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1,829
|
tracking_orders
|
spider:train_spider.json:6925
|
List the names of all distinct products in alphabetical order.
|
SELECT DISTINCT product_name FROM products ORDER BY product_name
|
[
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"the",
"names",
"of",
"all",
"distinct",
"products",
"in",
"alphabetical",
"order",
"."
] |
[
{
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{
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"type": "table",
"value": "products"
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"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,830
|
beer_factory
|
bird:train.json:5321
|
What is the full name of the customer who gave a 5-star rating and commented "The quintessential dessert root beer. No ice cream required" on his review?
|
SELECT T1.First, T1.Last FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.StarRating = 5 AND T2.Review = 'The quintessential dessert root beer. No ice cream required.'
|
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] |
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{
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{
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{
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"value": "first"
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"type": "column",
"value": "last"
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{
"id": 6,
"type": "value",
"value": "5"
}
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"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,831
|
university_basketball
|
spider:train_spider.json:979
|
List all public schools and their locations.
|
SELECT school , LOCATION FROM university WHERE affiliation = 'Public'
|
[
"List",
"all",
"public",
"schools",
"and",
"their",
"locations",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "affiliation"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "column",
"value": "location"
},
{
"id": 1,
"type": "column",
"value": "school"
},
{
"id": 4,
"type": "value",
"value": "Public"
}
] |
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}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
1,833
|
student_1
|
spider:train_spider.json:4088
|
For each grade 0 classroom, report the total number of students.
|
SELECT classroom , count(*) FROM list WHERE grade = "0" GROUP BY classroom
|
[
"For",
"each",
"grade",
"0",
"classroom",
",",
"report",
"the",
"total",
"number",
"of",
"students",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "classroom"
},
{
"id": 2,
"type": "column",
"value": "grade"
},
{
"id": 0,
"type": "table",
"value": "list"
},
{
"id": 3,
"type": "column",
"value": "0"
}
] |
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{
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},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,834
|
hospital_1
|
spider:train_spider.json:3997
|
What are the distinct names of nurses on call?
|
SELECT DISTINCT T1.name FROM nurse AS T1 JOIN on_call AS T2 ON T1.EmployeeID = T2.nurse
|
[
"What",
"are",
"the",
"distinct",
"names",
"of",
"nurses",
"on",
"call",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "employeeid"
},
{
"id": 2,
"type": "table",
"value": "on_call"
},
{
"id": 1,
"type": "table",
"value": "nurse"
},
{
"id": 4,
"type": "column",
"value": "nurse"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
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] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O"
] |
1,835
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4203
|
Which employees have the role with code "HR"? Find their names.
|
SELECT employee_name FROM Employees WHERE role_code = "HR"
|
[
"Which",
"employees",
"have",
"the",
"role",
"with",
"code",
"\"",
"HR",
"\"",
"?",
"Find",
"their",
"names",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "employee_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "role_code"
},
{
"id": 3,
"type": "column",
"value": "HR"
}
] |
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{
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}
] |
[
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,836
|
address
|
bird:train.json:5142
|
What is the state for area code of 787?
|
SELECT DISTINCT T2.state FROM area_code AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.area_code = 787
|
[
"What",
"is",
"the",
"state",
"for",
"area",
"code",
"of",
"787",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "area_code"
},
{
"id": 3,
"type": "column",
"value": "area_code"
},
{
"id": 2,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 4,
"type": "value",
"value": "787"
}
] |
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{
"entity_id": 18,
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},
{
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}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,837
|
chicago_crime
|
bird:train.json:8591
|
To which community area does the neighborhood Albany Park belong?
|
SELECT T2.community_area_name FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.neighborhood_name = 'Albany Park'
|
[
"To",
"which",
"community",
"area",
"does",
"the",
"neighborhood",
"Albany",
"Park",
"belong",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "community_area_name"
},
{
"id": 3,
"type": "column",
"value": "neighborhood_name"
},
{
"id": 5,
"type": "column",
"value": "community_area_no"
},
{
"id": 2,
"type": "table",
"value": "community_area"
},
{
"id": 1,
"type": "table",
"value": "neighborhood"
},
{
"id": 4,
"type": "value",
"value": "Albany Park"
}
] |
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2,
3
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},
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7,
8
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{
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"token_idxs": []
},
{
"entity_id": 19,
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] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
1,838
|
olympics
|
bird:train.json:4993
|
How many Olympic games were held in London?
|
SELECT COUNT(T1.games_id) FROM games_city AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.id WHERE T2.city_name = 'London'
|
[
"How",
"many",
"Olympic",
"games",
"were",
"held",
"in",
"London",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "games_city"
},
{
"id": 2,
"type": "column",
"value": "city_name"
},
{
"id": 4,
"type": "column",
"value": "games_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 3,
"type": "value",
"value": "London"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
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"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,839
|
address
|
bird:train.json:5155
|
What is the Asian population in the city with the alias Leeds?
|
SELECT SUM(T2.asian_population) FROM alias AS T1 INNER JOIN zip_data AS T2 ON T1.zip_code = T2.zip_code WHERE T1.alias = 'Leeds'
|
[
"What",
"is",
"the",
"Asian",
"population",
"in",
"the",
"city",
"with",
"the",
"alias",
"Leeds",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "asian_population"
},
{
"id": 1,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "zip_code"
},
{
"id": 0,
"type": "table",
"value": "alias"
},
{
"id": 2,
"type": "column",
"value": "alias"
},
{
"id": 3,
"type": "value",
"value": "Leeds"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
3,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
1,840
|
codebase_community
|
bird:dev.json:661
|
How old is the most influential user?
|
SELECT Age FROM users WHERE Reputation = ( SELECT MAX(Reputation) FROM users )
|
[
"How",
"old",
"is",
"the",
"most",
"influential",
"user",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "reputation"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,841
|
customers_and_orders
|
bird:test.json:304
|
What are the names of products that have not been ordered?
|
SELECT product_name FROM Products EXCEPT SELECT T1.product_name FROM Products AS t1 JOIN Order_items AS T2 ON T1.product_id = T2.product_id
|
[
"What",
"are",
"the",
"names",
"of",
"products",
"that",
"have",
"not",
"been",
"ordered",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 2,
"type": "table",
"value": "order_items"
},
{
"id": 3,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,842
|
movielens
|
bird:train.json:2291
|
How many of the users who rate the movie with the id '2462959' are female?
|
SELECT COUNT(T1.userid) FROM users AS T1 INNER JOIN u2base AS T2 ON T1.userid = T2.userid WHERE T2.userid = 2462959 AND T1.u_gender = 'F'
|
[
"How",
"many",
"of",
"the",
"users",
"who",
"rate",
"the",
"movie",
"with",
"the",
"i",
"d",
"'",
"2462959",
"'",
"are",
"female",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "u_gender"
},
{
"id": 3,
"type": "value",
"value": "2462959"
},
{
"id": 1,
"type": "table",
"value": "u2base"
},
{
"id": 2,
"type": "column",
"value": "userid"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 5,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"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-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
1,843
|
company_office
|
spider:train_spider.json:4570
|
Whah are the name of each industry and the number of companies in that industry?
|
SELECT Industry , COUNT(*) FROM Companies GROUP BY Industry
|
[
"Whah",
"are",
"the",
"name",
"of",
"each",
"industry",
"and",
"the",
"number",
"of",
"companies",
"in",
"that",
"industry",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "companies"
},
{
"id": 1,
"type": "column",
"value": "industry"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,844
|
retails
|
bird:train.json:6682
|
Please list the phone numbers of all the customers in the household segment and are in Brazil.
|
SELECT T1.c_phone FROM customer AS T1 INNER JOIN nation AS T2 ON T1.c_nationkey = T2.n_nationkey WHERE T1.c_mktsegment = 'HOUSEHOLD' AND T2.n_name = 'BRAZIL'
|
[
"Please",
"list",
"the",
"phone",
"numbers",
"of",
"all",
"the",
"customers",
"in",
"the",
"household",
"segment",
"and",
"are",
"in",
"Brazil",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "c_mktsegment"
},
{
"id": 3,
"type": "column",
"value": "c_nationkey"
},
{
"id": 4,
"type": "column",
"value": "n_nationkey"
},
{
"id": 6,
"type": "value",
"value": "HOUSEHOLD"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 0,
"type": "column",
"value": "c_phone"
},
{
"id": 2,
"type": "table",
"value": "nation"
},
{
"id": 7,
"type": "column",
"value": "n_name"
},
{
"id": 8,
"type": "value",
"value": "BRAZIL"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"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": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
16
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,845
|
authors
|
bird:train.json:3603
|
Give the title and author's name of the papers published between 2000 and 2005 that include the topic optical properties.
|
SELECT T1.Title, T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T1.Keyword LIKE '%optical properties%' AND T1.Year BETWEEN 2000 AND 2005 AND T1.Title <> ''
|
[
"Give",
"the",
"title",
"and",
"author",
"'s",
"name",
"of",
"the",
"papers",
"published",
"between",
"2000",
"and",
"2005",
"that",
"include",
"the",
"topic",
"optical",
"properties",
"."
] |
[
{
"id": 7,
"type": "value",
"value": "%optical properties%"
},
{
"id": 3,
"type": "table",
"value": "paperauthor"
},
{
"id": 5,
"type": "column",
"value": "paperid"
},
{
"id": 6,
"type": "column",
"value": "keyword"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 8,
"type": "column",
"value": "year"
},
{
"id": 9,
"type": "value",
"value": "2000"
},
{
"id": 10,
"type": "value",
"value": "2005"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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": [
19,
20
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
12
]
},
{
"entity_id": 10,
"token_idxs": [
14
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,846
|
address
|
bird:train.json:5094
|
What is the highest gender ratio of the residential areas in Arecibo county?
|
SELECT CAST(T1.male_population AS REAL) / T1.female_population FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T2.county = 'ARECIBO' AND T1.female_population <> 0 ORDER BY 1 DESC LIMIT 1
|
[
"What",
"is",
"the",
"highest",
"gender",
"ratio",
"of",
"the",
"residential",
"areas",
"in",
"Arecibo",
"county",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "female_population"
},
{
"id": 8,
"type": "column",
"value": "male_population"
},
{
"id": 0,
"type": "table",
"value": "zip_data"
},
{
"id": 4,
"type": "column",
"value": "zip_code"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "value",
"value": "ARECIBO"
},
{
"id": 5,
"type": "column",
"value": "county"
},
{
"id": 2,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"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": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,847
|
race_track
|
spider:train_spider.json:780
|
What are the names of different tracks, and how many races has each had?
|
SELECT T2.name , count(*) FROM race AS T1 JOIN track AS T2 ON T1.track_id = T2.track_id GROUP BY T1.track_id
|
[
"What",
"are",
"the",
"names",
"of",
"different",
"tracks",
",",
"and",
"how",
"many",
"races",
"has",
"each",
"had",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "track_id"
},
{
"id": 3,
"type": "table",
"value": "track"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "race"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,848
|
mondial_geo
|
bird:train.json:8300
|
Please list the mountains in the country with the lowest inflation rate.
|
SELECT Mountain FROM geo_mountain WHERE Country = ( SELECT Country FROM economy ORDER BY Inflation ASC LIMIT 1 )
|
[
"Please",
"list",
"the",
"mountains",
"in",
"the",
"country",
"with",
"the",
"lowest",
"inflation",
"rate",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "geo_mountain"
},
{
"id": 4,
"type": "column",
"value": "inflation"
},
{
"id": 1,
"type": "column",
"value": "mountain"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "economy"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,849
|
solvency_ii
|
spider:train_spider.json:4591
|
Show the product type codes that have at least two products.
|
SELECT Product_Type_Code FROM Products GROUP BY Product_Type_Code HAVING COUNT(*) >= 2
|
[
"Show",
"the",
"product",
"type",
"codes",
"that",
"have",
"at",
"least",
"two",
"products",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "product_type_code"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,850
|
insurance_policies
|
spider:train_spider.json:3871
|
Tell me the the date when the first claim was made.
|
SELECT Date_Claim_Made FROM Claims ORDER BY Date_Claim_Made ASC LIMIT 1
|
[
"Tell",
"me",
"the",
"the",
"date",
"when",
"the",
"first",
"claim",
"was",
"made",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "date_claim_made"
},
{
"id": 0,
"type": "table",
"value": "claims"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,851
|
mondial_geo
|
bird:train.json:8284
|
In which province is the highest volcano mountain located in?
|
SELECT T1.Province FROM country AS T1 INNER JOIN geo_mountain AS T2 ON T1.Code = T2.Country INNER JOIN mountain AS T3 ON T3.Name = T2.Mountain WHERE T3.Type = 'volcano' ORDER BY T3.Height DESC LIMIT 1
|
[
"In",
"which",
"province",
"is",
"the",
"highest",
"volcano",
"mountain",
"located",
"in",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "geo_mountain"
},
{
"id": 0,
"type": "column",
"value": "province"
},
{
"id": 1,
"type": "table",
"value": "mountain"
},
{
"id": 8,
"type": "column",
"value": "mountain"
},
{
"id": 3,
"type": "value",
"value": "volcano"
},
{
"id": 5,
"type": "table",
"value": "country"
},
{
"id": 10,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "height"
},
{
"id": 2,
"type": "column",
"value": "type"
},
{
"id": 7,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
1,852
|
car_retails
|
bird:train.json:1659
|
For Which order was the most profitable, please list the customer name of the order and the profit of the order.
|
SELECT t3.customerName, (t1.priceEach - t4.buyPrice) * t1.quantityOrdered FROM orderdetails AS t1 INNER JOIN orders AS t2 ON t1.orderNumber = t2.orderNumber INNER JOIN customers AS t3 ON t2.customerNumber = t3.customerNumber INNER JOIN products AS t4 ON t1.productCode = t4.productCode GROUP BY t3.customerName, t1.priceEach, t4.buyPrice, t1.quantityOrdered ORDER BY (t1.priceEach - t4.buyPrice) * t1.quantityOrdered DESC LIMIT 1
|
[
"For",
"Which",
"order",
"was",
"the",
"most",
"profitable",
",",
"please",
"list",
"the",
"customer",
"name",
"of",
"the",
"order",
"and",
"the",
"profit",
"of",
"the",
"order",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "quantityordered"
},
{
"id": 9,
"type": "column",
"value": "customernumber"
},
{
"id": 0,
"type": "column",
"value": "customername"
},
{
"id": 7,
"type": "table",
"value": "orderdetails"
},
{
"id": 6,
"type": "column",
"value": "productcode"
},
{
"id": 10,
"type": "column",
"value": "ordernumber"
},
{
"id": 1,
"type": "column",
"value": "priceeach"
},
{
"id": 5,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "column",
"value": "buyprice"
},
{
"id": 4,
"type": "table",
"value": "products"
},
{
"id": 8,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": [
2
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
15
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,853
|
game_1
|
spider:train_spider.json:5995
|
Show the average, minimum, and maximum age for different majors.
|
SELECT major , avg(age) , min(age) , max(age) FROM Student GROUP BY major
|
[
"Show",
"the",
"average",
",",
"minimum",
",",
"and",
"maximum",
"age",
"for",
"different",
"majors",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "major"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
1,854
|
store_1
|
spider:train_spider.json:630
|
What are the names of all Rock tracks that are stored on MPEG audio files?
|
SELECT T2.name FROM genres AS T1 JOIN tracks AS T2 ON T1.id = T2.genre_id JOIN media_types AS T3 ON T3.id = T2.media_type_id WHERE T1.name = "Rock" AND T3.name = "MPEG audio file";
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"Rock",
"tracks",
"that",
"are",
"stored",
"on",
"MPEG",
"audio",
"files",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "MPEG audio file"
},
{
"id": 5,
"type": "column",
"value": "media_type_id"
},
{
"id": 1,
"type": "table",
"value": "media_types"
},
{
"id": 8,
"type": "column",
"value": "genre_id"
},
{
"id": 2,
"type": "table",
"value": "genres"
},
{
"id": 3,
"type": "table",
"value": "tracks"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "Rock"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": [
12,
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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
1,855
|
institution_sports
|
bird:test.json:1648
|
Return the cities and provinces of institutions.
|
SELECT City , Province FROM institution
|
[
"Return",
"the",
"cities",
"and",
"provinces",
"of",
"institutions",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "institution"
},
{
"id": 2,
"type": "column",
"value": "province"
},
{
"id": 1,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
1,856
|
social_media
|
bird:train.json:842
|
Please list the texts of all the tweets in French posted by male users.
|
SELECT T1.text FROM twitter AS T1 INNER JOIN user AS T2 ON T1.UserID = T2.UserID WHERE T2.Gender = 'Male' AND T1.Lang = 'fr'
|
[
"Please",
"list",
"the",
"texts",
"of",
"all",
"the",
"tweets",
"in",
"French",
"posted",
"by",
"male",
"users",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "twitter"
},
{
"id": 2,
"type": "column",
"value": "userid"
},
{
"id": 3,
"type": "column",
"value": "gender"
},
{
"id": 0,
"type": "column",
"value": "text"
},
{
"id": 4,
"type": "value",
"value": "Male"
},
{
"id": 5,
"type": "column",
"value": "lang"
},
{
"id": 6,
"type": "value",
"value": "fr"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,857
|
shakespeare
|
bird:train.json:2977
|
How many scenes are there in King John?
|
SELECT COUNT(T2.Scene) FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id WHERE T1.Title = 'King John'
|
[
"How",
"many",
"scenes",
"are",
"there",
"in",
"King",
"John",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "King John"
},
{
"id": 1,
"type": "table",
"value": "chapters"
},
{
"id": 6,
"type": "column",
"value": "work_id"
},
{
"id": 0,
"type": "table",
"value": "works"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "column",
"value": "scene"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,858
|
public_review_platform
|
bird:train.json:4026
|
List out the state of businesses which have opening time at 1AM.
|
SELECT DISTINCT T1.state FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T2.opening_time = '1AM'
|
[
"List",
"out",
"the",
"state",
"of",
"businesses",
"which",
"have",
"opening",
"time",
"at",
"1AM",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "business_hours"
},
{
"id": 3,
"type": "column",
"value": "opening_time"
},
{
"id": 5,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "business"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 4,
"type": "value",
"value": "1AM"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,859
|
soccer_3
|
bird:test.json:16
|
Show names of players and names of clubs they are in.
|
SELECT T2.Name , T1.Name FROM club AS T1 JOIN player AS T2 ON T1.Club_ID = T2.Club_ID
|
[
"Show",
"names",
"of",
"players",
"and",
"names",
"of",
"clubs",
"they",
"are",
"in",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "club_id"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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-TABLE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,860
|
airline
|
bird:train.json:5885
|
Provide the destinations of flight number 1596.
|
SELECT DEST FROM Airlines WHERE OP_CARRIER_FL_NUM = 1596
|
[
"Provide",
"the",
"destinations",
"of",
"flight",
"number",
"1596",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "op_carrier_fl_num"
},
{
"id": 0,
"type": "table",
"value": "airlines"
},
{
"id": 1,
"type": "column",
"value": "dest"
},
{
"id": 3,
"type": "value",
"value": "1596"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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"
] |
1,861
|
world_development_indicators
|
bird:train.json:2091
|
Please list the countries under the lending category of the International Development Associations and have a external debt reporting finished by estimation.
|
SELECT ShortName, ExternalDebtReportingStatus FROM Country WHERE LendingCategory = 'IDA'
|
[
"Please",
"list",
"the",
"countries",
"under",
"the",
"lending",
"category",
"of",
"the",
"International",
"Development",
"Associations",
"and",
"have",
"a",
"external",
"debt",
"reporting",
"finished",
"by",
"estimation",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "externaldebtreportingstatus"
},
{
"id": 3,
"type": "column",
"value": "lendingcategory"
},
{
"id": 1,
"type": "column",
"value": "shortname"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "value",
"value": "IDA"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
16,
17,
18
]
},
{
"entity_id": 3,
"token_idxs": [
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O"
] |
1,862
|
retails
|
bird:train.json:6909
|
What is the name of the country of the supplier with the highest debt?
|
SELECT T2.n_name FROM supplier AS T1 INNER JOIN nation AS T2 ON T1.s_nationkey = T2.n_nationkey ORDER BY T1.s_suppkey DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"country",
"of",
"the",
"supplier",
"with",
"the",
"highest",
"debt",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "s_nationkey"
},
{
"id": 5,
"type": "column",
"value": "n_nationkey"
},
{
"id": 3,
"type": "column",
"value": "s_suppkey"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 0,
"type": "column",
"value": "n_name"
},
{
"id": 2,
"type": "table",
"value": "nation"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,863
|
hockey
|
bird:train.json:7613
|
List all players' given name who are good at both left and right hand and playing the forward position.
|
SELECT nameGiven FROM Master WHERE shootCatch IS NULL AND pos = 'F'
|
[
"List",
"all",
"players",
"'",
"given",
"name",
"who",
"are",
"good",
"at",
"both",
"left",
"and",
"right",
"hand",
"and",
"playing",
"the",
"forward",
"position",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "shootcatch"
},
{
"id": 1,
"type": "column",
"value": "namegiven"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 3,
"type": "column",
"value": "pos"
},
{
"id": 4,
"type": "value",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,864
|
cars
|
bird:train.json:3063
|
Among the cars with 8 cylinders, what is the name of the one that's the most expensive?
|
SELECT T1.car_name FROM data AS T1 INNER JOIN price AS T2 ON T1.ID = T2.ID WHERE T1.cylinders = 8 ORDER BY T2.price DESC LIMIT 1
|
[
"Among",
"the",
"cars",
"with",
"8",
"cylinders",
",",
"what",
"is",
"the",
"name",
"of",
"the",
"one",
"that",
"'s",
"the",
"most",
"expensive",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "cylinders"
},
{
"id": 0,
"type": "column",
"value": "car_name"
},
{
"id": 2,
"type": "table",
"value": "price"
},
{
"id": 5,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "table",
"value": "data"
},
{
"id": 6,
"type": "column",
"value": "id"
},
{
"id": 4,
"type": "value",
"value": "8"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"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-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,865
|
address_1
|
bird:test.json:817
|
Show me the city code of two cities with maximum distance.
|
SELECT city1_code , city2_code FROM Direct_distance ORDER BY distance DESC LIMIT 1
|
[
"Show",
"me",
"the",
"city",
"code",
"of",
"two",
"cities",
"with",
"maximum",
"distance",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "direct_distance"
},
{
"id": 1,
"type": "column",
"value": "city1_code"
},
{
"id": 2,
"type": "column",
"value": "city2_code"
},
{
"id": 3,
"type": "column",
"value": "distance"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,866
|
county_public_safety
|
spider:train_spider.json:2567
|
Which police forces operate in both counties that are located in the East and in the West?
|
SELECT Police_force FROM county_public_safety WHERE LOCATION = "East" INTERSECT SELECT Police_force FROM county_public_safety WHERE LOCATION = "West"
|
[
"Which",
"police",
"forces",
"operate",
"in",
"both",
"counties",
"that",
"are",
"located",
"in",
"the",
"East",
"and",
"in",
"the",
"West",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "county_public_safety"
},
{
"id": 1,
"type": "column",
"value": "police_force"
},
{
"id": 2,
"type": "column",
"value": "location"
},
{
"id": 3,
"type": "column",
"value": "East"
},
{
"id": 4,
"type": "column",
"value": "West"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1,
2
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,867
|
books
|
bird:train.json:6027
|
Indicate the ISBN13 of all the books that have less than 140 pages and more than 135.
|
SELECT isbn13 FROM book WHERE num_pages < 140 AND num_pages > 135
|
[
"Indicate",
"the",
"ISBN13",
"of",
"all",
"the",
"books",
"that",
"have",
"less",
"than",
"140",
"pages",
"and",
"more",
"than",
"135",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "num_pages"
},
{
"id": 1,
"type": "column",
"value": "isbn13"
},
{
"id": 0,
"type": "table",
"value": "book"
},
{
"id": 3,
"type": "value",
"value": "140"
},
{
"id": 4,
"type": "value",
"value": "135"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,868
|
retails
|
bird:train.json:6874
|
Please list the names of all the suppliers for the part with the highest retail price.
|
SELECT T3.s_phone FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN supplier AS T3 ON T2.ps_suppkey = T3.s_suppkey WHERE T1.p_name = 'hot spring dodger dim light' ORDER BY T1.p_size DESC LIMIT 1
|
[
"Please",
"list",
"the",
"names",
"of",
"all",
"the",
"suppliers",
"for",
"the",
"part",
"with",
"the",
"highest",
"retail",
"price",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "hot spring dodger dim light"
},
{
"id": 7,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 10,
"type": "column",
"value": "ps_partkey"
},
{
"id": 8,
"type": "column",
"value": "s_suppkey"
},
{
"id": 9,
"type": "column",
"value": "p_partkey"
},
{
"id": 1,
"type": "table",
"value": "supplier"
},
{
"id": 6,
"type": "table",
"value": "partsupp"
},
{
"id": 0,
"type": "column",
"value": "s_phone"
},
{
"id": 2,
"type": "column",
"value": "p_name"
},
{
"id": 4,
"type": "column",
"value": "p_size"
},
{
"id": 5,
"type": "table",
"value": "part"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,869
|
student_club
|
bird:dev.json:1393
|
Provide the full name and email address of the Student_Club's Secretary.
|
SELECT first_name, last_name, email FROM member WHERE position = 'Secretary'
|
[
"Provide",
"the",
"full",
"name",
"and",
"email",
"address",
"of",
"the",
"Student_Club",
"'s",
"Secretary",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 2,
"type": "column",
"value": "last_name"
},
{
"id": 5,
"type": "value",
"value": "Secretary"
},
{
"id": 4,
"type": "column",
"value": "position"
},
{
"id": 0,
"type": "table",
"value": "member"
},
{
"id": 3,
"type": "column",
"value": "email"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,870
|
advertising_agencies
|
bird:test.json:2113
|
Show all invoice ids and the number of payments for each invoice.
|
SELECT invoice_id , count(*) FROM Payments GROUP BY invoice_id
|
[
"Show",
"all",
"invoice",
"ids",
"and",
"the",
"number",
"of",
"payments",
"for",
"each",
"invoice",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "invoice_id"
},
{
"id": 0,
"type": "table",
"value": "payments"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"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-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,871
|
regional_sales
|
bird:train.json:2633
|
What is the percentage of total orders from stores in Orange County in 2018?
|
SELECT CAST(SUM(CASE WHEN T2.County = 'Orange County' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OrderNumber) FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE T1.OrderDate LIKE '%/%/18'
|
[
"What",
"is",
"the",
"percentage",
"of",
"total",
"orders",
"from",
"stores",
"in",
"Orange",
"County",
"in",
"2018",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "Store Locations"
},
{
"id": 11,
"type": "value",
"value": "Orange County"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 7,
"type": "column",
"value": "ordernumber"
},
{
"id": 2,
"type": "column",
"value": "orderdate"
},
{
"id": 5,
"type": "column",
"value": "_storeid"
},
{
"id": 4,
"type": "column",
"value": "storeid"
},
{
"id": 3,
"type": "value",
"value": "%/%/18"
},
{
"id": 10,
"type": "column",
"value": "county"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "0"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"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": [
11
]
},
{
"entity_id": 11,
"token_idxs": [
10
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
1,872
|
donor
|
bird:train.json:3297
|
List the poverty level of all the schools that received donations with the zip code "7079".
|
SELECT DISTINCT T2.poverty_level FROM donations AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T1.donor_zip = 7079
|
[
"List",
"the",
"poverty",
"level",
"of",
"all",
"the",
"schools",
"that",
"received",
"donations",
"with",
"the",
"zip",
"code",
"\"",
"7079",
"\"",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "poverty_level"
},
{
"id": 1,
"type": "table",
"value": "donations"
},
{
"id": 3,
"type": "column",
"value": "donor_zip"
},
{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 2,
"type": "table",
"value": "projects"
},
{
"id": 4,
"type": "value",
"value": "7079"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
1,873
|
chinook_1
|
spider:train_spider.json:843
|
What is the average unit price of tracks that belong to Jazz genre?
|
SELECT AVG(UnitPrice) FROM GENRE AS T1 JOIN TRACK AS T2 ON T1.GenreId = T2.GenreId WHERE T1.Name = "Jazz"
|
[
"What",
"is",
"the",
"average",
"unit",
"price",
"of",
"tracks",
"that",
"belong",
"to",
"Jazz",
"genre",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "unitprice"
},
{
"id": 5,
"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": "Jazz"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
1,874
|
document_management
|
spider:train_spider.json:4540
|
What are the different role codes for users, and how many users have each?
|
SELECT count(*) , role_code FROM users GROUP BY role_code
|
[
"What",
"are",
"the",
"different",
"role",
"codes",
"for",
"users",
",",
"and",
"how",
"many",
"users",
"have",
"each",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "role_code"
},
{
"id": 0,
"type": "table",
"value": "users"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
1,875
|
hockey
|
bird:train.json:7671
|
Among the players who died in Massachussets, how many of them have won an award?
|
SELECT COUNT(DISTINCT T1.playerID) FROM Master AS T1 INNER JOIN AwardsPlayers AS T2 ON T1.playerID = T2.playerID WHERE T1.deathState = 'MA'
|
[
"Among",
"the",
"players",
"who",
"died",
"in",
"Massachussets",
",",
"how",
"many",
"of",
"them",
"have",
"won",
"an",
"award",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "awardsplayers"
},
{
"id": 2,
"type": "column",
"value": "deathstate"
},
{
"id": 4,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "master"
},
{
"id": 3,
"type": "value",
"value": "MA"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,877
|
public_review_platform
|
bird:train.json:4100
|
How many businesses are not closed in the city of Mesa?
|
SELECT COUNT(business_id) FROM Business WHERE city = 'Mesa' AND active = 'true'
|
[
"How",
"many",
"businesses",
"are",
"not",
"closed",
"in",
"the",
"city",
"of",
"Mesa",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "business"
},
{
"id": 4,
"type": "column",
"value": "active"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 3,
"type": "value",
"value": "Mesa"
},
{
"id": 5,
"type": "value",
"value": "true"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,878
|
talkingdata
|
bird:train.json:1236
|
How many OPPO devices are there?
|
SELECT COUNT(device_id) FROM phone_brand_device_model2 WHERE phone_brand = 'OPPO'
|
[
"How",
"many",
"OPPO",
"devices",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "phone_brand_device_model2"
},
{
"id": 1,
"type": "column",
"value": "phone_brand"
},
{
"id": 3,
"type": "column",
"value": "device_id"
},
{
"id": 2,
"type": "value",
"value": "OPPO"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O"
] |
1,879
|
professional_basketball
|
bird:train.json:2900
|
How many players did not get more than 10 steals between the years 2000 and 2005?
|
SELECT COUNT(DISTINCT playerID) FROM player_allstar WHERE season_id BETWEEN 2000 AND 2005 AND steals <= 10
|
[
"How",
"many",
"players",
"did",
"not",
"get",
"more",
"than",
"10",
"steals",
"between",
"the",
"years",
"2000",
"and",
"2005",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "player_allstar"
},
{
"id": 2,
"type": "column",
"value": "season_id"
},
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 5,
"type": "column",
"value": "steals"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 4,
"type": "value",
"value": "2005"
},
{
"id": 6,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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13
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,880
|
university_rank
|
bird:test.json:1778
|
What are the names and codes for all majors ordered by their code?
|
SELECT major_name , major_code FROM Major ORDER BY major_code
|
[
"What",
"are",
"the",
"names",
"and",
"codes",
"for",
"all",
"majors",
"ordered",
"by",
"their",
"code",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "major_name"
},
{
"id": 2,
"type": "column",
"value": "major_code"
},
{
"id": 0,
"type": "table",
"value": "major"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,881
|
journal_committee
|
spider:train_spider.json:661
|
Show the names of editors that are on the committee of journals with sales bigger than 3000.
|
SELECT T2.Name FROM journal_committee AS T1 JOIN editor AS T2 ON T1.Editor_ID = T2.Editor_ID JOIN journal AS T3 ON T1.Journal_ID = T3.Journal_ID WHERE T3.Sales > 3000
|
[
"Show",
"the",
"names",
"of",
"editors",
"that",
"are",
"on",
"the",
"committee",
"of",
"journals",
"with",
"sales",
"bigger",
"than",
"3000",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "journal_committee"
},
{
"id": 6,
"type": "column",
"value": "journal_id"
},
{
"id": 7,
"type": "column",
"value": "editor_id"
},
{
"id": 1,
"type": "table",
"value": "journal"
},
{
"id": 5,
"type": "table",
"value": "editor"
},
{
"id": 2,
"type": "column",
"value": "sales"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "3000"
}
] |
[
{
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"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
1,882
|
movie_platform
|
bird:train.json:14
|
What is the percentage of rated movies were released in year 2021?
|
SELECT CAST(SUM(CASE WHEN T1.movie_release_year = 2021 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM movies AS T1 INNER JOIN ratings AS T2 ON T1.movie_id = T2.movie_id
|
[
"What",
"is",
"the",
"percentage",
"of",
"rated",
"movies",
"were",
"released",
"in",
"year",
"2021",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "movie_release_year"
},
{
"id": 2,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 7,
"type": "value",
"value": "2021"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 0,
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6
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{
"entity_id": 18,
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},
{
"entity_id": 19,
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
1,883
|
shipping
|
bird:train.json:5652
|
What is the brand of the truck that is used to ship by Zachery Hicks?
|
SELECT DISTINCT T1.make FROM truck AS T1 INNER JOIN shipment AS T2 ON T1.truck_id = T2.truck_id INNER JOIN driver AS T3 ON T3.driver_id = T2.driver_id WHERE T3.first_name = 'Zachery' AND T3.last_name = 'Hicks'
|
[
"What",
"is",
"the",
"brand",
"of",
"the",
"truck",
"that",
"is",
"used",
"to",
"ship",
"by",
"Zachery",
"Hicks",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "first_name"
},
{
"id": 4,
"type": "column",
"value": "driver_id"
},
{
"id": 7,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "table",
"value": "shipment"
},
{
"id": 9,
"type": "column",
"value": "truck_id"
},
{
"id": 6,
"type": "value",
"value": "Zachery"
},
{
"id": 1,
"type": "table",
"value": "driver"
},
{
"id": 2,
"type": "table",
"value": "truck"
},
{
"id": 8,
"type": "value",
"value": "Hicks"
},
{
"id": 0,
"type": "column",
"value": "make"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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{
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},
{
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}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
1,884
|
legislator
|
bird:train.json:4778
|
List the official full names of 10 legislators who have a YouTube account but no Instagram account.
|
SELECT T2.official_full_name FROM `social-media` AS T1 INNER JOIN current AS T2 ON T1.bioguide = T2.bioguide_id WHERE T1.facebook IS NOT NULL AND (T1.instagram IS NULL OR T1.instagram = '') LIMIT 10
|
[
"List",
"the",
"official",
"full",
"names",
"of",
"10",
"legislators",
"who",
"have",
"a",
"YouTube",
"account",
"but",
"no",
"Instagram",
"account",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "official_full_name"
},
{
"id": 1,
"type": "table",
"value": "social-media"
},
{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 6,
"type": "column",
"value": "instagram"
},
{
"id": 3,
"type": "column",
"value": "bioguide"
},
{
"id": 5,
"type": "column",
"value": "facebook"
},
{
"id": 2,
"type": "table",
"value": "current"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,885
|
european_football_1
|
bird:train.json:2792
|
Which team had more home victories in the 2021 season's matches of the Bundesliga division, Augsburg or Mainz?
|
SELECT CASE WHEN COUNT(CASE WHEN T1.HomeTeam = 'Augsburg' THEN 1 ELSE NULL END) - COUNT(CASE WHEN T1.HomeTeam = ' Mainz' THEN 1 ELSE NULL END) > 0 THEN 'Augsburg' ELSE 'Mainz' END FROM matchs AS T1 INNER JOIN divisions AS T2 ON T1.Div = T2.division WHERE T1.season = 2021 AND T1.FTR = 'H'
|
[
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"home",
"victories",
"in",
"the",
"2021",
"season",
"'s",
"matches",
"of",
"the",
"Bundesliga",
"division",
",",
"Augsburg",
"or",
"Mainz",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "divisions"
},
{
"id": 4,
"type": "column",
"value": "division"
},
{
"id": 9,
"type": "value",
"value": "Augsburg"
},
{
"id": 12,
"type": "column",
"value": "hometeam"
},
{
"id": 0,
"type": "table",
"value": "matchs"
},
{
"id": 5,
"type": "column",
"value": "season"
},
{
"id": 13,
"type": "value",
"value": " Mainz"
},
{
"id": 2,
"type": "value",
"value": "Mainz"
},
{
"id": 6,
"type": "value",
"value": "2021"
},
{
"id": 3,
"type": "column",
"value": "div"
},
{
"id": 7,
"type": "column",
"value": "ftr"
},
{
"id": 8,
"type": "value",
"value": "H"
},
{
"id": 10,
"type": "value",
"value": "0"
},
{
"id": 11,
"type": "value",
"value": "1"
}
] |
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{
"entity_id": 0,
"token_idxs": [
11
]
},
{
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19
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1
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
1,886
|
professional_basketball
|
bird:train.json:2927
|
How many turnovers per game did the assist champion had in the 2003 NBA season?
|
SELECT AVG(T2.turnovers) FROM players AS T1 INNER JOIN players_teams AS T2 ON T1.playerID = T2.playerID WHERE T2.year = 2003 GROUP BY T1.playerID, T2.assists ORDER BY T2.assists DESC LIMIT 1
|
[
"How",
"many",
"turnovers",
"per",
"game",
"did",
"the",
"assist",
"champion",
"had",
"in",
"the",
"2003",
"NBA",
"season",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "players_teams"
},
{
"id": 6,
"type": "column",
"value": "turnovers"
},
{
"id": 0,
"type": "column",
"value": "playerid"
},
{
"id": 1,
"type": "column",
"value": "assists"
},
{
"id": 2,
"type": "table",
"value": "players"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2003"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
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7
]
},
{
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3
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,887
|
student_club
|
bird:dev.json:1376
|
Among all the closed events, which event has the highest spend-to-budget ratio?
|
SELECT T2.event_name FROM budget AS T1 INNER JOIN event AS T2 ON T1.link_to_event = T2.event_id WHERE T2.status = 'Closed' ORDER BY T1.spent / T1.amount DESC LIMIT 1
|
[
"Among",
"all",
"the",
"closed",
"events",
",",
"which",
"event",
"has",
"the",
"highest",
"spend",
"-",
"to",
"-",
"budget",
"ratio",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "link_to_event"
},
{
"id": 0,
"type": "column",
"value": "event_name"
},
{
"id": 6,
"type": "column",
"value": "event_id"
},
{
"id": 1,
"type": "table",
"value": "budget"
},
{
"id": 3,
"type": "column",
"value": "status"
},
{
"id": 4,
"type": "value",
"value": "Closed"
},
{
"id": 8,
"type": "column",
"value": "amount"
},
{
"id": 2,
"type": "table",
"value": "event"
},
{
"id": 7,
"type": "column",
"value": "spent"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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15
]
},
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7
]
},
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3
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0
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"entity_id": 16,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
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}
] |
[
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
1,888
|
retails
|
bird:train.json:6706
|
How many customers are in debt?
|
SELECT COUNT(c_custkey) FROM customer WHERE c_acctbal < 0
|
[
"How",
"many",
"customers",
"are",
"in",
"debt",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "c_acctbal"
},
{
"id": 3,
"type": "column",
"value": "c_custkey"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
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},
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},
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 15,
"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"
] |
1,890
|
retail_world
|
bird:train.json:6659
|
What is the title of the employee who handled order id 10270?
|
SELECT T1.Title FROM Employees AS T1 INNER JOIN Orders AS T2 ON T1.EmployeeID = T2.EmployeeID WHERE T2.OrderID = 10257
|
[
"What",
"is",
"the",
"title",
"of",
"the",
"employee",
"who",
"handled",
"order",
"i",
"d",
"10270",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "employeeid"
},
{
"id": 1,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "orderid"
},
{
"id": 2,
"type": "table",
"value": "orders"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "value",
"value": "10257"
}
] |
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},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
1,892
|
candidate_poll
|
spider:train_spider.json:2407
|
What are the names of all people, ordered by their date of birth?
|
SELECT name FROM people ORDER BY date_of_birth
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"people",
",",
"ordered",
"by",
"their",
"date",
"of",
"birth",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "date_of_birth"
},
{
"id": 0,
"type": "table",
"value": "people"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
1,893
|
card_games
|
bird:dev.json:368
|
What is the percentage of borderless cards?
|
SELECT CAST(SUM(CASE WHEN borderColor = 'borderless' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(id) FROM cards
|
[
"What",
"is",
"the",
"percentage",
"of",
"borderless",
"cards",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "bordercolor"
},
{
"id": 6,
"type": "value",
"value": "borderless"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
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",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
1,895
|
voter_2
|
spider:train_spider.json:5473
|
What are the distinct last names of the students who have class president votes?
|
SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_President_VOTE
|
[
"What",
"are",
"the",
"distinct",
"last",
"names",
"of",
"the",
"students",
"who",
"have",
"class",
"president",
"votes",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "class_president_vote"
},
{
"id": 2,
"type": "table",
"value": "voting_record"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "lname"
},
{
"id": 3,
"type": "column",
"value": "stuid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
1,896
|
regional_sales
|
bird:train.json:2606
|
List out the name of orders which have delivery date of 6/13/2018.
|
SELECT DISTINCT T FROM ( SELECT IIF(DeliveryDate = '6/13/18', OrderNumber, NULL) AS T FROM `Sales Orders` ) WHERE T IS NOT NULL
|
[
"List",
"out",
"the",
"name",
"of",
"orders",
"which",
"have",
"delivery",
"date",
"of",
"6/13/2018",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 3,
"type": "column",
"value": "deliverydate"
},
{
"id": 2,
"type": "column",
"value": "ordernumber"
},
{
"id": 4,
"type": "value",
"value": "6/13/18"
},
{
"id": 0,
"type": "column",
"value": "t"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,897
|
professional_basketball
|
bird:train.json:2858
|
How many players with the first name Joe were drafted in 1970?
|
SELECT COUNT(DISTINCT playerID) FROM draft WHERE firstName = 'Joe' AND draftYear = 1970
|
[
"How",
"many",
"players",
"with",
"the",
"first",
"name",
"Joe",
"were",
"drafted",
"in",
"1970",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "firstname"
},
{
"id": 4,
"type": "column",
"value": "draftyear"
},
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 0,
"type": "table",
"value": "draft"
},
{
"id": 5,
"type": "value",
"value": "1970"
},
{
"id": 3,
"type": "value",
"value": "Joe"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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": []
},
{
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"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,898
|
entertainment_awards
|
spider:train_spider.json:4598
|
How many artworks are there?
|
SELECT count(*) FROM artwork
|
[
"How",
"many",
"artworks",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "artwork"
}
] |
[
{
"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"
] |
1,899
|
university
|
bird:train.json:8083
|
Please list the names of all the universities that scored under 60 in teaching in 2011 and are in the United States of America.
|
SELECT T3.university_name FROM ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id INNER JOIN university AS T3 ON T3.id = T2.university_id INNER JOIN country AS T4 ON T4.id = T3.country_id WHERE T4.country_name = 'United States of America' AND T2.year = 2011 AND T2.score < 60 AND T1.criteria_name = 'Teaching'
|
[
"Please",
"list",
"the",
"names",
"of",
"all",
"the",
"universities",
"that",
"scored",
"under",
"60",
"in",
"teaching",
"in",
"2011",
"and",
"are",
"in",
"the",
"United",
"States",
"of",
"America",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "United States of America"
},
{
"id": 14,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 16,
"type": "column",
"value": "ranking_criteria_id"
},
{
"id": 13,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 11,
"type": "column",
"value": "criteria_name"
},
{
"id": 15,
"type": "column",
"value": "university_id"
},
{
"id": 5,
"type": "column",
"value": "country_name"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 12,
"type": "value",
"value": "Teaching"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 9,
"type": "column",
"value": "score"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2011"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 10,
"type": "value",
"value": "60"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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7
]
},
{
"entity_id": 3,
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{
"entity_id": 4,
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{
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{
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},
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},
{
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9
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": [
13
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,900
|
cre_Theme_park
|
spider:train_spider.json:5919
|
What are the names and descriptions of the photos taken at the tourist attraction "film festival"?
|
SELECT T1.Name , T1.Description FROM PHOTOS AS T1 JOIN TOURIST_ATTRACTIONS AS T2 ON T1.Tourist_Attraction_ID = T2.Tourist_Attraction_ID WHERE T2.Name = "film festival"
|
[
"What",
"are",
"the",
"names",
"and",
"descriptions",
"of",
"the",
"photos",
"taken",
"at",
"the",
"tourist",
"attraction",
"\"",
"film",
"festival",
"\"",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "tourist_attraction_id"
},
{
"id": 3,
"type": "table",
"value": "tourist_attractions"
},
{
"id": 4,
"type": "column",
"value": "film festival"
},
{
"id": 1,
"type": "column",
"value": "description"
},
{
"id": 2,
"type": "table",
"value": "photos"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
1,901
|
movie_platform
|
bird:train.json:5
|
What is the average rating for movie titled 'When Will I Be Loved'?
|
SELECT AVG(T2.rating_score) FROM movies AS T1 INNER JOIN ratings AS T2 ON T1.movie_id = T2.movie_id WHERE T1.movie_title = 'When Will I Be Loved'
|
[
"What",
"is",
"the",
"average",
"rating",
"for",
"movie",
"titled",
"'",
"When",
"Will",
"I",
"Be",
"Loved",
"'",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "When Will I Be Loved"
},
{
"id": 4,
"type": "column",
"value": "rating_score"
},
{
"id": 2,
"type": "column",
"value": "movie_title"
},
{
"id": 5,
"type": "column",
"value": "movie_id"
},
{
"id": 1,
"type": "table",
"value": "ratings"
},
{
"id": 0,
"type": "table",
"value": "movies"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,902
|
voter_2
|
spider:train_spider.json:5482
|
Find the first and last names of all the female (sex is F) students who have president votes.
|
SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F"
|
[
"Find",
"the",
"first",
"and",
"last",
"names",
"of",
"all",
"the",
"female",
"(",
"sex",
"is",
"F",
")",
"students",
"who",
"have",
"president",
"votes",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "president_vote"
},
{
"id": 3,
"type": "table",
"value": "voting_record"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 6,
"type": "column",
"value": "stuid"
},
{
"id": 4,
"type": "column",
"value": "sex"
},
{
"id": 5,
"type": "column",
"value": "F"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
18,
19
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,903
|
olympics
|
bird:train.json:5012
|
How many kinds of events does athletics have?
|
SELECT COUNT(T2.event_name) FROM sport AS T1 INNER JOIN event AS T2 ON T1.id = T2.sport_id WHERE T1.sport_name = 'Athletics'
|
[
"How",
"many",
"kinds",
"of",
"events",
"does",
"athletics",
"have",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "sport_name"
},
{
"id": 4,
"type": "column",
"value": "event_name"
},
{
"id": 3,
"type": "value",
"value": "Athletics"
},
{
"id": 6,
"type": "column",
"value": "sport_id"
},
{
"id": 0,
"type": "table",
"value": "sport"
},
{
"id": 1,
"type": "table",
"value": "event"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"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",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O"
] |
1,904
|
pilot_1
|
bird:test.json:1151
|
Find the pilots who have either plane Piper Cub or plane F-14 Fighter.
|
SELECT pilot_name FROM pilotskills WHERE plane_name = 'Piper Cub' OR plane_name = 'F-14 Fighter'
|
[
"Find",
"the",
"pilots",
"who",
"have",
"either",
"plane",
"Piper",
"Cub",
"or",
"plane",
"F-14",
"Fighter",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "F-14 Fighter"
},
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "pilot_name"
},
{
"id": 2,
"type": "column",
"value": "plane_name"
},
{
"id": 3,
"type": "value",
"value": "Piper Cub"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,905
|
tracking_orders
|
spider:train_spider.json:6905
|
Give me the names of customers who have placed orders between 2009-01-01 and 2010-01-01.
|
SELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 ON T1.customer_id = T2.customer_id WHERE T2.date_order_placed >= "2009-01-01" AND T2.date_order_placed <= "2010-01-01"
|
[
"Give",
"me",
"the",
"names",
"of",
"customers",
"who",
"have",
"placed",
"orders",
"between",
"2009",
"-",
"01",
"-",
"01",
"and",
"2010",
"-",
"01",
"-",
"01",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "date_order_placed"
},
{
"id": 0,
"type": "column",
"value": "customer_name"
},
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "column",
"value": "2009-01-01"
},
{
"id": 6,
"type": "column",
"value": "2010-01-01"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11,
12,
13,
14,
15
]
},
{
"entity_id": 6,
"token_idxs": [
17,
18,
19,
20,
21
]
},
{
"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-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
1,906
|
machine_repair
|
spider:train_spider.json:2251
|
Show names of technicians and series of machines they are assigned to repair.
|
SELECT T3.Name , T2.Machine_series FROM repair_assignment AS T1 JOIN machine AS T2 ON T1.machine_id = T2.machine_id JOIN technician AS T3 ON T1.technician_ID = T3.technician_ID
|
[
"Show",
"names",
"of",
"technicians",
"and",
"series",
"of",
"machines",
"they",
"are",
"assigned",
"to",
"repair",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "repair_assignment"
},
{
"id": 1,
"type": "column",
"value": "machine_series"
},
{
"id": 5,
"type": "column",
"value": "technician_id"
},
{
"id": 2,
"type": "table",
"value": "technician"
},
{
"id": 6,
"type": "column",
"value": "machine_id"
},
{
"id": 4,
"type": "table",
"value": "machine"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O"
] |
1,907
|
phone_market
|
spider:train_spider.json:1990
|
For each phone, show its names and total number of stocks.
|
SELECT T2.Name , sum(T1.Num_of_stock) FROM phone_market AS T1 JOIN phone AS T2 ON T1.Phone_ID = T2.Phone_ID GROUP BY T2.Name
|
[
"For",
"each",
"phone",
",",
"show",
"its",
"names",
"and",
"total",
"number",
"of",
"stocks",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "phone_market"
},
{
"id": 3,
"type": "column",
"value": "num_of_stock"
},
{
"id": 4,
"type": "column",
"value": "phone_id"
},
{
"id": 2,
"type": "table",
"value": "phone"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
1,908
|
book_press
|
bird:test.json:1973
|
list all the names of press in descending order of the profit of the year.
|
SELECT name FROM press ORDER BY Year_Profits_billion DESC
|
[
"list",
"all",
"the",
"names",
"of",
"press",
"in",
"descending",
"order",
"of",
"the",
"profit",
"of",
"the",
"year",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "year_profits_billion"
},
{
"id": 0,
"type": "table",
"value": "press"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,909
|
club_1
|
spider:train_spider.json:4253
|
Give me the name of each club.
|
SELECT clubname FROM club
|
[
"Give",
"me",
"the",
"name",
"of",
"each",
"club",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "clubname"
},
{
"id": 0,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,910
|
codebase_community
|
bird:dev.json:644
|
Provide the last edit date and last edit user ID for the post "Detecting a given face in a database of facial images".
|
SELECT LastEditDate, LastEditorUserId FROM posts WHERE Title = 'Detecting a given face in a database of facial images'
|
[
"Provide",
"the",
"last",
"edit",
"date",
"and",
"last",
"edit",
"user",
"ID",
"for",
"the",
"post",
"\"",
"Detecting",
"a",
"given",
"face",
"in",
"a",
"database",
"of",
"facial",
"images",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Detecting a given face in a database of facial images"
},
{
"id": 2,
"type": "column",
"value": "lasteditoruserid"
},
{
"id": 1,
"type": "column",
"value": "lasteditdate"
},
{
"id": 0,
"type": "table",
"value": "posts"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
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"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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14,
15,
16,
17,
18,
19,
20,
21,
22,
23
]
},
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},
{
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"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,911
|
sakila_1
|
spider:train_spider.json:3001
|
Return the amount of the largest payment.
|
SELECT amount FROM payment ORDER BY amount DESC LIMIT 1
|
[
"Return",
"the",
"amount",
"of",
"the",
"largest",
"payment",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "payment"
},
{
"id": 1,
"type": "column",
"value": "amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,912
|
hospital_1
|
spider:train_spider.json:3902
|
what is the name and position of the head whose department has least number of employees?
|
SELECT T2.name , T2.position FROM department AS T1 JOIN physician AS T2 ON T1.head = T2.EmployeeID GROUP BY departmentID ORDER BY count(departmentID) LIMIT 1;
|
[
"what",
"is",
"the",
"name",
"and",
"position",
"of",
"the",
"head",
"whose",
"department",
"has",
"least",
"number",
"of",
"employees",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "departmentid"
},
{
"id": 3,
"type": "table",
"value": "department"
},
{
"id": 6,
"type": "column",
"value": "employeeid"
},
{
"id": 4,
"type": "table",
"value": "physician"
},
{
"id": 2,
"type": "column",
"value": "position"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "head"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
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15
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,913
|
allergy_1
|
spider:train_spider.json:487
|
Show the student id of the oldest student.
|
SELECT StuID FROM Student WHERE age = (SELECT max(age) FROM Student)
|
[
"Show",
"the",
"student",
"i",
"d",
"of",
"the",
"oldest",
"student",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "stuid"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,914
|
e_commerce
|
bird:test.json:48
|
What are the id, name, price and color of the products which have not been ordered for at least twice?
|
SELECT product_id , product_name , product_price , product_color FROM Products EXCEPT SELECT T1.product_id , T1.product_name , T1.product_price , T1.product_color FROM Products AS T1 JOIN Order_items AS T2 ON T1.product_id = T2.product_id JOIN Orders AS T3 ON T2.order_id = T3.order_id GROUP BY T1.product_id HAVING count(*) >= 2
|
[
"What",
"are",
"the",
"i",
"d",
",",
"name",
",",
"price",
"and",
"color",
"of",
"the",
"products",
"which",
"have",
"not",
"been",
"ordered",
"for",
"at",
"least",
"twice",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "product_price"
},
{
"id": 4,
"type": "column",
"value": "product_color"
},
{
"id": 2,
"type": "column",
"value": "product_name"
},
{
"id": 7,
"type": "table",
"value": "order_items"
},
{
"id": 1,
"type": "column",
"value": "product_id"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 8,
"type": "column",
"value": "order_id"
},
{
"id": 5,
"type": "table",
"value": "orders"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,915
|
video_games
|
bird:train.json:3362
|
When was the game titled 3DS Classic Collection released?
|
SELECT T1.release_year FROM game_platform AS T1 INNER JOIN game_publisher AS T2 ON T1.game_publisher_id = T2.id INNER JOIN game AS T3 ON T2.game_id = T3.id WHERE T3.game_name = '3DS Classic Collection'
|
[
"When",
"was",
"the",
"game",
"titled",
"3DS",
"Classic",
"Collection",
"released",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "3DS Classic Collection"
},
{
"id": 8,
"type": "column",
"value": "game_publisher_id"
},
{
"id": 5,
"type": "table",
"value": "game_publisher"
},
{
"id": 4,
"type": "table",
"value": "game_platform"
},
{
"id": 0,
"type": "column",
"value": "release_year"
},
{
"id": 2,
"type": "column",
"value": "game_name"
},
{
"id": 6,
"type": "column",
"value": "game_id"
},
{
"id": 1,
"type": "table",
"value": "game"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
1,916
|
european_football_2
|
bird:dev.json:1032
|
Give the name of the league with the highest matches of all time and how many matches were played in the said league.
|
SELECT t2.name, t1.max_count FROM League AS t2 JOIN (SELECT league_id, MAX(cnt) AS max_count FROM (SELECT league_id, COUNT(id) AS cnt FROM Match GROUP BY league_id) AS subquery) AS t1 ON t1.league_id = t2.id
|
[
"Give",
"the",
"name",
"of",
"the",
"league",
"with",
"the",
"highest",
"matches",
"of",
"all",
"time",
"and",
"how",
"many",
"matches",
"were",
"played",
"in",
"the",
"said",
"league",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "max_count"
},
{
"id": 3,
"type": "column",
"value": "league_id"
},
{
"id": 2,
"type": "table",
"value": "league"
},
{
"id": 6,
"type": "table",
"value": "match"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "cnt"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
22
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
21
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
1,917
|
soccer_2016
|
bird:train.json:1938
|
Among the South African players, how many were born before 4/11/1980?
|
SELECT SUM(CASE WHEN T1.DOB < '1980-4-11' THEN 1 ELSE 0 END) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_Id WHERE T2.Country_Name = 'South Africa'
|
[
"Among",
"the",
"South",
"African",
"players",
",",
"how",
"many",
"were",
"born",
"before",
"4/11/1980",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 3,
"type": "value",
"value": "South Africa"
},
{
"id": 4,
"type": "column",
"value": "country_id"
},
{
"id": 8,
"type": "value",
"value": "1980-4-11"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 7,
"type": "column",
"value": "dob"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2,
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,918
|
soccer_3
|
bird:test.json:15
|
Of players who have more than 2 wins, what is the country of the player who makes the most?
|
SELECT Country FROM player WHERE Wins_count > 2 ORDER BY Earnings DESC LIMIT 1
|
[
"Of",
"players",
"who",
"have",
"more",
"than",
"2",
"wins",
",",
"what",
"is",
"the",
"country",
"of",
"the",
"player",
"who",
"makes",
"the",
"most",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "wins_count"
},
{
"id": 4,
"type": "column",
"value": "earnings"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"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-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,919
|
thrombosis_prediction
|
bird:dev.json:1291
|
How many male patients have a normal level of both albumin and total protein?
|
SELECT COUNT(T1.ID) FROM Patient AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T1.SEX = 'M' AND T2.ALB > 3.5 AND T2.ALB < 5.5 AND T2.TP BETWEEN 6.0 AND 8.5
|
[
"How",
"many",
"male",
"patients",
"have",
"a",
"normal",
"level",
"of",
"both",
"albumin",
"and",
"total",
"protein",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 3,
"type": "column",
"value": "sex"
},
{
"id": 5,
"type": "column",
"value": "alb"
},
{
"id": 6,
"type": "value",
"value": "3.5"
},
{
"id": 7,
"type": "value",
"value": "5.5"
},
{
"id": 9,
"type": "value",
"value": "6.0"
},
{
"id": 10,
"type": "value",
"value": "8.5"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "column",
"value": "tp"
},
{
"id": 4,
"type": "value",
"value": "M"
}
] |
[
{
"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": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,920
|
european_football_2
|
bird:dev.json:1105
|
How was Francesco Migliore's attacking work rate on 2015/5/1?
|
SELECT t2.attacking_work_rate FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id WHERE t2.`date` LIKE '2015-05-01%' AND t1.player_name = 'Francesco Migliore'
|
[
"How",
"was",
"Francesco",
"Migliore",
"'s",
"attacking",
"work",
"rate",
"on",
"2015/5/1",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "attacking_work_rate"
},
{
"id": 7,
"type": "value",
"value": "Francesco Migliore"
},
{
"id": 2,
"type": "table",
"value": "player_attributes"
},
{
"id": 3,
"type": "column",
"value": "player_api_id"
},
{
"id": 5,
"type": "value",
"value": "2015-05-01%"
},
{
"id": 6,
"type": "column",
"value": "player_name"
},
{
"id": 1,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
2,
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",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,922
|
public_review_platform
|
bird:train.json:3877
|
What is the average business time for Yelp_Business no.1 on weekends?
|
SELECT T1.closing_time + 12 - T1.opening_time AS "avg opening hours" FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id WHERE T1.business_id = 1 AND (T2.day_of_week = 'Sunday' OR T2.day_of_week = 'Sunday')
|
[
"What",
"is",
"the",
"average",
"business",
"time",
"for",
"Yelp_Business",
"no.1",
"on",
"weekends",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "business_hours"
},
{
"id": 2,
"type": "column",
"value": "opening_time"
},
{
"id": 6,
"type": "column",
"value": "closing_time"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 8,
"type": "column",
"value": "day_of_week"
},
{
"id": 3,
"type": "column",
"value": "day_id"
},
{
"id": 9,
"type": "value",
"value": "Sunday"
},
{
"id": 1,
"type": "table",
"value": "days"
},
{
"id": 7,
"type": "value",
"value": "12"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
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",
"O",
"O",
"O"
] |
1,923
|
books
|
bird:train.json:6063
|
Which book by Hirohiko Araki was published on 6/6/2006?
|
SELECT T1.title FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'Hirohiko Araki' AND T1.publication_date = '2006-06-06'
|
[
"Which",
"book",
"by",
"Hirohiko",
"Araki",
"was",
"published",
"on",
"6/6/2006",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "publication_date"
},
{
"id": 6,
"type": "value",
"value": "Hirohiko Araki"
},
{
"id": 3,
"type": "table",
"value": "book_author"
},
{
"id": 5,
"type": "column",
"value": "author_name"
},
{
"id": 8,
"type": "value",
"value": "2006-06-06"
},
{
"id": 4,
"type": "column",
"value": "author_id"
},
{
"id": 9,
"type": "column",
"value": "book_id"
},
{
"id": 1,
"type": "table",
"value": "author"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
3,
4
]
},
{
"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",
"O",
"O",
"O",
"O",
"O"
] |
1,924
|
cre_Doc_and_collections
|
bird:test.json:714
|
For the document subset with the most number of different documents , what are the ids and names of the subset , as well as the number of documents ?
|
select t1.document_subset_id , t2.document_subset_name , count(distinct t1.document_object_id) from document_subset_members as t1 join document_subsets as t2 on t1.document_subset_id = t2.document_subset_id group by t1.document_subset_id order by count(*) desc limit 1;
|
[
"For",
"the",
"document",
"subset",
"with",
"the",
"most",
"number",
"of",
"different",
"documents",
",",
"what",
"are",
"the",
"ids",
"and",
"names",
"of",
"the",
"subset",
",",
"as",
"well",
"as",
"the",
"number",
"of",
"documents",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "document_subset_members"
},
{
"id": 1,
"type": "column",
"value": "document_subset_name"
},
{
"id": 0,
"type": "column",
"value": "document_subset_id"
},
{
"id": 4,
"type": "column",
"value": "document_object_id"
},
{
"id": 3,
"type": "table",
"value": "document_subsets"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
2,
3
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,925
|
customers_and_invoices
|
spider:train_spider.json:1575
|
Show the number of customers for each gender.
|
SELECT gender , count(*) FROM Customers GROUP BY gender
|
[
"Show",
"the",
"number",
"of",
"customers",
"for",
"each",
"gender",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "gender"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
1,926
|
professional_basketball
|
bird:train.json:2884
|
List out all the coach ID who have served more than 2 different teams.
|
SELECT coachID FROM coaches GROUP BY coachID HAVING COUNT(DISTINCT tmID) > 2
|
[
"List",
"out",
"all",
"the",
"coach",
"ID",
"who",
"have",
"served",
"more",
"than",
"2",
"different",
"teams",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "coaches"
},
{
"id": 1,
"type": "column",
"value": "coachid"
},
{
"id": 3,
"type": "column",
"value": "tmid"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"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",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,927
|
college_completion
|
bird:train.json:3714
|
Which city is "Rensselaer Polytechnic Institute" located in?
|
SELECT T FROM ( SELECT DISTINCT CASE WHEN chronname = 'Rensselaer Polytechnic Institute' THEN city ELSE NULL END AS T FROM institution_details ) WHERE T IS NOT NULL
|
[
"Which",
"city",
"is",
"\"",
"Rensselaer",
"Polytechnic",
"Institute",
"\"",
"located",
"in",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Rensselaer Polytechnic Institute"
},
{
"id": 1,
"type": "table",
"value": "institution_details"
},
{
"id": 3,
"type": "column",
"value": "chronname"
},
{
"id": 2,
"type": "column",
"value": "city"
},
{
"id": 0,
"type": "column",
"value": "t"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,928
|
address_1
|
bird:test.json:826
|
Give the average distance between Boston and other cities.
|
SELECT avg(distance) FROM Direct_distance AS T1 JOIN City AS T2 ON T1.city1_code = T2.city_code WHERE T2.city_name = "Boston"
|
[
"Give",
"the",
"average",
"distance",
"between",
"Boston",
"and",
"other",
"cities",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "direct_distance"
},
{
"id": 5,
"type": "column",
"value": "city1_code"
},
{
"id": 2,
"type": "column",
"value": "city_name"
},
{
"id": 6,
"type": "column",
"value": "city_code"
},
{
"id": 4,
"type": "column",
"value": "distance"
},
{
"id": 3,
"type": "column",
"value": "Boston"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
1,929
|
video_games
|
bird:train.json:3480
|
Calculate the total sales made by the games released in 2000.
|
SELECT SUM(T1.num_sales) FROM region_sales AS T1 INNER JOIN game_platform AS T2 ON T1.game_platform_id = T2.id WHERE T2.release_year = 2000
|
[
"Calculate",
"the",
"total",
"sales",
"made",
"by",
"the",
"games",
"released",
"in",
"2000",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "game_platform_id"
},
{
"id": 1,
"type": "table",
"value": "game_platform"
},
{
"id": 0,
"type": "table",
"value": "region_sales"
},
{
"id": 2,
"type": "column",
"value": "release_year"
},
{
"id": 4,
"type": "column",
"value": "num_sales"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,930
|
movie_2
|
bird:test.json:1808
|
What are the movie titles for ones that are played in the Odeon theater?
|
SELECT T1.title FROM movies AS T1 JOIN movietheaters AS T2 ON T1.code = T2.movie WHERE T2.name = 'Odeon'
|
[
"What",
"are",
"the",
"movie",
"titles",
"for",
"ones",
"that",
"are",
"played",
"in",
"the",
"Odeon",
"theater",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "movietheaters"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 4,
"type": "value",
"value": "Odeon"
},
{
"id": 6,
"type": "column",
"value": "movie"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
3
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,931
|
olympics
|
bird:train.json:5069
|
List down the games ID of games held in Tokyo.
|
SELECT T1.games_id FROM games_city AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.id WHERE T2.city_name = 'Tokyo'
|
[
"List",
"down",
"the",
"games",
"ID",
"of",
"games",
"held",
"in",
"Tokyo",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "games_city"
},
{
"id": 3,
"type": "column",
"value": "city_name"
},
{
"id": 0,
"type": "column",
"value": "games_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 4,
"type": "value",
"value": "Tokyo"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
1,932
|
flight_company
|
spider:train_spider.json:6380
|
Which of the airport names contains the word 'international'?
|
SELECT name FROM airport WHERE name LIKE '%international%'
|
[
"Which",
"of",
"the",
"airport",
"names",
"contains",
"the",
"word",
"'",
"international",
"'",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "%international%"
},
{
"id": 0,
"type": "table",
"value": "airport"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
1,933
|
shakespeare
|
bird:train.json:3027
|
Calculate the percentage of paragraphs in all chapters of "All's Well That Ends Well".
|
SELECT CAST(SUM(IIF(T1.Title = 'All''s Well That Ends Well', 1, 0)) AS REAL) * 100 / COUNT(T3.id) FROM works AS T1 INNER JOIN chapters AS T2 ON T1.id = T2.work_id INNER JOIN paragraphs AS T3 ON T2.id = T3.chapter_id
|
[
"Calculate",
"the",
"percentage",
"of",
"paragraphs",
"in",
"all",
"chapters",
"of",
"\"",
"All",
"'s",
"Well",
"That",
"Ends",
"Well",
"\"",
"."
] |
[
{
"id": 10,
"type": "value",
"value": "All's Well That Ends Well"
},
{
"id": 0,
"type": "table",
"value": "paragraphs"
},
{
"id": 4,
"type": "column",
"value": "chapter_id"
},
{
"id": 2,
"type": "table",
"value": "chapters"
},
{
"id": 6,
"type": "column",
"value": "work_id"
},
{
"id": 1,
"type": "table",
"value": "works"
},
{
"id": 9,
"type": "column",
"value": "title"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "1"
},
{
"id": 8,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
10,
11,
12,
13,
14,
15
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,934
|
cre_Theme_park
|
spider:train_spider.json:5903
|
Which location names contain the word "film"?
|
SELECT Location_Name FROM LOCATIONS WHERE Location_Name LIKE "%film%"
|
[
"Which",
"location",
"names",
"contain",
"the",
"word",
"\"",
"film",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "location_name"
},
{
"id": 0,
"type": "table",
"value": "locations"
},
{
"id": 2,
"type": "column",
"value": "%film%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
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