question_id
int64 0
16.1k
| db_id
stringclasses 259
values | dber_id
stringlengths 15
29
| question
stringlengths 16
325
| SQL
stringlengths 18
1.25k
| tokens
listlengths 4
62
| entities
listlengths 0
21
| entity_to_token
listlengths 20
20
| dber_tags
listlengths 4
62
|
|---|---|---|---|---|---|---|---|---|
2,252
|
cs_semester
|
bird:train.json:925
|
What is the name of the most difficult course?
|
SELECT name FROM course WHERE diff = ( SELECT MAX(diff) FROM course )
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"most",
"difficult",
"course",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "diff"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
2,253
|
document_management
|
spider:train_spider.json:4512
|
Return the type code of the document named "David CV".
|
SELECT document_type_code FROM documents WHERE document_name = "David CV"
|
[
"Return",
"the",
"type",
"code",
"of",
"the",
"document",
"named",
"\"",
"David",
"CV",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "document_type_code"
},
{
"id": 2,
"type": "column",
"value": "document_name"
},
{
"id": 0,
"type": "table",
"value": "documents"
},
{
"id": 3,
"type": "column",
"value": "David CV"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
2,254
|
dorm_1
|
spider:train_spider.json:5758
|
Find the name and capacity of the dorm with least number of amenities.
|
SELECT T1.dorm_name , T1.student_capacity FROM dorm AS T1 JOIN has_amenity AS T2 ON T1.dormid = T2.dormid JOIN dorm_amenity AS T3 ON T2.amenid = T3.amenid GROUP BY T2.dormid ORDER BY count(*) LIMIT 1
|
[
"Find",
"the",
"name",
"and",
"capacity",
"of",
"the",
"dorm",
"with",
"least",
"number",
"of",
"amenities",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "student_capacity"
},
{
"id": 3,
"type": "table",
"value": "dorm_amenity"
},
{
"id": 5,
"type": "table",
"value": "has_amenity"
},
{
"id": 1,
"type": "column",
"value": "dorm_name"
},
{
"id": 0,
"type": "column",
"value": "dormid"
},
{
"id": 6,
"type": "column",
"value": "amenid"
},
{
"id": 4,
"type": "table",
"value": "dorm"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": [
2,
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",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O"
] |
2,255
|
toxicology
|
bird:dev.json:276
|
Write down the atom IDs of the first and second atoms of triple bond type molecules.
|
SELECT T2.atom_id, T2.atom_id2 FROM bond AS T1 INNER JOIN connected AS T2 ON T1.bond_id = T2.bond_id WHERE T1.bond_type = '#'
|
[
"Write",
"down",
"the",
"atom",
"IDs",
"of",
"the",
"first",
"and",
"second",
"atoms",
"of",
"triple",
"bond",
"type",
"molecules",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "connected"
},
{
"id": 4,
"type": "column",
"value": "bond_type"
},
{
"id": 1,
"type": "column",
"value": "atom_id2"
},
{
"id": 0,
"type": "column",
"value": "atom_id"
},
{
"id": 6,
"type": "column",
"value": "bond_id"
},
{
"id": 2,
"type": "table",
"value": "bond"
},
{
"id": 5,
"type": "value",
"value": "#"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O"
] |
2,256
|
formula_1
|
bird:dev.json:959
|
What is the fastest lap number of the champion in 2009?
|
SELECT T1.fastestLap FROM results AS T1 INNER JOIN races AS T2 on T1.raceId = T2.raceId WHERE T2.year = 2009 AND T1.time LIKE '_:%:__.___'
|
[
"What",
"is",
"the",
"fastest",
"lap",
"number",
"of",
"the",
"champion",
"in",
"2009",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "fastestlap"
},
{
"id": 7,
"type": "value",
"value": "_:%:__.___"
},
{
"id": 1,
"type": "table",
"value": "results"
},
{
"id": 3,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2009"
},
{
"id": 6,
"type": "column",
"value": "time"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
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",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,257
|
manufactory_1
|
spider:train_spider.json:5286
|
Find the number of manufactures that are based in Tokyo or Beijing.
|
SELECT count(*) FROM manufacturers WHERE headquarter = 'Tokyo' OR headquarter = 'Beijing'
|
[
"Find",
"the",
"number",
"of",
"manufactures",
"that",
"are",
"based",
"in",
"Tokyo",
"or",
"Beijing",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 1,
"type": "column",
"value": "headquarter"
},
{
"id": 3,
"type": "value",
"value": "Beijing"
},
{
"id": 2,
"type": "value",
"value": "Tokyo"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,258
|
human_resources
|
bird:train.json:8973
|
What is the average salary of the worst performing managers?
|
SELECT AVG(CAST(REPLACE(SUBSTR(T1.salary, 4), ',', '') AS REAL)) FROM employee AS T1 INNER JOIN position AS T2 ON T1.positionID = T2.positionID WHERE T1.performance = 'Poor' AND T2.positiontitle = 'Manager'
|
[
"What",
"is",
"the",
"average",
"salary",
"of",
"the",
"worst",
"performing",
"managers",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "positiontitle"
},
{
"id": 3,
"type": "column",
"value": "performance"
},
{
"id": 2,
"type": "column",
"value": "positionid"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "table",
"value": "position"
},
{
"id": 6,
"type": "value",
"value": "Manager"
},
{
"id": 8,
"type": "column",
"value": "salary"
},
{
"id": 4,
"type": "value",
"value": "Poor"
},
{
"id": 7,
"type": "value",
"value": ","
},
{
"id": 9,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
4
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,259
|
college_1
|
spider:train_spider.json:3305
|
Find the name, address, number of students in the departments that have the top 3 highest number of students.
|
SELECT T2.dept_name , T2.dept_address , count(*) FROM student AS T1 JOIN department AS T2 ON T1.dept_code = T2.dept_code GROUP BY T1.dept_code ORDER BY count(*) DESC LIMIT 3
|
[
"Find",
"the",
"name",
",",
"address",
",",
"number",
"of",
"students",
"in",
"the",
"departments",
"that",
"have",
"the",
"top",
"3",
"highest",
"number",
"of",
"students",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "dept_address"
},
{
"id": 4,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "dept_code"
},
{
"id": 1,
"type": "column",
"value": "dept_name"
},
{
"id": 3,
"type": "table",
"value": "student"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,260
|
real_estate_rentals
|
bird:test.json:1430
|
What are the zip codes of properties which do not belong to users who own at most 2 properties?
|
SELECT T1.zip_postcode FROM Addresses AS T1 JOIN Properties AS T2 ON T1.address_id = T2.property_address_id WHERE T2.owner_user_id NOT IN ( SELECT owner_user_id FROM Properties GROUP BY owner_user_id HAVING count(*) <= 2 );
|
[
"What",
"are",
"the",
"zip",
"codes",
"of",
"properties",
"which",
"do",
"not",
"belong",
"to",
"users",
"who",
"own",
"at",
"most",
"2",
"properties",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "property_address_id"
},
{
"id": 5,
"type": "column",
"value": "owner_user_id"
},
{
"id": 0,
"type": "column",
"value": "zip_postcode"
},
{
"id": 2,
"type": "table",
"value": "properties"
},
{
"id": 3,
"type": "column",
"value": "address_id"
},
{
"id": 1,
"type": "table",
"value": "addresses"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,261
|
workshop_paper
|
spider:train_spider.json:5826
|
Show different colleges along with the number of authors of submission from each college.
|
SELECT College , COUNT(*) FROM submission GROUP BY College
|
[
"Show",
"different",
"colleges",
"along",
"with",
"the",
"number",
"of",
"authors",
"of",
"submission",
"from",
"each",
"college",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "submission"
},
{
"id": 1,
"type": "column",
"value": "college"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
2,262
|
app_store
|
bird:train.json:2536
|
List all the negative comments on the "Dog Run - Pet Dog Simulator" app.
|
SELECT Translated_Review FROM user_reviews WHERE App = 'Dog Run - Pet Dog Simulator' AND Sentiment = 'Negative'
|
[
"List",
"all",
"the",
"negative",
"comments",
"on",
"the",
"\"",
"Dog",
"Run",
"-",
"Pet",
"Dog",
"Simulator",
"\"",
"app",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Dog Run - Pet Dog Simulator"
},
{
"id": 1,
"type": "column",
"value": "translated_review"
},
{
"id": 0,
"type": "table",
"value": "user_reviews"
},
{
"id": 4,
"type": "column",
"value": "sentiment"
},
{
"id": 5,
"type": "value",
"value": "Negative"
},
{
"id": 2,
"type": "column",
"value": "app"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10,
11,
12,
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"O"
] |
2,263
|
tracking_orders
|
spider:train_spider.json:6887
|
what are the order id and customer id of the oldest order?
|
SELECT order_id , customer_id FROM orders ORDER BY date_order_placed LIMIT 1
|
[
"what",
"are",
"the",
"order",
"i",
"d",
"and",
"customer",
"i",
"d",
"of",
"the",
"oldest",
"order",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "date_order_placed"
},
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "column",
"value": "order_id"
},
{
"id": 0,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,264
|
conference
|
bird:test.json:1094
|
What are the names and nationalities of the people who did not participate in any ACL conferences?
|
SELECT name , nationality FROM staff WHERE staff_id NOT IN (SELECT T2.staff_id FROM Conference AS T1 JOIN Conference_participation AS T2 ON T1.conference_id = T2.conference_id WHERE T1.Conference_Name = "ACL")
|
[
"What",
"are",
"the",
"names",
"and",
"nationalities",
"of",
"the",
"people",
"who",
"did",
"not",
"participate",
"in",
"any",
"ACL",
"conferences",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "conference_participation"
},
{
"id": 6,
"type": "column",
"value": "conference_name"
},
{
"id": 8,
"type": "column",
"value": "conference_id"
},
{
"id": 2,
"type": "column",
"value": "nationality"
},
{
"id": 4,
"type": "table",
"value": "conference"
},
{
"id": 3,
"type": "column",
"value": "staff_id"
},
{
"id": 0,
"type": "table",
"value": "staff"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "ACL"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
12,
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
2,265
|
chicago_crime
|
bird:train.json:8739
|
Please state the district name where incident number JB106545 took place.
|
SELECT T1.case_number FROM Crime AS T1 INNER JOIN FBI_Code AS T2 ON T1.fbi_code_no = T2.fbi_code_no WHERE T2.title = 'Criminal Sexual Assault' AND T2.crime_against = 'Persons' AND T1.arrest = 'TRUE' LIMIT 3
|
[
"Please",
"state",
"the",
"district",
"name",
"where",
"incident",
"number",
"JB106545",
"took",
"place",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Criminal Sexual Assault"
},
{
"id": 6,
"type": "column",
"value": "crime_against"
},
{
"id": 0,
"type": "column",
"value": "case_number"
},
{
"id": 3,
"type": "column",
"value": "fbi_code_no"
},
{
"id": 2,
"type": "table",
"value": "fbi_code"
},
{
"id": 7,
"type": "value",
"value": "Persons"
},
{
"id": 8,
"type": "column",
"value": "arrest"
},
{
"id": 1,
"type": "table",
"value": "crime"
},
{
"id": 4,
"type": "column",
"value": "title"
},
{
"id": 9,
"type": "value",
"value": "TRUE"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
1
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,268
|
products_gen_characteristics
|
spider:train_spider.json:5590
|
What is the description of the color for most products?
|
SELECT t2.color_description FROM products AS t1 JOIN ref_colors AS t2 ON t1.color_code = t2.color_code GROUP BY t2.color_description ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"color",
"for",
"most",
"products",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "color_description"
},
{
"id": 2,
"type": "table",
"value": "ref_colors"
},
{
"id": 3,
"type": "column",
"value": "color_code"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,269
|
bike_1
|
spider:train_spider.json:169
|
What are the ids of stations that have latitude above 37.4 and never had bike availability below 7?
|
SELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7
|
[
"What",
"are",
"the",
"ids",
"of",
"stations",
"that",
"have",
"latitude",
"above",
"37.4",
"and",
"never",
"had",
"bike",
"availability",
"below",
"7",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "bikes_available"
},
{
"id": 2,
"type": "column",
"value": "station_id"
},
{
"id": 0,
"type": "table",
"value": "station"
},
{
"id": 1,
"type": "table",
"value": "status"
},
{
"id": 5,
"type": "value",
"value": "37.4"
},
{
"id": 4,
"type": "column",
"value": "lat"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "7"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
14,
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,270
|
professional_basketball
|
bird:train.json:2798
|
List the team name and the total wins of the team in year 2005 which has greater winning from the previous year.
|
SELECT T1.name, T1.won FROM teams AS T1 INNER JOIN ( SELECT * FROM teams WHERE year = 2004 ) AS T2 on T1.tmID = T2.tmID WHERE T1.year = 2005 and T1.won > T2.won
|
[
"List",
"the",
"team",
"name",
"and",
"the",
"total",
"wins",
"of",
"the",
"team",
"in",
"year",
"2005",
"which",
"has",
"greater",
"winning",
"from",
"the",
"previous",
"year",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "teams"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "tmid"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "2005"
},
{
"id": 6,
"type": "value",
"value": "2004"
},
{
"id": 1,
"type": "column",
"value": "won"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,271
|
chinook_1
|
spider:train_spider.json:826
|
What is the name of the artist with the greatest number of albums?
|
SELECT T2.Name FROM ALBUM AS T1 JOIN ARTIST AS T2 ON T1.ArtistId = T2.ArtistId GROUP BY T2.Name ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"artist",
"with",
"the",
"greatest",
"number",
"of",
"albums",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "artistid"
},
{
"id": 2,
"type": "table",
"value": "artist"
},
{
"id": 1,
"type": "table",
"value": "album"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,272
|
address_1
|
bird:test.json:800
|
Give the country with the fewest students.
|
SELECT T1.country FROM City AS T1 JOIN Student AS T2 ON T1.city_code = T2.city_code GROUP BY T1.country ORDER BY count(*) LIMIT 1
|
[
"Give",
"the",
"country",
"with",
"the",
"fewest",
"students",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "city_code"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,273
|
cre_Theme_park
|
spider:train_spider.json:5962
|
Find the names of the tourist attractions that is either accessible by bus or at address 254 Ottilie Junction.
|
SELECT T2.Name FROM Locations AS T1 JOIN Tourist_Attractions AS T2 ON T1.Location_ID = T2.Location_ID WHERE T1.Address = "254 Ottilie Junction" OR T2.How_to_Get_There = "bus"
|
[
"Find",
"the",
"names",
"of",
"the",
"tourist",
"attractions",
"that",
"is",
"either",
"accessible",
"by",
"bus",
"or",
"at",
"address",
"254",
"Ottilie",
"Junction",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "254 Ottilie Junction"
},
{
"id": 2,
"type": "table",
"value": "tourist_attractions"
},
{
"id": 6,
"type": "column",
"value": "how_to_get_there"
},
{
"id": 3,
"type": "column",
"value": "location_id"
},
{
"id": 1,
"type": "table",
"value": "locations"
},
{
"id": 4,
"type": "column",
"value": "address"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "bus"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
16,
17,
18
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
2,274
|
performance_attendance
|
spider:train_spider.json:1318
|
Show the names of members and the location of performances they attended in ascending alphabetical order of their names.
|
SELECT T2.Name , T3.Location FROM member_attendance AS T1 JOIN member AS T2 ON T1.Member_ID = T2.Member_ID JOIN performance AS T3 ON T1.Performance_ID = T3.Performance_ID ORDER BY T2.Name ASC
|
[
"Show",
"the",
"names",
"of",
"members",
"and",
"the",
"location",
"of",
"performances",
"they",
"attended",
"in",
"ascending",
"alphabetical",
"order",
"of",
"their",
"names",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "member_attendance"
},
{
"id": 5,
"type": "column",
"value": "performance_id"
},
{
"id": 2,
"type": "table",
"value": "performance"
},
{
"id": 6,
"type": "column",
"value": "member_id"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 4,
"type": "table",
"value": "member"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"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",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,275
|
student_assessment
|
spider:train_spider.json:86
|
What are the cell phone numbers of the candidates that received an assessment code of "Fail"?
|
SELECT T3.cell_mobile_number FROM candidates AS T1 JOIN candidate_assessments AS T2 ON T1.candidate_id = T2.candidate_id JOIN people AS T3 ON T1.candidate_id = T3.person_id WHERE T2.asessment_outcome_code = "Fail"
|
[
"What",
"are",
"the",
"cell",
"phone",
"numbers",
"of",
"the",
"candidates",
"that",
"received",
"an",
"assessment",
"code",
"of",
"\"",
"Fail",
"\"",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "asessment_outcome_code"
},
{
"id": 5,
"type": "table",
"value": "candidate_assessments"
},
{
"id": 0,
"type": "column",
"value": "cell_mobile_number"
},
{
"id": 6,
"type": "column",
"value": "candidate_id"
},
{
"id": 4,
"type": "table",
"value": "candidates"
},
{
"id": 7,
"type": "column",
"value": "person_id"
},
{
"id": 1,
"type": "table",
"value": "people"
},
{
"id": 3,
"type": "column",
"value": "Fail"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4,
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,276
|
app_store
|
bird:train.json:2561
|
List down the rating for the App Learn C++.
|
SELECT DISTINCT Rating FROM playstore WHERE App = 'Learn C++'
|
[
"List",
"down",
"the",
"rating",
"for",
"the",
"App",
"Learn",
"C++",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "playstore"
},
{
"id": 3,
"type": "value",
"value": "Learn C++"
},
{
"id": 1,
"type": "column",
"value": "rating"
},
{
"id": 2,
"type": "column",
"value": "app"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"O"
] |
2,277
|
retails
|
bird:train.json:6829
|
What is the account balance of the supplier with the most parts?
|
SELECT T.s_acctbal FROM ( SELECT T1.s_acctbal, COUNT(T2.ps_suppkey) AS num FROM supplier AS T1 INNER JOIN partsupp AS T2 ON T1.s_suppkey = T2.ps_suppkey GROUP BY T1.s_suppkey ) AS T ORDER BY T.num DESC LIMIT 1
|
[
"What",
"is",
"the",
"account",
"balance",
"of",
"the",
"supplier",
"with",
"the",
"most",
"parts",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 0,
"type": "column",
"value": "s_acctbal"
},
{
"id": 2,
"type": "column",
"value": "s_suppkey"
},
{
"id": 3,
"type": "table",
"value": "supplier"
},
{
"id": 4,
"type": "table",
"value": "partsupp"
},
{
"id": 1,
"type": "column",
"value": "num"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,278
|
shipping
|
bird:train.json:5595
|
Where was the destination city of shipment no.1701?
|
SELECT T2.city_name FROM shipment AS T1 INNER JOIN city AS T2 ON T1.city_id = T2.city_id WHERE T1.ship_id = '1701'
|
[
"Where",
"was",
"the",
"destination",
"city",
"of",
"shipment",
"no.1701",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "city_name"
},
{
"id": 1,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "column",
"value": "ship_id"
},
{
"id": 5,
"type": "column",
"value": "city_id"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "1701"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"O"
] |
2,279
|
chinook_1
|
spider:train_spider.json:821
|
Hom many albums does the artist "Metallica" have?
|
SELECT COUNT(*) FROM ALBUM AS T1 JOIN ARTIST AS T2 ON T1.ArtistId = T2.ArtistId WHERE T2.Name = "Metallica"
|
[
"Hom",
"many",
"albums",
"does",
"the",
"artist",
"\"",
"Metallica",
"\"",
"have",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Metallica"
},
{
"id": 4,
"type": "column",
"value": "artistid"
},
{
"id": 1,
"type": "table",
"value": "artist"
},
{
"id": 0,
"type": "table",
"value": "album"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,280
|
movielens
|
bird:train.json:2324
|
How many female actors have been played a role in any of French or USA movies?
|
SELECT COUNT(T2.actorid) FROM movies AS T1 INNER JOIN movies2actors AS T2 ON T1.movieid = T2.movieid WHERE T1.country IN ('France', 'USA')
|
[
"How",
"many",
"female",
"actors",
"have",
"been",
"played",
"a",
"role",
"in",
"any",
"of",
"French",
"or",
"USA",
"movies",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "movies2actors"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "actorid"
},
{
"id": 6,
"type": "column",
"value": "movieid"
},
{
"id": 0,
"type": "table",
"value": "movies"
},
{
"id": 3,
"type": "value",
"value": "France"
},
{
"id": 4,
"type": "value",
"value": "USA"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,281
|
medicine_enzyme_interaction
|
spider:train_spider.json:937
|
List the names and the locations that the enzymes can make an effect.
|
SELECT name , LOCATION FROM enzyme
|
[
"List",
"the",
"names",
"and",
"the",
"locations",
"that",
"the",
"enzymes",
"can",
"make",
"an",
"effect",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "enzyme"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,282
|
medicine_enzyme_interaction
|
spider:train_spider.json:935
|
List the name of enzymes in descending lexicographical order.
|
SELECT name FROM enzyme ORDER BY name DESC
|
[
"List",
"the",
"name",
"of",
"enzymes",
"in",
"descending",
"lexicographical",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "enzyme"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,283
|
legislator
|
bird:train.json:4863
|
What is the ratio between famous current legislators and famous historical legislators?
|
SELECT CAST(COUNT(CASE WHEN wikipedia_id IS NOT NULL THEN bioguide_id ELSE 0 END) AS REAL) * 100 / ( SELECT COUNT(CASE WHEN wikipedia_id IS NOT NULL THEN bioguide_id ELSE 0 END) FROM historical ) FROM current
|
[
"What",
"is",
"the",
"ratio",
"between",
"famous",
"current",
"legislators",
"and",
"famous",
"historical",
"legislators",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "wikipedia_id"
},
{
"id": 4,
"type": "column",
"value": "bioguide_id"
},
{
"id": 2,
"type": "table",
"value": "historical"
},
{
"id": 0,
"type": "table",
"value": "current"
},
{
"id": 1,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
2,284
|
financial
|
bird:dev.json:151
|
Please list the name of the districts with accounts that made withdrawal transactions.
|
SELECT DISTINCT T1.A2 FROM district AS T1 INNER JOIN account AS T2 ON T1.district_id = T2.district_id INNER JOIN trans AS T3 ON T2.account_id = T3.account_id WHERE T3.type = 'VYDAJ'
|
[
"Please",
"list",
"the",
"name",
"of",
"the",
"districts",
"with",
"accounts",
"that",
"made",
"withdrawal",
"transactions",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "district_id"
},
{
"id": 6,
"type": "column",
"value": "account_id"
},
{
"id": 4,
"type": "table",
"value": "district"
},
{
"id": 5,
"type": "table",
"value": "account"
},
{
"id": 1,
"type": "table",
"value": "trans"
},
{
"id": 3,
"type": "value",
"value": "VYDAJ"
},
{
"id": 2,
"type": "column",
"value": "type"
},
{
"id": 0,
"type": "column",
"value": "a2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,285
|
farm
|
spider:train_spider.json:53
|
What are the official names of cities that have population over 1500 or less than 500?
|
SELECT Official_Name FROM city WHERE Population > 1500 OR Population < 500
|
[
"What",
"are",
"the",
"official",
"names",
"of",
"cities",
"that",
"have",
"population",
"over",
"1500",
"or",
"less",
"than",
"500",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "official_name"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 3,
"type": "value",
"value": "1500"
},
{
"id": 4,
"type": "value",
"value": "500"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,288
|
tracking_orders
|
spider:train_spider.json:6931
|
What is the name of the customer who has the largest number of orders?
|
SELECT T1.customer_name FROM customers AS T1 JOIN orders AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"customer",
"who",
"has",
"the",
"largest",
"number",
"of",
"orders",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"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",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,289
|
retail_world
|
bird:train.json:6402
|
What is the last name of the employees who must report to the Vice President of Sales?
|
SELECT LastName FROM Employees WHERE ReportsTo = ( SELECT EmployeeID FROM Employees WHERE Title = 'Vice President, Sales' )
|
[
"What",
"is",
"the",
"last",
"name",
"of",
"the",
"employees",
"who",
"must",
"report",
"to",
"the",
"Vice",
"President",
"of",
"Sales",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Vice President, Sales"
},
{
"id": 3,
"type": "column",
"value": "employeeid"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 2,
"type": "column",
"value": "reportsto"
},
{
"id": 1,
"type": "column",
"value": "lastname"
},
{
"id": 4,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13,
14,
15,
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,290
|
beer_factory
|
bird:train.json:5341
|
What is the average review given by a subscriber?
|
SELECT AVG(T2.StarRating) FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID WHERE T1.SubscribedToEmailList = 'TRUE'
|
[
"What",
"is",
"the",
"average",
"review",
"given",
"by",
"a",
"subscriber",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "subscribedtoemaillist"
},
{
"id": 1,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 4,
"type": "column",
"value": "starrating"
},
{
"id": 5,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "value",
"value": "TRUE"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2,
3,
4
]
},
{
"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",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,291
|
college_completion
|
bird:train.json:3730
|
Give the state and name of institutions in year of data release from 2010 to 2012 with black students.
|
SELECT DISTINCT T1.state, T1.chronname FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T2.race = 'B' AND T2.year BETWEEN 2010 AND 2012
|
[
"Give",
"the",
"state",
"and",
"name",
"of",
"institutions",
"in",
"year",
"of",
"data",
"release",
"from",
"2010",
"to",
"2012",
"with",
"black",
"students",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "institution_details"
},
{
"id": 3,
"type": "table",
"value": "institution_grads"
},
{
"id": 1,
"type": "column",
"value": "chronname"
},
{
"id": 4,
"type": "column",
"value": "unitid"
},
{
"id": 0,
"type": "column",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "race"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "2010"
},
{
"id": 9,
"type": "value",
"value": "2012"
},
{
"id": 6,
"type": "value",
"value": "B"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"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": [
8
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O"
] |
2,292
|
human_resources
|
bird:train.json:8969
|
How many male Regional Managers are there?
|
SELECT COUNT(*) FROM employee AS T1 INNER JOIN position AS T2 ON T1.positionID = T2.positionID WHERE T2.positiontitle = 'Regional Manager' AND T1.gender = 'M'
|
[
"How",
"many",
"male",
"Regional",
"Managers",
"are",
"there",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Regional Manager"
},
{
"id": 3,
"type": "column",
"value": "positiontitle"
},
{
"id": 2,
"type": "column",
"value": "positionid"
},
{
"id": 0,
"type": "table",
"value": "employee"
},
{
"id": 1,
"type": "table",
"value": "position"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 6,
"type": "value",
"value": "M"
}
] |
[
{
"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": [
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-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
2,293
|
soccer_3
|
bird:test.json:22
|
Show names of clubs in descending order of average earnings of players belonging.
|
SELECT T1.Name FROM club AS T1 JOIN player AS T2 ON T1.Club_ID = T2.Club_ID GROUP BY T1.Club_ID ORDER BY avg(T2.Earnings) DESC
|
[
"Show",
"names",
"of",
"clubs",
"in",
"descending",
"order",
"of",
"average",
"earnings",
"of",
"players",
"belonging",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "earnings"
},
{
"id": 0,
"type": "column",
"value": "club_id"
},
{
"id": 3,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O"
] |
2,294
|
mondial_geo
|
bird:train.json:8365
|
How many lakes are there in the 4th most populous African country with a republican form of government?
|
SELECT COUNT(*) FROM geo_lake WHERE Country = ( SELECT T4.Code FROM ( SELECT T2.Code, T2.Population FROM encompasses AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code INNER JOIN politics AS T3 ON T1.Country = T3.Country WHERE T1.Continent = 'Africa' AND T1.Percentage = 100 AND T3.Government = 'republic' ORDER BY Population DESC LIMIT 4 ) AS T4 ORDER BY population ASC LIMIT 1 )
|
[
"How",
"many",
"lakes",
"are",
"there",
"in",
"the",
"4th",
"most",
"populous",
"African",
"country",
"with",
"a",
"republican",
"form",
"of",
"government",
"?"
] |
[
{
"id": 5,
"type": "table",
"value": "encompasses"
},
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 9,
"type": "column",
"value": "percentage"
},
{
"id": 11,
"type": "column",
"value": "government"
},
{
"id": 7,
"type": "column",
"value": "continent"
},
{
"id": 0,
"type": "table",
"value": "geo_lake"
},
{
"id": 4,
"type": "table",
"value": "politics"
},
{
"id": 12,
"type": "value",
"value": "republic"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 6,
"type": "table",
"value": "country"
},
{
"id": 8,
"type": "value",
"value": "Africa"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 10,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
17
]
},
{
"entity_id": 12,
"token_idxs": [
14
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
2,295
|
flight_4
|
spider:train_spider.json:6867
|
For each country and airline name, how many routes are there?
|
SELECT T1.country , T1.name , count(*) FROM airlines AS T1 JOIN routes AS T2 ON T1.alid = T2.alid GROUP BY T1.country , T1.name
|
[
"For",
"each",
"country",
"and",
"airline",
"name",
",",
"how",
"many",
"routes",
"are",
"there",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "airlines"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "routes"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "alid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
2,297
|
e_learning
|
spider:train_spider.json:3773
|
Return the addresses of the course authors or tutors whose personal name is "Cathrine".
|
SELECT address_line_1 FROM Course_Authors_and_Tutors WHERE personal_name = "Cathrine"
|
[
"Return",
"the",
"addresses",
"of",
"the",
"course",
"authors",
"or",
"tutors",
"whose",
"personal",
"name",
"is",
"\"",
"Cathrine",
"\"",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 1,
"type": "column",
"value": "address_line_1"
},
{
"id": 2,
"type": "column",
"value": "personal_name"
},
{
"id": 3,
"type": "column",
"value": "Cathrine"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6,
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,298
|
film_rank
|
spider:train_spider.json:4146
|
List the title of films that do not have any market estimation.
|
SELECT Title FROM film WHERE Film_ID NOT IN (SELECT Film_ID FROM film_market_estimation)
|
[
"List",
"the",
"title",
"of",
"films",
"that",
"do",
"not",
"have",
"any",
"market",
"estimation",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "film_market_estimation"
},
{
"id": 2,
"type": "column",
"value": "film_id"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,299
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6414
|
Return the id of the project that has the fewest corresponding documents.
|
SELECT project_id FROM Documents GROUP BY project_id ORDER BY count(*) ASC LIMIT 1
|
[
"Return",
"the",
"i",
"d",
"of",
"the",
"project",
"that",
"has",
"the",
"fewest",
"corresponding",
"documents",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "project_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"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",
"O",
"B-TABLE",
"O"
] |
2,300
|
superhero
|
bird:dev.json:803
|
What is the power ID of cryokinesis?
|
SELECT id FROM superpower WHERE power_name = 'Cryokinesis'
|
[
"What",
"is",
"the",
"power",
"ID",
"of",
"cryokinesis",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Cryokinesis"
},
{
"id": 0,
"type": "table",
"value": "superpower"
},
{
"id": 2,
"type": "column",
"value": "power_name"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,301
|
products_for_hire
|
spider:train_spider.json:1968
|
How many different product types are there?
|
SELECT count(DISTINCT product_type_code) FROM products_for_hire
|
[
"How",
"many",
"different",
"product",
"types",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "products_for_hire"
},
{
"id": 1,
"type": "column",
"value": "product_type_code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5,
6
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"I-TABLE",
"O"
] |
2,302
|
european_football_2
|
bird:dev.json:1031
|
At present, calculate for the player's age who have a sprint speed of no less than 97 between 2013 to 2015.
|
SELECT DISTINCT DATETIME() - T2.birthday age FROM Player_Attributes AS t1 INNER JOIN Player AS t2 ON t1.player_api_id = t2.player_api_id WHERE STRFTIME('%Y',t1.`date`) >= '2013' AND STRFTIME('%Y',t1.`date`) <= '2015' AND t1.sprint_speed >= 97
|
[
"At",
"present",
",",
"calculate",
"for",
"the",
"player",
"'s",
"age",
"who",
"have",
"a",
"sprint",
"speed",
"of",
"no",
"less",
"than",
"97",
"between",
"2013",
"to",
"2015",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "player_attributes"
},
{
"id": 3,
"type": "column",
"value": "player_api_id"
},
{
"id": 6,
"type": "column",
"value": "sprint_speed"
},
{
"id": 2,
"type": "column",
"value": "birthday"
},
{
"id": 1,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "value",
"value": "2013"
},
{
"id": 5,
"type": "value",
"value": "2015"
},
{
"id": 9,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "97"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
20
]
},
{
"entity_id": 5,
"token_idxs": [
22
]
},
{
"entity_id": 6,
"token_idxs": [
12,
13
]
},
{
"entity_id": 7,
"token_idxs": [
18
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
0
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,303
|
bike_1
|
spider:train_spider.json:187
|
What are the ids and durations of the trips with the top 3 durations?
|
SELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3
|
[
"What",
"are",
"the",
"ids",
"and",
"durations",
"of",
"the",
"trips",
"with",
"the",
"top",
"3",
"durations",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "duration"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O"
] |
2,304
|
student_loan
|
bird:train.json:4502
|
What is the organization enlisted by student168?
|
SELECT organ FROM enlist WHERE name = 'student168'
|
[
"What",
"is",
"the",
"organization",
"enlisted",
"by",
"student168",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "student168"
},
{
"id": 0,
"type": "table",
"value": "enlist"
},
{
"id": 1,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,305
|
public_review_platform
|
bird:train.json:3980
|
Mention the user average star, elite year and the compliment type of user ID 6027 whereby number of compliments reach uber.
|
SELECT T2.user_average_stars, T1.year_id, T4.compliment_type, T3.number_of_compliments FROM Elite AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id INNER JOIN Users_Compliments AS T3 ON T2.user_id = T3.user_id INNER JOIN Compliments AS T4 ON T3.compliment_id = T4.compliment_id INNER JOIN Years AS T5 ON T1.year_id = T5.year_id WHERE T3.number_of_compliments = 'Uber' AND T3.user_id = 6027
|
[
"Mention",
"the",
"user",
"average",
"star",
",",
"elite",
"year",
"and",
"the",
"compliment",
"type",
"of",
"user",
"ID",
"6027",
"whereby",
"number",
"of",
"compliments",
"reach",
"uber",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "number_of_compliments"
},
{
"id": 0,
"type": "column",
"value": "user_average_stars"
},
{
"id": 9,
"type": "table",
"value": "users_compliments"
},
{
"id": 2,
"type": "column",
"value": "compliment_type"
},
{
"id": 10,
"type": "column",
"value": "compliment_id"
},
{
"id": 5,
"type": "table",
"value": "compliments"
},
{
"id": 1,
"type": "column",
"value": "year_id"
},
{
"id": 7,
"type": "column",
"value": "user_id"
},
{
"id": 4,
"type": "table",
"value": "years"
},
{
"id": 11,
"type": "table",
"value": "elite"
},
{
"id": 12,
"type": "table",
"value": "users"
},
{
"id": 6,
"type": "value",
"value": "Uber"
},
{
"id": 8,
"type": "value",
"value": "6027"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
17,
18
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"entity_id": 6,
"token_idxs": [
21
]
},
{
"entity_id": 7,
"token_idxs": [
13,
14
]
},
{
"entity_id": 8,
"token_idxs": [
15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
10
]
},
{
"entity_id": 11,
"token_idxs": [
6
]
},
{
"entity_id": 12,
"token_idxs": [
2
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,306
|
music_platform_2
|
bird:train.json:7949
|
What is the rating and category of the podcast entitled Sitcomadon?
|
SELECT DISTINCT T3.rating, T1.category FROM categories AS T1 INNER JOIN podcasts AS T2 ON T2.podcast_id = T1.podcast_id INNER JOIN reviews AS T3 ON T3.podcast_id = T2.podcast_id WHERE T2.title = 'Sitcomadon'
|
[
"What",
"is",
"the",
"rating",
"and",
"category",
"of",
"the",
"podcast",
"entitled",
"Sitcomadon",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Sitcomadon"
},
{
"id": 5,
"type": "table",
"value": "categories"
},
{
"id": 7,
"type": "column",
"value": "podcast_id"
},
{
"id": 1,
"type": "column",
"value": "category"
},
{
"id": 6,
"type": "table",
"value": "podcasts"
},
{
"id": 2,
"type": "table",
"value": "reviews"
},
{
"id": 0,
"type": "column",
"value": "rating"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,307
|
mondial_geo
|
bird:train.json:8486
|
List the full name its capital of all the countries with parliamentary democracy government.
|
SELECT T1.Capital FROM country AS T1 INNER JOIN politics AS T2 ON T1.Code = T2.Country WHERE T2.Government = 'parliamentary democracy'
|
[
"List",
"the",
"full",
"name",
"its",
"capital",
"of",
"all",
"the",
"countries",
"with",
"parliamentary",
"democracy",
"government",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "parliamentary democracy"
},
{
"id": 3,
"type": "column",
"value": "government"
},
{
"id": 2,
"type": "table",
"value": "politics"
},
{
"id": 0,
"type": "column",
"value": "capital"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
2,308
|
world_development_indicators
|
bird:train.json:2163
|
Which countries use Euro as their currency? List down the table name.
|
SELECT TableName FROM Country WHERE CurrencyUnit = 'Euro'
|
[
"Which",
"countries",
"use",
"Euro",
"as",
"their",
"currency",
"?",
"List",
"down",
"the",
"table",
"name",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "currencyunit"
},
{
"id": 1,
"type": "column",
"value": "tablename"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "value",
"value": "Euro"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
11,
12
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,309
|
thrombosis_prediction
|
bird:dev.json:1196
|
What is the most common sign of patients with SLE disease?
|
SELECT Symptoms FROM Examination WHERE Diagnosis = 'SLE' GROUP BY Symptoms ORDER BY COUNT(Symptoms) DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"common",
"sign",
"of",
"patients",
"with",
"SLE",
"disease",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 2,
"type": "column",
"value": "diagnosis"
},
{
"id": 1,
"type": "column",
"value": "symptoms"
},
{
"id": 3,
"type": "value",
"value": "SLE"
}
] |
[
{
"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": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,310
|
professional_basketball
|
bird:train.json:2896
|
What is the percentage of offense rebounds from the total rebounds of the players in year 2000.
|
SELECT CAST(SUM(T2.o_rebounds) AS REAL) * 100 / SUM(T2.rebounds) FROM players_teams AS T1 INNER JOIN player_allstar AS T2 ON T1.playerID = T2.playerID WHERE T1.year = 2000
|
[
"What",
"is",
"the",
"percentage",
"of",
"offense",
"rebounds",
"from",
"the",
"total",
"rebounds",
"of",
"the",
"players",
"in",
"year",
"2000",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "player_allstar"
},
{
"id": 0,
"type": "table",
"value": "players_teams"
},
{
"id": 7,
"type": "column",
"value": "o_rebounds"
},
{
"id": 4,
"type": "column",
"value": "playerid"
},
{
"id": 6,
"type": "column",
"value": "rebounds"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2000"
},
{
"id": 5,
"type": "value",
"value": "100"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,311
|
cre_Students_Information_Systems
|
bird:test.json:511
|
List the start time and the end time of the students' addresses for the students who have 2 transcripts.
|
SELECT date_from , date_to FROM Students_Addresses WHERE student_id IN ( SELECT student_id FROM Transcripts GROUP BY student_id HAVING count(*) = 2 )
|
[
"List",
"the",
"start",
"time",
"and",
"the",
"end",
"time",
"of",
"the",
"students",
"'",
"addresses",
"for",
"the",
"students",
"who",
"have",
"2",
"transcripts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "students_addresses"
},
{
"id": 4,
"type": "table",
"value": "transcripts"
},
{
"id": 3,
"type": "column",
"value": "student_id"
},
{
"id": 1,
"type": "column",
"value": "date_from"
},
{
"id": 2,
"type": "column",
"value": "date_to"
},
{
"id": 5,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11,
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
19
]
},
{
"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",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,312
|
tracking_share_transactions
|
spider:train_spider.json:5884
|
What are the details of the lots which are not used in any transactions?
|
SELECT lot_details FROM Lots EXCEPT SELECT T1.lot_details FROM Lots AS T1 JOIN transactions_lots AS T2 ON T1.lot_id = T2.lot_id
|
[
"What",
"are",
"the",
"details",
"of",
"the",
"lots",
"which",
"are",
"not",
"used",
"in",
"any",
"transactions",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "transactions_lots"
},
{
"id": 1,
"type": "column",
"value": "lot_details"
},
{
"id": 3,
"type": "column",
"value": "lot_id"
},
{
"id": 0,
"type": "table",
"value": "lots"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,313
|
sales_in_weather
|
bird:train.json:8141
|
Please list the dates on which the temperature of station no.2 was above the 30-year normal.
|
SELECT `date` FROM weather WHERE station_nbr = 2 AND depart > 0
|
[
"Please",
"list",
"the",
"dates",
"on",
"which",
"the",
"temperature",
"of",
"station",
"no.2",
"was",
"above",
"the",
"30",
"-",
"year",
"normal",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "station_nbr"
},
{
"id": 0,
"type": "table",
"value": "weather"
},
{
"id": 4,
"type": "column",
"value": "depart"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "value",
"value": "2"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O"
] |
2,314
|
student_assessment
|
spider:train_spider.json:56
|
which course has most number of registered students?
|
SELECT T1.course_name FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_Id GROUP BY T1.course_id ORDER BY count(*) DESC LIMIT 1
|
[
"which",
"course",
"has",
"most",
"number",
"of",
"registered",
"students",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "student_course_registrations"
},
{
"id": 1,
"type": "column",
"value": "course_name"
},
{
"id": 0,
"type": "column",
"value": "course_id"
},
{
"id": 2,
"type": "table",
"value": "courses"
}
] |
[
{
"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": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,315
|
bakery_1
|
bird:test.json:1492
|
What are the ids with apple flavor?
|
SELECT id FROM goods WHERE flavor = "Apple"
|
[
"What",
"are",
"the",
"ids",
"with",
"apple",
"flavor",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "flavor"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 3,
"type": "column",
"value": "Apple"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,316
|
retail_world
|
bird:train.json:6323
|
What is the name of the supplier company for Aniseed Syrup?
|
SELECT T2.CompanyName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.ProductName = 'Aniseed Syrup'
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"supplier",
"company",
"for",
"Aniseed",
"Syrup",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Aniseed Syrup"
},
{
"id": 0,
"type": "column",
"value": "companyname"
},
{
"id": 3,
"type": "column",
"value": "productname"
},
{
"id": 5,
"type": "column",
"value": "supplierid"
},
{
"id": 2,
"type": "table",
"value": "suppliers"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9,
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,317
|
sakila_1
|
spider:train_spider.json:2939
|
What are the title and id of the film which has a rental rate of 0.99 and an inventory of below 3?
|
SELECT title , film_id FROM film WHERE rental_rate = 0.99 INTERSECT SELECT T1.title , T1.film_id FROM film AS T1 JOIN inventory AS T2 ON T1.film_id = T2.film_id GROUP BY T1.film_id HAVING count(*) < 3
|
[
"What",
"are",
"the",
"title",
"and",
"i",
"d",
"of",
"the",
"film",
"which",
"has",
"a",
"rental",
"rate",
"of",
"0.99",
"and",
"an",
"inventory",
"of",
"below",
"3",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "rental_rate"
},
{
"id": 5,
"type": "table",
"value": "inventory"
},
{
"id": 1,
"type": "column",
"value": "film_id"
},
{
"id": 2,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "film"
},
{
"id": 4,
"type": "value",
"value": "0.99"
},
{
"id": 6,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
13,
14
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
19
]
},
{
"entity_id": 6,
"token_idxs": [
22
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,318
|
school_finance
|
spider:train_spider.json:1900
|
How many budgets are above 3000 in year 2001 or before?
|
SELECT count(*) FROM budget WHERE budgeted > 3000 AND YEAR <= 2001
|
[
"How",
"many",
"budgets",
"are",
"above",
"3000",
"in",
"year",
"2001",
"or",
"before",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "budgeted"
},
{
"id": 0,
"type": "table",
"value": "budget"
},
{
"id": 2,
"type": "value",
"value": "3000"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2001"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"O"
] |
2,319
|
cs_semester
|
bird:train.json:875
|
How many students took the hardest course?
|
SELECT COUNT(T1.student_id) FROM registration AS T1 INNER JOIN course AS T2 ON T1.course_id = T2.course_id WHERE T2.diff = 5
|
[
"How",
"many",
"students",
"took",
"the",
"hardest",
"course",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "registration"
},
{
"id": 4,
"type": "column",
"value": "student_id"
},
{
"id": 5,
"type": "column",
"value": "course_id"
},
{
"id": 1,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "column",
"value": "diff"
},
{
"id": 3,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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"
] |
2,320
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4247
|
Which employees do not destroy any document? Find their employee ids.
|
SELECT employee_id FROM Employees EXCEPT SELECT Destroyed_by_Employee_ID FROM Documents_to_be_destroyed
|
[
"Which",
"employees",
"do",
"not",
"destroy",
"any",
"document",
"?",
"Find",
"their",
"employee",
"ids",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "documents_to_be_destroyed"
},
{
"id": 3,
"type": "column",
"value": "destroyed_by_employee_id"
},
{
"id": 2,
"type": "column",
"value": "employee_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,321
|
film_rank
|
spider:train_spider.json:4157
|
Return the title of the film with the highest high estimate?
|
SELECT t1.title FROM film AS T1 JOIN film_market_estimation AS T2 ON T1.Film_ID = T2.Film_ID ORDER BY high_estimate DESC LIMIT 1
|
[
"Return",
"the",
"title",
"of",
"the",
"film",
"with",
"the",
"highest",
"high",
"estimate",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "film_market_estimation"
},
{
"id": 3,
"type": "column",
"value": "high_estimate"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 1,
"type": "table",
"value": "film"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,322
|
college_1
|
spider:train_spider.json:3279
|
What is department name and office for the professor whose last name is Heffington?
|
SELECT T3.dept_name , T2.prof_office FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num JOIN department AS T3 ON T2.dept_code = T3.dept_code WHERE T1.emp_lname = 'Heffington'
|
[
"What",
"is",
"department",
"name",
"and",
"office",
"for",
"the",
"professor",
"whose",
"last",
"name",
"is",
"Heffington",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "prof_office"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 4,
"type": "value",
"value": "Heffington"
},
{
"id": 0,
"type": "column",
"value": "dept_name"
},
{
"id": 3,
"type": "column",
"value": "emp_lname"
},
{
"id": 6,
"type": "table",
"value": "professor"
},
{
"id": 7,
"type": "column",
"value": "dept_code"
},
{
"id": 5,
"type": "table",
"value": "employee"
},
{
"id": 8,
"type": "column",
"value": "emp_num"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,323
|
driving_school
|
spider:train_spider.json:6690
|
How much in total does customer with first name as Carole and last name as Bernhard paid?
|
SELECT sum(T1.amount_payment) FROM Customer_Payments AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T2.first_name = "Carole" AND T2.last_name = "Bernhard"
|
[
"How",
"much",
"in",
"total",
"does",
"customer",
"with",
"first",
"name",
"as",
"Carole",
"and",
"last",
"name",
"as",
"Bernhard",
"paid",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customer_payments"
},
{
"id": 2,
"type": "column",
"value": "amount_payment"
},
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 7,
"type": "column",
"value": "Bernhard"
},
{
"id": 5,
"type": "column",
"value": "Carole"
}
] |
[
{
"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": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": [
12,
13
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
2,324
|
entrepreneur
|
spider:train_spider.json:2286
|
Return the weights of entrepreneurs, ordered descending by amount of money requested.
|
SELECT T2.Weight FROM entrepreneur AS T1 JOIN people AS T2 ON T1.People_ID = T2.People_ID ORDER BY T1.Money_Requested DESC
|
[
"Return",
"the",
"weights",
"of",
"entrepreneurs",
",",
"ordered",
"descending",
"by",
"amount",
"of",
"money",
"requested",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "money_requested"
},
{
"id": 1,
"type": "table",
"value": "entrepreneur"
},
{
"id": 4,
"type": "column",
"value": "people_id"
},
{
"id": 0,
"type": "column",
"value": "weight"
},
{
"id": 2,
"type": "table",
"value": "people"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,325
|
club_1
|
spider:train_spider.json:4311
|
What are the names of the clubs that have "Davis Steven" as a member?
|
SELECT DISTINCT t1.clubname FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t3.fname = "Davis" AND t3.lname = "Steven"
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"clubs",
"that",
"have",
"\"",
"Davis",
"Steven",
"\"",
"as",
"a",
"member",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "member_of_club"
},
{
"id": 0,
"type": "column",
"value": "clubname"
},
{
"id": 1,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "column",
"value": "Steven"
},
{
"id": 9,
"type": "column",
"value": "clubid"
},
{
"id": 4,
"type": "column",
"value": "stuid"
},
{
"id": 5,
"type": "column",
"value": "fname"
},
{
"id": 6,
"type": "column",
"value": "Davis"
},
{
"id": 7,
"type": "column",
"value": "lname"
},
{
"id": 2,
"type": "table",
"value": "club"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": [
11
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,326
|
student_loan
|
bird:train.json:4369
|
For the students who have been absent from school for the longest time, how many months have they been absent?
|
SELECT MAX(month) FROM longest_absense_from_school
|
[
"For",
"the",
"students",
"who",
"have",
"been",
"absent",
"from",
"school",
"for",
"the",
"longest",
"time",
",",
"how",
"many",
"months",
"have",
"they",
"been",
"absent",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "longest_absense_from_school"
},
{
"id": 1,
"type": "column",
"value": "month"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
2,327
|
shakespeare
|
bird:train.json:3021
|
How many chapters include the character name "First Witch"?
|
SELECT COUNT(T2.chapter_id) FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T1.CharName = 'First Witch'
|
[
"How",
"many",
"chapters",
"include",
"the",
"character",
"name",
"\"",
"First",
"Witch",
"\"",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "character_id"
},
{
"id": 3,
"type": "value",
"value": "First Witch"
},
{
"id": 0,
"type": "table",
"value": "characters"
},
{
"id": 1,
"type": "table",
"value": "paragraphs"
},
{
"id": 4,
"type": "column",
"value": "chapter_id"
},
{
"id": 2,
"type": "column",
"value": "charname"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6
]
},
{
"entity_id": 3,
"token_idxs": [
8,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
2,328
|
behavior_monitoring
|
spider:train_spider.json:3104
|
Find the id and first name of the student that has the most number of assessment notes?
|
SELECT T1.student_id , T2.first_name FROM Assessment_Notes AS T1 JOIN Students AS T2 ON T1.student_id = T2.student_id GROUP BY T1.student_id ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"i",
"d",
"and",
"first",
"name",
"of",
"the",
"student",
"that",
"has",
"the",
"most",
"number",
"of",
"assessment",
"notes",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "assessment_notes"
},
{
"id": 0,
"type": "column",
"value": "student_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 3,
"type": "table",
"value": "students"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
16,
17
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,329
|
hospital_1
|
spider:train_spider.json:3991
|
What are the names of patients who are not taking the medication of Procrastin-X.
|
SELECT name FROM patient EXCEPT SELECT T1.name FROM patient AS T1 JOIN Prescribes AS T2 ON T2.Patient = T1.SSN JOIN Medication AS T3 ON T2.Medication = T3.Code WHERE T3.name = 'Procrastin-X'
|
[
"What",
"are",
"the",
"names",
"of",
"patients",
"who",
"are",
"not",
"taking",
"the",
"medication",
"of",
"Procrastin",
"-",
"X."
] |
[
{
"id": 3,
"type": "value",
"value": "Procrastin-X"
},
{
"id": 2,
"type": "table",
"value": "medication"
},
{
"id": 4,
"type": "table",
"value": "prescribes"
},
{
"id": 5,
"type": "column",
"value": "medication"
},
{
"id": 0,
"type": "table",
"value": "patient"
},
{
"id": 7,
"type": "column",
"value": "patient"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "column",
"value": "code"
},
{
"id": 8,
"type": "column",
"value": "ssn"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE"
] |
2,330
|
financial
|
bird:dev.json:135
|
After making a credit card withdrawal, how many account/s with monthly issuance has a negative balance?
|
SELECT COUNT(T1.account_id) FROM trans AS T1 INNER JOIN account AS T2 ON T1.account_id = T2.account_id WHERE T1.balance < 0 AND T1.operation = 'VYBER KARTOU' AND T2.frequency = 'POPLATEK MESICNE'
|
[
"After",
"making",
"a",
"credit",
"card",
"withdrawal",
",",
"how",
"many",
"account",
"/",
"s",
"with",
"monthly",
"issuance",
"has",
"a",
"negative",
"balance",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "POPLATEK MESICNE"
},
{
"id": 6,
"type": "value",
"value": "VYBER KARTOU"
},
{
"id": 2,
"type": "column",
"value": "account_id"
},
{
"id": 5,
"type": "column",
"value": "operation"
},
{
"id": 7,
"type": "column",
"value": "frequency"
},
{
"id": 1,
"type": "table",
"value": "account"
},
{
"id": 3,
"type": "column",
"value": "balance"
},
{
"id": 0,
"type": "table",
"value": "trans"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
18
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,331
|
college_1
|
spider:train_spider.json:3219
|
Find the total number of hours have done for all students in each department.
|
SELECT sum(stu_hrs) , dept_code FROM student GROUP BY dept_code
|
[
"Find",
"the",
"total",
"number",
"of",
"hours",
"have",
"done",
"for",
"all",
"students",
"in",
"each",
"department",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "dept_code"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stu_hrs"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
2,332
|
european_football_2
|
bird:dev.json:1080
|
Among the players whose preferred foot was the left foot when attacking, how many of them would remain in his position when the team attacked?
|
SELECT COUNT(player_api_id) FROM Player_Attributes WHERE preferred_foot = 'left' AND attacking_work_rate = 'low'
|
[
"Among",
"the",
"players",
"whose",
"preferred",
"foot",
"was",
"the",
"left",
"foot",
"when",
"attacking",
",",
"how",
"many",
"of",
"them",
"would",
"remain",
"in",
"his",
"position",
"when",
"the",
"team",
"attacked",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "attacking_work_rate"
},
{
"id": 0,
"type": "table",
"value": "player_attributes"
},
{
"id": 2,
"type": "column",
"value": "preferred_foot"
},
{
"id": 1,
"type": "column",
"value": "player_api_id"
},
{
"id": 3,
"type": "value",
"value": "left"
},
{
"id": 5,
"type": "value",
"value": "low"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,333
|
talkingdata
|
bird:train.json:1047
|
How many users are there in the Home Decoration category?
|
SELECT COUNT(T1.app_id) FROM app_labels AS T1 INNER JOIN label_categories AS T2 ON T2.label_id = T1.label_id WHERE T2.category = 'Home Decoration'
|
[
"How",
"many",
"users",
"are",
"there",
"in",
"the",
"Home",
"Decoration",
"category",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "label_categories"
},
{
"id": 3,
"type": "value",
"value": "Home Decoration"
},
{
"id": 0,
"type": "table",
"value": "app_labels"
},
{
"id": 2,
"type": "column",
"value": "category"
},
{
"id": 5,
"type": "column",
"value": "label_id"
},
{
"id": 4,
"type": "column",
"value": "app_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
2,334
|
network_2
|
spider:train_spider.json:4480
|
What is the total number of people who has no friend living in the city of Austin.
|
SELECT count(DISTINCT name) FROM PersonFriend WHERE friend NOT IN (SELECT name FROM person WHERE city = 'Austin')
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"people",
"who",
"has",
"no",
"friend",
"living",
"in",
"the",
"city",
"of",
"Austin",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "personfriend"
},
{
"id": 2,
"type": "column",
"value": "friend"
},
{
"id": 3,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "value",
"value": "Austin"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,335
|
manufactory_1
|
spider:train_spider.json:5293
|
Return the total revenue of companies with headquarters in Tokyo or Taiwan.
|
SELECT sum(revenue) FROM manufacturers WHERE Headquarter = 'Tokyo' OR Headquarter = 'Taiwan'
|
[
"Return",
"the",
"total",
"revenue",
"of",
"companies",
"with",
"headquarters",
"in",
"Tokyo",
"or",
"Taiwan",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "manufacturers"
},
{
"id": 2,
"type": "column",
"value": "headquarter"
},
{
"id": 1,
"type": "column",
"value": "revenue"
},
{
"id": 4,
"type": "value",
"value": "Taiwan"
},
{
"id": 3,
"type": "value",
"value": "Tokyo"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
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",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,336
|
cre_Doc_Tracking_DB
|
spider:train_spider.json:4230
|
Show the location codes with at least 3 documents.
|
SELECT location_code FROM Document_locations GROUP BY location_code HAVING count(*) >= 3
|
[
"Show",
"the",
"location",
"codes",
"with",
"at",
"least",
"3",
"documents",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "document_locations"
},
{
"id": 1,
"type": "column",
"value": "location_code"
},
{
"id": 2,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,337
|
tracking_software_problems
|
spider:train_spider.json:5381
|
Sort all the distinct product names in alphabetical order.
|
SELECT DISTINCT product_name FROM product ORDER BY product_name
|
[
"Sort",
"all",
"the",
"distinct",
"product",
"names",
"in",
"alphabetical",
"order",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 0,
"type": "table",
"value": "product"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,338
|
movie_3
|
bird:train.json:9260
|
Indicate the title of all the films rated as 'Adults Only'.
|
SELECT title FROM film WHERE rating = 'NC-17'
|
[
"Indicate",
"the",
"title",
"of",
"all",
"the",
"films",
"rated",
"as",
"'",
"Adults",
"Only",
"'",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "value",
"value": "NC-17"
},
{
"id": 0,
"type": "table",
"value": "film"
}
] |
[
{
"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",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,339
|
simpson_episodes
|
bird:train.json:4353
|
What is the episode ID that received 2 stars and 9 votes?
|
SELECT episode_id FROM Vote WHERE stars = 2 AND votes = 9;
|
[
"What",
"is",
"the",
"episode",
"ID",
"that",
"received",
"2",
"stars",
"and",
"9",
"votes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "episode_id"
},
{
"id": 2,
"type": "column",
"value": "stars"
},
{
"id": 4,
"type": "column",
"value": "votes"
},
{
"id": 0,
"type": "table",
"value": "vote"
},
{
"id": 3,
"type": "value",
"value": "2"
},
{
"id": 5,
"type": "value",
"value": "9"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,341
|
social_media
|
bird:train.json:794
|
What is the average number of tweets posted by the users in a city in Argentina?
|
SELECT SUM(CASE WHEN T2.City = 'Buenos Aires' THEN 1.0 ELSE 0 END) / COUNT(T1.TweetID) AS avg FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T2.Country = 'Argentina'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"tweets",
"posted",
"by",
"the",
"users",
"in",
"a",
"city",
"in",
"Argentina",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "Buenos Aires"
},
{
"id": 4,
"type": "column",
"value": "locationid"
},
{
"id": 3,
"type": "value",
"value": "Argentina"
},
{
"id": 1,
"type": "table",
"value": "location"
},
{
"id": 0,
"type": "table",
"value": "twitter"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "tweetid"
},
{
"id": 8,
"type": "column",
"value": "city"
},
{
"id": 7,
"type": "value",
"value": "1.0"
},
{
"id": 6,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,342
|
college_completion
|
bird:train.json:3745
|
What is the website address of the institution with the highest number of White degree-seeking students at 2-year institutions in 2008?
|
SELECT T1.site FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T2.race = 'W' AND T2.cohort = '2y all' AND T2.year = 2008 ORDER BY T2.grad_cohort DESC LIMIT 1
|
[
"What",
"is",
"the",
"website",
"address",
"of",
"the",
"institution",
"with",
"the",
"highest",
"number",
"of",
"White",
"degree",
"-",
"seeking",
"students",
"at",
"2",
"-",
"year",
"institutions",
"in",
"2008",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "institution_details"
},
{
"id": 2,
"type": "table",
"value": "institution_grads"
},
{
"id": 3,
"type": "column",
"value": "grad_cohort"
},
{
"id": 4,
"type": "column",
"value": "unitid"
},
{
"id": 7,
"type": "column",
"value": "cohort"
},
{
"id": 8,
"type": "value",
"value": "2y all"
},
{
"id": 0,
"type": "column",
"value": "site"
},
{
"id": 5,
"type": "column",
"value": "race"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "2008"
},
{
"id": 6,
"type": "value",
"value": "W"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
22
]
},
{
"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": [
21
]
},
{
"entity_id": 10,
"token_idxs": [
24
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,343
|
california_schools
|
bird:dev.json:24
|
Give the names of the schools with the percent eligible for free meals in K-12 is more than 0.1 and test takers whose test score is greater than or equal to 1500?
|
SELECT T2.`School Name` FROM satscores AS T1 INNER JOIN frpm AS T2 ON T1.cds = T2.CDSCode WHERE CAST(T2.`Free Meal Count (K-12)` AS REAL) / T2.`Enrollment (K-12)` > 0.1 AND T1.NumGE1500 > 0
|
[
"Give",
"the",
"names",
"of",
"the",
"schools",
"with",
"the",
"percent",
"eligible",
"for",
"free",
"meals",
"in",
"K-12",
"is",
"more",
"than",
"0.1",
"and",
"test",
"takers",
"whose",
"test",
"score",
"is",
"greater",
"than",
"or",
"equal",
"to",
"1500",
"?"
] |
[
{
"id": 9,
"type": "column",
"value": "Free Meal Count (K-12)"
},
{
"id": 8,
"type": "column",
"value": "Enrollment (K-12)"
},
{
"id": 0,
"type": "column",
"value": "School Name"
},
{
"id": 1,
"type": "table",
"value": "satscores"
},
{
"id": 6,
"type": "column",
"value": "numge1500"
},
{
"id": 4,
"type": "column",
"value": "cdscode"
},
{
"id": 2,
"type": "table",
"value": "frpm"
},
{
"id": 3,
"type": "column",
"value": "cds"
},
{
"id": 5,
"type": "value",
"value": "0.1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
23
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
24
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": [
31
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
11,
12,
13,
14
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,344
|
music_2
|
spider:train_spider.json:5264
|
Find the name of songs that does not have a back vocal.
|
SELECT DISTINCT title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid EXCEPT SELECT t2.title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid WHERE TYPE = "back"
|
[
"Find",
"the",
"name",
"of",
"songs",
"that",
"does",
"not",
"have",
"a",
"back",
"vocal",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "vocals"
},
{
"id": 5,
"type": "column",
"value": "songid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "songs"
},
{
"id": 3,
"type": "column",
"value": "type"
},
{
"id": 4,
"type": "column",
"value": "back"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"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",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
2,345
|
professional_basketball
|
bird:train.json:2802
|
Who is the longest serving coach from year 1970 to 1980. List the coach ID and the team(s) he served.
|
SELECT coachID, tmID FROM coaches WHERE year BETWEEN 1970 AND 1980 ORDER BY stint DESC LIMIT 1
|
[
"Who",
"is",
"the",
"longest",
"serving",
"coach",
"from",
"year",
"1970",
"to",
"1980",
".",
"List",
"the",
"coach",
"ID",
"and",
"the",
"team(s",
")",
"he",
"served",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "coaches"
},
{
"id": 1,
"type": "column",
"value": "coachid"
},
{
"id": 6,
"type": "column",
"value": "stint"
},
{
"id": 2,
"type": "column",
"value": "tmid"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "1970"
},
{
"id": 5,
"type": "value",
"value": "1980"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
14
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,346
|
bike_1
|
spider:train_spider.json:120
|
What is the id of the shortest trip?
|
SELECT id FROM trip ORDER BY duration LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"the",
"shortest",
"trip",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "duration"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,347
|
software_company
|
bird:train.json:8575
|
In male customers with an occupation handlers or cleaners, what is the percentage of customers with a true response?
|
SELECT CAST(SUM(CASE WHEN T2.RESPONSE = 'true' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(T2.REFID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.OCCUPATION = 'Handlers-cleaners' AND T1.SEX = 'Male'
|
[
"In",
"male",
"customers",
"with",
"an",
"occupation",
"handlers",
"or",
"cleaners",
",",
"what",
"is",
"the",
"percentage",
"of",
"customers",
"with",
"a",
"true",
"response",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "Handlers-cleaners"
},
{
"id": 1,
"type": "table",
"value": "mailings1_2"
},
{
"id": 4,
"type": "column",
"value": "occupation"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 11,
"type": "column",
"value": "response"
},
{
"id": 3,
"type": "column",
"value": "refid"
},
{
"id": 7,
"type": "value",
"value": "Male"
},
{
"id": 12,
"type": "value",
"value": "true"
},
{
"id": 6,
"type": "column",
"value": "sex"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 10,
"type": "value",
"value": "1.0"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"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": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
1
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
19
]
},
{
"entity_id": 12,
"token_idxs": [
18
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,348
|
sakila_1
|
spider:train_spider.json:2988
|
When did the first payment happen?
|
SELECT payment_date FROM payment ORDER BY payment_date ASC LIMIT 1
|
[
"When",
"did",
"the",
"first",
"payment",
"happen",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "payment_date"
},
{
"id": 0,
"type": "table",
"value": "payment"
}
] |
[
{
"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": []
},
{
"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"
] |
2,349
|
district_spokesman
|
bird:test.json:1195
|
Find the names of the districts which have had both spokesman with rank position 1 and 2.
|
SELECT t3.name FROM spokesman AS t1 JOIN spokesman_district AS t2 ON t1.Spokesman_ID = t2.Spokesman_ID JOIN district AS t3 ON t3.district_id = t2.district_id WHERE t1.rank_position = 1 INTERSECT SELECT t3.name FROM spokesman AS t1 JOIN spokesman_district AS t2 ON t1.Spokesman_ID = t2.Spokesman_ID JOIN district AS t3 ON t3.district_id = t2.district_id WHERE t1.rank_position = 2
|
[
"Find",
"the",
"names",
"of",
"the",
"districts",
"which",
"have",
"had",
"both",
"spokesman",
"with",
"rank",
"position",
"1",
"and",
"2",
"."
] |
[
{
"id": 6,
"type": "table",
"value": "spokesman_district"
},
{
"id": 2,
"type": "column",
"value": "rank_position"
},
{
"id": 8,
"type": "column",
"value": "spokesman_id"
},
{
"id": 7,
"type": "column",
"value": "district_id"
},
{
"id": 5,
"type": "table",
"value": "spokesman"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "1"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,350
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6457
|
What are the ids of documents which don't have expense budgets?
|
SELECT document_id FROM Documents EXCEPT SELECT document_id FROM Documents_with_expenses
|
[
"What",
"are",
"the",
"ids",
"of",
"documents",
"which",
"do",
"n't",
"have",
"expense",
"budgets",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "documents_with_expenses"
},
{
"id": 2,
"type": "column",
"value": "document_id"
},
{
"id": 0,
"type": "table",
"value": "documents"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,351
|
world_development_indicators
|
bird:train.json:2194
|
What country has the latest trade data with a series code of "SP.DYN.CDRT.IN
"? List the table name of the country.
|
SELECT DISTINCT T1.TableName FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T1.LatestTradeData = 2013 AND T2.IndicatorCode = 'SP.DYN.CDRT.IN'
|
[
"What",
"country",
"has",
"the",
"latest",
"trade",
"data",
"with",
"a",
"series",
"code",
"of",
"\"",
"SP.DYN.CDRT.IN",
"\n",
"\"",
"?",
"List",
"the",
"table",
"name",
"of",
"the",
"country",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "latesttradedata"
},
{
"id": 7,
"type": "value",
"value": "SP.DYN.CDRT.IN"
},
{
"id": 6,
"type": "column",
"value": "indicatorcode"
},
{
"id": 3,
"type": "column",
"value": "countrycode"
},
{
"id": 2,
"type": "table",
"value": "indicators"
},
{
"id": 0,
"type": "column",
"value": "tablename"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 5,
"type": "value",
"value": "2013"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19,
20
]
},
{
"entity_id": 1,
"token_idxs": [
23
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
13
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,352
|
voter_2
|
spider:train_spider.json:5507
|
Count the number of voting records for each election cycle.
|
SELECT Election_Cycle , count(*) FROM VOTING_RECORD GROUP BY Election_Cycle
|
[
"Count",
"the",
"number",
"of",
"voting",
"records",
"for",
"each",
"election",
"cycle",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "election_cycle"
},
{
"id": 0,
"type": "table",
"value": "voting_record"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
8,
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",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,353
|
mondial_geo
|
bird:train.json:8451
|
Which company falls under the category of an associated member? Please provide the organization's full name.
|
SELECT NAME FROM organization WHERE country IN ( SELECT country FROM politics WHERE dependent != '' )
|
[
"Which",
"company",
"falls",
"under",
"the",
"category",
"of",
"an",
"associated",
"member",
"?",
"Please",
"provide",
"the",
"organization",
"'s",
"full",
"name",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "organization"
},
{
"id": 4,
"type": "column",
"value": "dependent"
},
{
"id": 3,
"type": "table",
"value": "politics"
},
{
"id": 2,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
2,354
|
shakespeare
|
bird:train.json:3042
|
Please list any two character names in chapter 18708.
|
SELECT T1.CharName FROM characters AS T1 INNER JOIN paragraphs AS T2 ON T1.id = T2.character_id WHERE T2.chapter_id = 18708 LIMIT 2
|
[
"Please",
"list",
"any",
"two",
"character",
"names",
"in",
"chapter",
"18708",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "character_id"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 2,
"type": "table",
"value": "paragraphs"
},
{
"id": 3,
"type": "column",
"value": "chapter_id"
},
{
"id": 0,
"type": "column",
"value": "charname"
},
{
"id": 4,
"type": "value",
"value": "18708"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
2,355
|
tracking_orders
|
spider:train_spider.json:6889
|
Find the id of the order whose shipment tracking number is "3452".
|
SELECT order_id FROM shipments WHERE shipment_tracking_number = "3452"
|
[
"Find",
"the",
"i",
"d",
"of",
"the",
"order",
"whose",
"shipment",
"tracking",
"number",
"is",
"\"",
"3452",
"\"",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "shipment_tracking_number"
},
{
"id": 0,
"type": "table",
"value": "shipments"
},
{
"id": 1,
"type": "column",
"value": "order_id"
},
{
"id": 3,
"type": "column",
"value": "3452"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,356
|
talkingdata
|
bird:train.json:1043
|
How many active users were there in the event id 2?
|
SELECT COUNT(is_active) FROM app_events WHERE event_id = 2 AND is_active = 1
|
[
"How",
"many",
"active",
"users",
"were",
"there",
"in",
"the",
"event",
"i",
"d",
"2",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "app_events"
},
{
"id": 1,
"type": "column",
"value": "is_active"
},
{
"id": 2,
"type": "column",
"value": "event_id"
},
{
"id": 3,
"type": "value",
"value": "2"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
2,357
|
theme_gallery
|
spider:train_spider.json:1683
|
Show the theme for exhibitions with both records of an attendance below 100 and above 500.
|
SELECT T2.theme FROM exhibition_record AS T1 JOIN exhibition AS T2 ON T1.exhibition_id = T2.exhibition_id WHERE T1.attendance < 100 INTERSECT SELECT T2.theme FROM exhibition_record AS T1 JOIN exhibition AS T2 ON T1.exhibition_id = T2.exhibition_id WHERE T1.attendance > 500
|
[
"Show",
"the",
"theme",
"for",
"exhibitions",
"with",
"both",
"records",
"of",
"an",
"attendance",
"below",
"100",
"and",
"above",
"500",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "exhibition_record"
},
{
"id": 6,
"type": "column",
"value": "exhibition_id"
},
{
"id": 2,
"type": "table",
"value": "exhibition"
},
{
"id": 3,
"type": "column",
"value": "attendance"
},
{
"id": 0,
"type": "column",
"value": "theme"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "500"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.