"Continent",
",",
"which",
"one",
"covers",
"the",
"greatest",
"area",
"?"
] |
[
{
"id": 10,
"type": "table",
"value": "encompasses"
},
{
"id": 4,
"type": "table",
"value": "geo_desert"
},
{
"id": 6,
"type": "table",
"value": "continent"
},
{
"id": 11,
"type": "column",
"value": "continent"
},
{
"id": 2,
"type": "value",
"value": "America"
},
{
"id": 7,
"type": "column",
"value": "country"
},
{
"id": 9,
"type": "table",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "desert"
},
{
"id": 5,
"type": "column",
"value": "desert"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "area"
},
{
"id": 8,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
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6
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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",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
12,599
|
bike_1
|
spider:train_spider.json:211
|
What is the average latitude and longitude of the starting points of all trips?
|
SELECT avg(T1.lat) , avg(T1.long) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id
|
[
"What",
"is",
"the",
"average",
"latitude",
"and",
"longitude",
"of",
"the",
"starting",
"points",
"of",
"all",
"trips",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "start_station_id"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "table",
"value": "trip"
},
{
"id": 3,
"type": "column",
"value": "long"
},
{
"id": 2,
"type": "column",
"value": "lat"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
12,600
|
cre_Doc_and_collections
|
bird:test.json:727
|
Which collection have most number of documents? List collection name, id and number of documents.
|
SELECT T1.Collection_Name , T1.Collection_ID , count(*) FROM Collections AS T1 JOIN Documents_in_Collections AS T2 ON T1.Collection_ID = T2.Collection_ID WHERE T1.Collection_Name = "Best" GROUP BY T1.Collection_ID ORDER BY count(*) DESC LIMIT 1;
|
[
"Which",
"collection",
"have",
"most",
"number",
"of",
"documents",
"?",
"List",
"collection",
"name",
",",
"i",
"d",
"and",
"number",
"of",
"documents",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "documents_in_collections"
},
{
"id": 1,
"type": "column",
"value": "collection_name"
},
{
"id": 0,
"type": "column",
"value": "collection_id"
},
{
"id": 2,
"type": "table",
"value": "collections"
},
{
"id": 4,
"type": "column",
"value": "Best"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,601
|
cars
|
bird:train.json:3074
|
What is the maximum acceleration of a car with price over $40000?
|
SELECT MAX(T1.acceleration) FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T2.price > 40000
|
[
"What",
"is",
"the",
"maximum",
"acceleration",
"of",
"a",
"car",
"with",
"price",
"over",
"$",
"40000",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "acceleration"
},
{
"id": 1,
"type": "table",
"value": "price"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 3,
"type": "value",
"value": "40000"
},
{
"id": 0,
"type": "table",
"value": "data"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"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",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
12,602
|
works_cycles
|
bird:train.json:7296
|
Which vendor's selling price for Hex Nut 5 is the lowest, please give the vendor's name.
|
SELECT T3.Name FROM ProductVendor AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID INNER JOIN Vendor AS T3 ON T1.BusinessEntityID = T3.BusinessEntityID WHERE T2.Name = 'Hex Nut 5' ORDER BY T1.StandardPrice LIMIT 1
|
[
"Which",
"vendor",
"'s",
"selling",
"price",
"for",
"Hex",
"Nut",
"5",
"is",
"the",
"lowest",
",",
"please",
"give",
"the",
"vendor",
"'s",
"name",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "businessentityid"
},
{
"id": 3,
"type": "column",
"value": "standardprice"
},
{
"id": 4,
"type": "table",
"value": "productvendor"
},
{
"id": 2,
"type": "value",
"value": "Hex Nut 5"
},
{
"id": 7,
"type": "column",
"value": "productid"
},
{
"id": 5,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "table",
"value": "vendor"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,603
|
donor
|
bird:train.json:3278
|
What is the average unit price of AKJ Books items?
|
SELECT SUM(item_unit_price) / SUM(item_quantity) FROM resources WHERE vendor_name = 'AKJ Books'
|
[
"What",
"is",
"the",
"average",
"unit",
"price",
"of",
"AKJ",
"Books",
"items",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "item_unit_price"
},
{
"id": 4,
"type": "column",
"value": "item_quantity"
},
{
"id": 1,
"type": "column",
"value": "vendor_name"
},
{
"id": 0,
"type": "table",
"value": "resources"
},
{
"id": 2,
"type": "value",
"value": "AKJ Books"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
12,604
|
university
|
bird:train.json:8003
|
List the names of all the universities that have no less than 50,000 students in the year 2012.
|
SELECT T2.university_name FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.num_students > 50000 AND T1.year = 2012
|
[
"List",
"the",
"names",
"of",
"all",
"the",
"universities",
"that",
"have",
"no",
"less",
"than",
"50,000",
"students",
"in",
"the",
"year",
"2012",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 5,
"type": "column",
"value": "num_students"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 6,
"type": "value",
"value": "50000"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2012"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": [
17
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
12,605
|
game_1
|
spider:train_spider.json:6048
|
What are the names of all games played by Linda Smith?
|
SELECT Gname FROM Plays_games AS T1 JOIN Video_games AS T2 ON T1.gameid = T2.gameid JOIN Student AS T3 ON T3.Stuid = T1.Stuid WHERE T3.Lname = "Smith" AND T3.Fname = "Linda"
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"games",
"played",
"by",
"Linda",
"Smith",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "plays_games"
},
{
"id": 3,
"type": "table",
"value": "video_games"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 9,
"type": "column",
"value": "gameid"
},
{
"id": 0,
"type": "column",
"value": "gname"
},
{
"id": 4,
"type": "column",
"value": "stuid"
},
{
"id": 5,
"type": "column",
"value": "lname"
},
{
"id": 6,
"type": "column",
"value": "Smith"
},
{
"id": 7,
"type": "column",
"value": "fname"
},
{
"id": 8,
"type": "column",
"value": "Linda"
}
] |
[
{
"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": [
10
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"entity_id": 9,
"token_idxs": [
6
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
12,606
|
mondial_geo
|
bird:train.json:8326
|
List all the coral islands along with its city and province.
|
SELECT City, Province FROM locatedOn WHERE Island IN ( SELECT Name FROM island WHERE Type = 'coral' )
|
[
"List",
"all",
"the",
"coral",
"islands",
"along",
"with",
"its",
"city",
"and",
"province",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "locatedon"
},
{
"id": 2,
"type": "column",
"value": "province"
},
{
"id": 3,
"type": "column",
"value": "island"
},
{
"id": 4,
"type": "table",
"value": "island"
},
{
"id": 7,
"type": "value",
"value": "coral"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "type"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
12,607
|
county_public_safety
|
spider:train_spider.json:2554
|
Show the name of cities in the county that has the largest number of police officers.
|
SELECT name FROM city WHERE county_ID = (SELECT county_ID FROM county_public_safety ORDER BY Police_officers DESC LIMIT 1)
|
[
"Show",
"the",
"name",
"of",
"cities",
"in",
"the",
"county",
"that",
"has",
"the",
"largest",
"number",
"of",
"police",
"officers",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "county_public_safety"
},
{
"id": 4,
"type": "column",
"value": "police_officers"
},
{
"id": 2,
"type": "column",
"value": "county_id"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14,
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
12,608
|
works_cycles
|
bird:train.json:7352
|
How many shipments by truck were made?
|
SELECT COUNT(*) FROM ShipMethod AS T1 INNER JOIN SalesOrderHeader AS T2 USING (ShipMethodID) WHERE T1.Name = 'XRQ - TRUCK GROUND'
|
[
"How",
"many",
"shipments",
"by",
"truck",
"were",
"made",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "XRQ - TRUCK GROUND"
},
{
"id": 1,
"type": "table",
"value": "salesorderheader"
},
{
"id": 0,
"type": "table",
"value": "shipmethod"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
12,609
|
movie_1
|
spider:train_spider.json:2488
|
For directors who had more than one movie, return the titles and produced years of all movies directed by them.
|
SELECT T1.title , T1.year FROM Movie AS T1 JOIN Movie AS T2 ON T1.director = T2.director WHERE T1.title != T2.title
|
[
"For",
"directors",
"who",
"had",
"more",
"than",
"one",
"movie",
",",
"return",
"the",
"titles",
"and",
"produced",
"years",
"of",
"all",
"movies",
"directed",
"by",
"them",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "director"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "year"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
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},
{
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{
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},
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,610
|
student_club
|
bird:dev.json:1323
|
List all the names of events that had an attendance of over 20 students but were not fundraisers.
|
SELECT T1.event_name FROM event AS T1 INNER JOIN attendance AS T2 ON T1.event_id = T2.link_to_event GROUP BY T1.event_id HAVING COUNT(T2.link_to_event) > 20 EXCEPT SELECT T1.event_name FROM event AS T1 WHERE T1.type = 'Fundraiser'
|
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"an",
"attendance",
"of",
"over",
"20",
"students",
"but",
"were",
"not",
"fundraisers",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "link_to_event"
},
{
"id": 2,
"type": "column",
"value": "event_name"
},
{
"id": 3,
"type": "table",
"value": "attendance"
},
{
"id": 6,
"type": "value",
"value": "Fundraiser"
},
{
"id": 0,
"type": "column",
"value": "event_id"
},
{
"id": 1,
"type": "table",
"value": "event"
},
{
"id": 5,
"type": "column",
"value": "type"
},
{
"id": 4,
"type": "value",
"value": "20"
}
] |
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{
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5
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},
{
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"entity_id": 15,
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{
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"token_idxs": []
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{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,611
|
world
|
bird:train.json:7829
|
List the countries and their official languages in Antarctica.
|
SELECT T1.Name, T2.Language FROM Country AS T1 INNER JOIN CountryLanguage AS T2 ON T1.Code = T2.CountryCode WHERE T1.Continent = 'Antarctica' AND T2.IsOfficial = 'T'
|
[
"List",
"the",
"countries",
"and",
"their",
"official",
"languages",
"in",
"Antarctica",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "countrylanguage"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 7,
"type": "value",
"value": "Antarctica"
},
{
"id": 8,
"type": "column",
"value": "isofficial"
},
{
"id": 6,
"type": "column",
"value": "continent"
},
{
"id": 1,
"type": "column",
"value": "language"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "code"
},
{
"id": 9,
"type": "value",
"value": "T"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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6
]
},
{
"entity_id": 2,
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2
]
},
{
"entity_id": 3,
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},
{
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},
{
"entity_id": 6,
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{
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8
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},
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5
]
},
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"entity_id": 9,
"token_idxs": []
},
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{
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},
{
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"entity_id": 14,
"token_idxs": []
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"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
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},
{
"entity_id": 18,
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
12,613
|
hockey
|
bird:train.json:7697
|
Which teams had the most postseason empty net goals in 2010 season? List their team names.
|
SELECT T2.name FROM Goalies AS T1 INNER JOIN Teams AS T2 ON T1.tmID = T2.tmID WHERE T1.year = 2010 GROUP BY T2.name ORDER BY SUM(PostENG) DESC LIMIT 1
|
[
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"empty",
"net",
"goals",
"in",
"2010",
"season",
"?",
"List",
"their",
"team",
"names",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "goalies"
},
{
"id": 6,
"type": "column",
"value": "posteng"
},
{
"id": 2,
"type": "table",
"value": "teams"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2010"
},
{
"id": 5,
"type": "column",
"value": "tmid"
}
] |
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"token_idxs": [
16
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},
{
"entity_id": 1,
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8
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1
]
},
{
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},
{
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10
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},
{
"entity_id": 5,
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},
{
"entity_id": 10,
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{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,614
|
hr_1
|
spider:train_spider.json:3465
|
Can you return all detailed info of jobs which was done by any of the employees who is presently earning a salary on and above 12000?
|
SELECT * FROM job_history AS T1 JOIN employees AS T2 ON T1.employee_id = T2.employee_id WHERE T2.salary >= 12000
|
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"by",
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"is",
"presently",
"earning",
"a",
"salary",
"on",
"and",
"above",
"12000",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "job_history"
},
{
"id": 4,
"type": "column",
"value": "employee_id"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "salary"
},
{
"id": 3,
"type": "value",
"value": "12000"
}
] |
[
{
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"token_idxs": []
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{
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21
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{
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"token_idxs": [
25
]
},
{
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},
{
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},
{
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{
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{
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{
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{
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"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
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"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,615
|
shipping
|
bird:train.json:5668
|
What is the address of the driver that delivers the shipment for the customer lives at 7052 Carroll Road, San Diego, California?
|
SELECT T3.address FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id INNER JOIN driver AS T3 ON T3.driver_id = T1.driver_id WHERE T2.address = '7052 Carroll Road' AND T2.city = 'San Diego' AND T2.state = 'CA'
|
[
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"that",
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"the",
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"for",
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"customer",
"lives",
"at",
"7052",
"Carroll",
"Road",
",",
"San",
"Diego",
",",
"California",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "7052 Carroll Road"
},
{
"id": 4,
"type": "column",
"value": "driver_id"
},
{
"id": 7,
"type": "value",
"value": "San Diego"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "address"
},
{
"id": 10,
"type": "column",
"value": "cust_id"
},
{
"id": 1,
"type": "table",
"value": "driver"
},
{
"id": 8,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "column",
"value": "city"
},
{
"id": 9,
"type": "value",
"value": "CA"
}
] |
[
{
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"token_idxs": [
3
]
},
{
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6
]
},
{
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10
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16,
17,
18
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},
{
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{
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20,
21
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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",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
12,617
|
thrombosis_prediction
|
bird:dev.json:1231
|
For patient born between 1936-1956, how many male patients have creatinine phosphokinase beyond the normal range?
|
SELECT COUNT(DISTINCT T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE STRFTIME('%Y', T1.Birthday) BETWEEN '1936' AND '1956' AND T1.SEX = 'M' AND T2.CPK >= 250
|
[
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"born",
"between",
"1936",
"-",
"1956",
",",
"how",
"many",
"male",
"patients",
"have",
"creatinine",
"phosphokinase",
"beyond",
"the",
"normal",
"range",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 10,
"type": "column",
"value": "birthday"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "value",
"value": "1936"
},
{
"id": 4,
"type": "value",
"value": "1956"
},
{
"id": 5,
"type": "column",
"value": "sex"
},
{
"id": 7,
"type": "column",
"value": "cpk"
},
{
"id": 8,
"type": "value",
"value": "250"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "%Y"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
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"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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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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{
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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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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,618
|
human_resources
|
bird:train.json:8933
|
Please list the social security numbers of the male employees with a salary of over $70,000 a year.
|
SELECT ssn FROM employee WHERE gender = 'M' AND CAST(REPLACE(SUBSTR(salary, 4), ',', '') AS REAL) > 70000
|
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"employees",
"with",
"a",
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"of",
"over",
"$",
"70,000",
"a",
"year",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 2,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "column",
"value": "salary"
},
{
"id": 4,
"type": "value",
"value": "70000"
},
{
"id": 1,
"type": "column",
"value": "ssn"
},
{
"id": 3,
"type": "value",
"value": "M"
},
{
"id": 5,
"type": "value",
"value": ","
},
{
"id": 7,
"type": "value",
"value": "4"
}
] |
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{
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},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,619
|
beer_factory
|
bird:train.json:5307
|
How many Folsom customers prefer to pay with Visa?
|
SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.City = 'Folsom' AND T2.CreditCardType = 'Visa'
|
[
"How",
"many",
"Folsom",
"customers",
"prefer",
"to",
"pay",
"with",
"Visa",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "creditcardtype"
},
{
"id": 1,
"type": "table",
"value": "transaction"
},
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "value",
"value": "Folsom"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 6,
"type": "value",
"value": "Visa"
}
] |
[
{
"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": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,620
|
cre_Doc_and_collections
|
bird:test.json:702
|
For each document object id, how many children do they have?
|
SELECT T2.Document_Object_ID , count(*) FROM Document_Objects AS T1 JOIN Document_Objects AS T2 ON T1.Parent_Document_Object_ID = T2.Document_Object_ID GROUP BY T2.Document_Object_ID ORDER BY count(*) DESC LIMIT 1;
|
[
"For",
"each",
"document",
"object",
"i",
"d",
",",
"how",
"many",
"children",
"do",
"they",
"have",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "parent_document_object_id"
},
{
"id": 0,
"type": "column",
"value": "document_object_id"
},
{
"id": 1,
"type": "table",
"value": "document_objects"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
12,621
|
online_exams
|
bird:test.json:227
|
Show the student answer texts that received both "Normal" and "Absent" as comments.
|
SELECT Student_Answer_Text FROM Student_Answers WHERE Comments = "Normal" INTERSECT SELECT Student_Answer_Text FROM Student_Answers WHERE Comments = "Absent"
|
[
"Show",
"the",
"student",
"answer",
"texts",
"that",
"received",
"both",
"\"",
"Normal",
"\"",
"and",
"\"",
"Absent",
"\"",
"as",
"comments",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "student_answer_text"
},
{
"id": 0,
"type": "table",
"value": "student_answers"
},
{
"id": 2,
"type": "column",
"value": "comments"
},
{
"id": 3,
"type": "column",
"value": "Normal"
},
{
"id": 4,
"type": "column",
"value": "Absent"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
12,622
|
school_finance
|
spider:train_spider.json:1893
|
How many donors have endowment for school named "Glenn"?
|
SELECT count(DISTINCT T1.donator_name) FROM endowment AS T1 JOIN school AS T2 ON T1.school_id = T2.school_id WHERE T2.school_name = "Glenn"
|
[
"How",
"many",
"donors",
"have",
"endowment",
"for",
"school",
"named",
"\"",
"Glenn",
"\"",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "donator_name"
},
{
"id": 2,
"type": "column",
"value": "school_name"
},
{
"id": 0,
"type": "table",
"value": "endowment"
},
{
"id": 5,
"type": "column",
"value": "school_id"
},
{
"id": 1,
"type": "table",
"value": "school"
},
{
"id": 3,
"type": "column",
"value": "Glenn"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
2,
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
12,623
|
student_assessment
|
spider:train_spider.json:73
|
Find id of the candidate whose email is stanley.monahan@example.org?
|
SELECT T2.candidate_id FROM people AS T1 JOIN candidates AS T2 ON T1.person_id = T2.candidate_id WHERE T1.email_address = "stanley.monahan@example.org"
|
[
"Find",
"i",
"d",
"of",
"the",
"candidate",
"whose",
"email",
"is",
"stanley.monahan@example.org",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "stanley.monahan@example.org"
},
{
"id": 3,
"type": "column",
"value": "email_address"
},
{
"id": 0,
"type": "column",
"value": "candidate_id"
},
{
"id": 2,
"type": "table",
"value": "candidates"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "people"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
12,624
|
menu
|
bird:train.json:5488
|
How many menu items were created on 28th March 2011?
|
SELECT COUNT(*) FROM MenuItem WHERE created_at LIKE '2011-03-28%'
|
[
"How",
"many",
"menu",
"items",
"were",
"created",
"on",
"28th",
"March",
"2011",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "2011-03-28%"
},
{
"id": 1,
"type": "column",
"value": "created_at"
},
{
"id": 0,
"type": "table",
"value": "menuitem"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
12,625
|
university
|
bird:train.json:8024
|
List the criteria names under the ranking system called Center for World University Ranking.
|
SELECT T2.criteria_name FROM ranking_system AS T1 INNER JOIN ranking_criteria AS T2 ON T1.id = T2.ranking_system_id WHERE T1.system_name = 'Center for World University Rankings'
|
[
"List",
"the",
"criteria",
"names",
"under",
"the",
"ranking",
"system",
"called",
"Center",
"for",
"World",
"University",
"Ranking",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Center for World University Rankings"
},
{
"id": 6,
"type": "column",
"value": "ranking_system_id"
},
{
"id": 2,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 1,
"type": "table",
"value": "ranking_system"
},
{
"id": 0,
"type": "column",
"value": "criteria_name"
},
{
"id": 3,
"type": "column",
"value": "system_name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
12,626
|
student_club
|
bird:dev.json:1320
|
Please list the event names of all the events attended by Maya Mclean.
|
SELECT T1.event_name FROM event AS T1 INNER JOIN attendance AS T2 ON T1.event_id = T2.link_to_event INNER JOIN member AS T3 ON T2.link_to_member = T3.member_id WHERE T3.first_name = 'Maya' AND T3.last_name = 'Mclean'
|
[
"Please",
"list",
"the",
"event",
"names",
"of",
"all",
"the",
"events",
"attended",
"by",
"Maya",
"Mclean",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "link_to_member"
},
{
"id": 11,
"type": "column",
"value": "link_to_event"
},
{
"id": 0,
"type": "column",
"value": "event_name"
},
{
"id": 3,
"type": "table",
"value": "attendance"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 5,
"type": "column",
"value": "member_id"
},
{
"id": 8,
"type": "column",
"value": "last_name"
},
{
"id": 10,
"type": "column",
"value": "event_id"
},
{
"id": 1,
"type": "table",
"value": "member"
},
{
"id": 9,
"type": "value",
"value": "Mclean"
},
{
"id": 2,
"type": "table",
"value": "event"
},
{
"id": 7,
"type": "value",
"value": "Maya"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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": [
11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
12
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
1,
2
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
12,627
|
trains
|
bird:train.json:690
|
How many trains are there that run in the east direction?
|
SELECT COUNT(id) FROM trains WHERE direction = 'east'
|
[
"How",
"many",
"trains",
"are",
"there",
"that",
"run",
"in",
"the",
"east",
"direction",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "direction"
},
{
"id": 0,
"type": "table",
"value": "trains"
},
{
"id": 2,
"type": "value",
"value": "east"
},
{
"id": 3,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
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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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
12,628
|
phone_1
|
spider:train_spider.json:1051
|
Find the pixels of the screen modes that are used by both phones with full accreditation types and phones with Provisional accreditation types.
|
SELECT t1.pixels FROM screen_mode AS t1 JOIN phone AS t2 ON t1.Graphics_mode = t2.screen_mode WHERE t2.Accreditation_type = 'Provisional' INTERSECT SELECT t1.pixels FROM screen_mode AS t1 JOIN phone AS t2 ON t1.Graphics_mode = t2.screen_mode WHERE t2.Accreditation_type = 'Full'
|
[
"Find",
"the",
"pixels",
"of",
"the",
"screen",
"modes",
"that",
"are",
"used",
"by",
"both",
"phones",
"with",
"full",
"accreditation",
"types",
"and",
"phones",
"with",
"Provisional",
"accreditation",
"types",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "accreditation_type"
},
{
"id": 6,
"type": "column",
"value": "graphics_mode"
},
{
"id": 1,
"type": "table",
"value": "screen_mode"
},
{
"id": 4,
"type": "value",
"value": "Provisional"
},
{
"id": 7,
"type": "column",
"value": "screen_mode"
},
{
"id": 0,
"type": "column",
"value": "pixels"
},
{
"id": 2,
"type": "table",
"value": "phone"
},
{
"id": 5,
"type": "value",
"value": "Full"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
15,
16
]
},
{
"entity_id": 4,
"token_idxs": [
20
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5,
6
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
12,629
|
codebase_community
|
bird:dev.json:675
|
How many users whose reputations are higher than 2000 and the number of views is higher than 1000?
|
SELECT COUNT(id) FROM users WHERE Reputation > 2000 AND Views > 1000
|
[
"How",
"many",
"users",
"whose",
"reputations",
"are",
"higher",
"than",
"2000",
"and",
"the",
"number",
"of",
"views",
"is",
"higher",
"than",
"1000",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "reputation"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 4,
"type": "column",
"value": "views"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 5,
"type": "value",
"value": "1000"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
17
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
12,630
|
computer_student
|
bird:train.json:1014
|
List any five of course IDs with professor IDs who taught master courses.
|
SELECT T1.course_id, T2.p_id FROM course AS T1 INNER JOIN taughtBy AS T2 ON T1.course_id = T2.course_id WHERE T1.courseLevel = 'Level_500' LIMIT 5
|
[
"List",
"any",
"five",
"of",
"course",
"IDs",
"with",
"professor",
"IDs",
"who",
"taught",
"master",
"courses",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "courselevel"
},
{
"id": 0,
"type": "column",
"value": "course_id"
},
{
"id": 5,
"type": "value",
"value": "Level_500"
},
{
"id": 3,
"type": "table",
"value": "taughtby"
},
{
"id": 2,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "column",
"value": "p_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
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