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962
|
customers_and_addresses
|
spider:train_spider.json:6099
|
What is the "active to date" of the latest contact channel used by "Tillman Ernser"?
|
SELECT max(t2.active_to_date) FROM customers AS t1 JOIN customer_contact_channels AS t2 ON t1.customer_id = t2.customer_id WHERE t1.customer_name = "Tillman Ernser"
|
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"id": 1,
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{
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"type": "column",
"value": "Tillman Ernser"
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{
"id": 4,
"type": "column",
"value": "active_to_date"
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{
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"type": "column",
"value": "customer_name"
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"type": "column",
"value": "customer_id"
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{
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"value": "customers"
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"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
963
|
e_government
|
spider:train_spider.json:6330
|
Find the name of all the cities and states.
|
SELECT town_city FROM addresses UNION SELECT state_province_county FROM addresses
|
[
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"the",
"name",
"of",
"all",
"the",
"cities",
"and",
"states",
"."
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{
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"value": "addresses"
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{
"id": 1,
"type": "column",
"value": "town_city"
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[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
965
|
university_rank
|
bird:test.json:1761
|
How many universities are in Illinois or Ohio?
|
SELECT count(*) FROM University WHERE state = 'Illinois' OR state = 'Ohio'
|
[
"How",
"many",
"universities",
"are",
"in",
"Illinois",
"or",
"Ohio",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "value",
"value": "Illinois"
},
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "value",
"value": "Ohio"
}
] |
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[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
966
|
food_inspection
|
bird:train.json:8773
|
How many restaurants' owners are in California?
|
SELECT COUNT(owner_state) FROM businesses WHERE owner_state = 'CA'
|
[
"How",
"many",
"restaurants",
"'",
"owners",
"are",
"in",
"California",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "owner_state"
},
{
"id": 0,
"type": "table",
"value": "businesses"
},
{
"id": 2,
"type": "value",
"value": "CA"
}
] |
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[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O"
] |
967
|
california_schools
|
bird:dev.json:64
|
What is the total number of schools with a mailing city in Hickman belonging to the charter number 00D4?
|
SELECT COUNT(*) FROM schools WHERE CharterNum = '00D4' AND MailCity = 'Hickman'
|
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] |
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{
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"value": "charternum"
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{
"id": 3,
"type": "column",
"value": "mailcity"
},
{
"id": 0,
"type": "table",
"value": "schools"
},
{
"id": 4,
"type": "value",
"value": "Hickman"
},
{
"id": 2,
"type": "value",
"value": "00D4"
}
] |
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"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
968
|
donor
|
bird:train.json:3289
|
How many total items were requested for the Onslow Co School District urban metro school projects?
|
SELECT SUM(T1.item_quantity) FROM resources AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.school_metro = 'urban' AND T2.school_district = 'Onslow Co School District'
|
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"?"
] |
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"type": "value",
"value": "Onslow Co School District"
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"value": "item_quantity"
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"value": "school_metro"
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{
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"type": "table",
"value": "projects"
},
{
"id": 5,
"type": "value",
"value": "urban"
}
] |
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"I-VALUE",
"B-COLUMN",
"B-COLUMN",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O"
] |
969
|
scientist_1
|
spider:train_spider.json:6507
|
Find the name of scientists who are not assigned to any project.
|
SELECT Name FROM scientists WHERE ssn NOT IN (SELECT scientist FROM AssignedTo)
|
[
"Find",
"the",
"name",
"of",
"scientists",
"who",
"are",
"not",
"assigned",
"to",
"any",
"project",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "scientists"
},
{
"id": 3,
"type": "table",
"value": "assignedto"
},
{
"id": 4,
"type": "column",
"value": "scientist"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "ssn"
}
] |
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"O",
"O",
"O"
] |
970
|
genes
|
bird:train.json:2499
|
How many pairs of positively correlated genes are both non-essential?
|
SELECT COUNT(T2.GeneID2) FROM Genes AS T1 INNER JOIN Interactions AS T2 ON T1.GeneID = T2.GeneID1 WHERE T2.Expression_Corr > 0 AND T1.Essential = 'Non-Essential'
|
[
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"of",
"positively",
"correlated",
"genes",
"are",
"both",
"non",
"-",
"essential",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "expression_corr"
},
{
"id": 8,
"type": "value",
"value": "Non-Essential"
},
{
"id": 1,
"type": "table",
"value": "interactions"
},
{
"id": 7,
"type": "column",
"value": "essential"
},
{
"id": 2,
"type": "column",
"value": "geneid2"
},
{
"id": 4,
"type": "column",
"value": "geneid1"
},
{
"id": 3,
"type": "column",
"value": "geneid"
},
{
"id": 0,
"type": "table",
"value": "genes"
},
{
"id": 6,
"type": "value",
"value": "0"
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[
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"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
971
|
customers_card_transactions
|
spider:train_spider.json:693
|
Show ids, first names, last names, and phones for all customers.
|
SELECT customer_id , customer_first_name , customer_last_name , customer_phone FROM Customers
|
[
"Show",
"ids",
",",
"first",
"names",
",",
"last",
"names",
",",
"and",
"phones",
"for",
"all",
"customers",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "customer_first_name"
},
{
"id": 3,
"type": "column",
"value": "customer_last_name"
},
{
"id": 4,
"type": "column",
"value": "customer_phone"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
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"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
972
|
software_company
|
bird:train.json:8574
|
What is the occupation and response of female customers within the number of inhabitants range of 20 to 25?
|
SELECT DISTINCT T1.OCCUPATION, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.SEX = 'Female' AND T3.INHABITANTS_K >= 20 AND T3.INHABITANTS_K <= 25
|
[
"What",
"is",
"the",
"occupation",
"and",
"response",
"of",
"female",
"customers",
"within",
"the",
"number",
"of",
"inhabitants",
"range",
"of",
"20",
"to",
"25",
"?"
] |
[
{
"id": 8,
"type": "column",
"value": "inhabitants_k"
},
{
"id": 4,
"type": "table",
"value": "mailings1_2"
},
{
"id": 0,
"type": "column",
"value": "occupation"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "response"
},
{
"id": 7,
"type": "value",
"value": "Female"
},
{
"id": 2,
"type": "table",
"value": "demog"
},
{
"id": 5,
"type": "column",
"value": "geoid"
},
{
"id": 12,
"type": "column",
"value": "refid"
},
{
"id": 6,
"type": "column",
"value": "sex"
},
{
"id": 9,
"type": "value",
"value": "20"
},
{
"id": 10,
"type": "value",
"value": "25"
},
{
"id": 11,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
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16
]
},
{
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18
]
},
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
973
|
retail_world
|
bird:train.json:6438
|
From which country is the company "Drachenblut Delikatessen" from?
|
SELECT Country FROM Customers WHERE CompanyName = 'Drachenblut Delikatessen'
|
[
"From",
"which",
"country",
"is",
"the",
"company",
"\"",
"Drachenblut",
"Delikatessen",
"\"",
"from",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Drachenblut Delikatessen"
},
{
"id": 2,
"type": "column",
"value": "companyname"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "country"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
974
|
manufactory_1
|
spider:train_spider.json:5333
|
What is the average price of products with manufacturer codes equal to 2?
|
SELECT avg(price) FROM products WHERE Manufacturer = 2
|
[
"What",
"is",
"the",
"average",
"price",
"of",
"products",
"with",
"manufacturer",
"codes",
"equal",
"to",
"2",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "manufacturer"
},
{
"id": 0,
"type": "table",
"value": "products"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
975
|
chicago_crime
|
bird:train.json:8696
|
List crimes that the FBI has classified as Drug Abuse by their report number.
|
SELECT T2.report_no FROM FBI_Code AS T1 INNER JOIN Crime AS T2 ON T2.fbi_code_no = T1.fbi_code_no WHERE T1.title = 'Drug Abuse'
|
[
"List",
"crimes",
"that",
"the",
"FBI",
"has",
"classified",
"as",
"Drug",
"Abuse",
"by",
"their",
"report",
"number",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "fbi_code_no"
},
{
"id": 4,
"type": "value",
"value": "Drug Abuse"
},
{
"id": 0,
"type": "column",
"value": "report_no"
},
{
"id": 1,
"type": "table",
"value": "fbi_code"
},
{
"id": 2,
"type": "table",
"value": "crime"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
976
|
journal_committee
|
spider:train_spider.json:665
|
List the date, theme and sales of the journal which did not have any of the listed editors serving on committee.
|
SELECT date , theme , sales FROM journal EXCEPT SELECT T1.date , T1.theme , T1.sales FROM journal AS T1 JOIN journal_committee AS T2 ON T1.journal_ID = T2.journal_ID
|
[
"List",
"the",
"date",
",",
"theme",
"and",
"sales",
"of",
"the",
"journal",
"which",
"did",
"not",
"have",
"any",
"of",
"the",
"listed",
"editors",
"serving",
"on",
"committee",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "journal_committee"
},
{
"id": 5,
"type": "column",
"value": "journal_id"
},
{
"id": 0,
"type": "table",
"value": "journal"
},
{
"id": 2,
"type": "column",
"value": "theme"
},
{
"id": 3,
"type": "column",
"value": "sales"
},
{
"id": 1,
"type": "column",
"value": "date"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
20,
21
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
977
|
mondial_geo
|
bird:train.json:8280
|
What is the area of Egypt as a percentage of Asia?
|
SELECT T2.Percentage FROM country AS T1 INNER JOIN encompasses AS T2 ON T1.Code = T2.Country INNER JOIN continent AS T3 ON T3.Name = T2.Continent WHERE T3.Name = 'Asia' AND T1.Name = 'Egypt'
|
[
"What",
"is",
"the",
"area",
"of",
"Egypt",
"as",
"a",
"percentage",
"of",
"Asia",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "encompasses"
},
{
"id": 0,
"type": "column",
"value": "percentage"
},
{
"id": 1,
"type": "table",
"value": "continent"
},
{
"id": 5,
"type": "column",
"value": "continent"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 9,
"type": "column",
"value": "country"
},
{
"id": 7,
"type": "value",
"value": "Egypt"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "Asia"
},
{
"id": 8,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": [
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",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
978
|
soccer_2
|
spider:train_spider.json:4999
|
What are the names of all the players who received a yes during tryouts, and also what are the names of their colleges?
|
SELECT T1.pName , T2.cName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes'
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"the",
"players",
"who",
"received",
"a",
"yes",
"during",
"tryouts",
",",
"and",
"also",
"what",
"are",
"the",
"names",
"of",
"their",
"colleges",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "decision"
},
{
"id": 2,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "table",
"value": "tryout"
},
{
"id": 0,
"type": "column",
"value": "pname"
},
{
"id": 1,
"type": "column",
"value": "cname"
},
{
"id": 5,
"type": "value",
"value": "yes"
},
{
"id": 6,
"type": "column",
"value": "pid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
20
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
979
|
college_3
|
spider:train_spider.json:4658
|
What is the name of the department in the Building Mergenthaler?
|
SELECT DName FROM DEPARTMENT WHERE Building = "Mergenthaler"
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"department",
"in",
"the",
"Building",
"Mergenthaler",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Mergenthaler"
},
{
"id": 0,
"type": "table",
"value": "department"
},
{
"id": 2,
"type": "column",
"value": "building"
},
{
"id": 1,
"type": "column",
"value": "dname"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
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9
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
980
|
e_government
|
spider:train_spider.json:6322
|
Find the last name of the latest contact individual of the organization "Labour Party".
|
SELECT t3.individual_last_name FROM organizations AS t1 JOIN organization_contact_individuals AS t2 ON t1.organization_id = t2.organization_id JOIN individuals AS t3 ON t2.individual_id = t3.individual_id WHERE t1.organization_name = "Labour Party" ORDER BY t2.date_contact_to DESC LIMIT 1
|
[
"Find",
"the",
"last",
"name",
"of",
"the",
"latest",
"contact",
"individual",
"of",
"the",
"organization",
"\"",
"Labour",
"Party",
"\"",
"."
] |
[
{
"id": 6,
"type": "table",
"value": "organization_contact_individuals"
},
{
"id": 0,
"type": "column",
"value": "individual_last_name"
},
{
"id": 2,
"type": "column",
"value": "organization_name"
},
{
"id": 4,
"type": "column",
"value": "date_contact_to"
},
{
"id": 8,
"type": "column",
"value": "organization_id"
},
{
"id": 5,
"type": "table",
"value": "organizations"
},
{
"id": 7,
"type": "column",
"value": "individual_id"
},
{
"id": 3,
"type": "column",
"value": "Labour Party"
},
{
"id": 1,
"type": "table",
"value": "individuals"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13,
14
]
},
{
"entity_id": 4,
"token_idxs": [
6,
7
]
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
981
|
app_store
|
bird:train.json:2574
|
What is the average rating of Apps falling under the racing genre and what is the percentage ratio of positive sentiment reviews?
|
SELECT AVG(T1.Rating), CAST(COUNT(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE NULL END) AS REAL) * 100 / COUNT(T2.Sentiment) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.Genres = 'Racing'
|
[
"What",
"is",
"the",
"average",
"rating",
"of",
"Apps",
"falling",
"under",
"the",
"racing",
"genre",
"and",
"what",
"is",
"the",
"percentage",
"ratio",
"of",
"positive",
"sentiment",
"reviews",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "user_reviews"
},
{
"id": 0,
"type": "table",
"value": "playstore"
},
{
"id": 7,
"type": "column",
"value": "sentiment"
},
{
"id": 9,
"type": "value",
"value": "Positive"
},
{
"id": 2,
"type": "column",
"value": "genres"
},
{
"id": 3,
"type": "value",
"value": "Racing"
},
{
"id": 4,
"type": "column",
"value": "rating"
},
{
"id": 5,
"type": "column",
"value": "app"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
21
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
20
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
19
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O"
] |
982
|
works_cycles
|
bird:train.json:7203
|
Provide the business entity ID who did not achieved projected yearly sales quota in 2013.
|
SELECT DISTINCT T1.BusinessEntityID FROM SalesPerson AS T1 INNER JOIN SalesPersonQuotaHistory AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE STRFTIME('%Y', T2.QuotaDate) = '2013' AND T1.SalesQuota < T1.SalesLastYear
|
[
"Provide",
"the",
"business",
"entity",
"ID",
"who",
"did",
"not",
"achieved",
"projected",
"yearly",
"sales",
"quota",
"in",
"2013",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "salespersonquotahistory"
},
{
"id": 0,
"type": "column",
"value": "businessentityid"
},
{
"id": 5,
"type": "column",
"value": "saleslastyear"
},
{
"id": 1,
"type": "table",
"value": "salesperson"
},
{
"id": 4,
"type": "column",
"value": "salesquota"
},
{
"id": 7,
"type": "column",
"value": "quotadate"
},
{
"id": 3,
"type": "value",
"value": "2013"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"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",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
983
|
bakery_1
|
bird:test.json:1503
|
How many types of Cake does this bakery sell?
|
SELECT count(*) FROM goods WHERE food = "Cake"
|
[
"How",
"many",
"types",
"of",
"Cake",
"does",
"this",
"bakery",
"sell",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 1,
"type": "column",
"value": "food"
},
{
"id": 2,
"type": "column",
"value": "Cake"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
984
|
simpson_episodes
|
bird:train.json:4220
|
Name the person, award, organization, result and credited status of the assistant director in S20-E13.
|
SELECT T1.person, T1.award, T1.organization, T1.result, T2.credited FROM Award AS T1 INNER JOIN Credit AS T2 ON T2.episode_id = T1.episode_id WHERE T2.episode_id = 'S20-E13' AND T2.role = 'assistant director';
|
[
"Name",
"the",
"person",
",",
"award",
",",
"organization",
",",
"result",
"and",
"credited",
"status",
"of",
"the",
"assistant",
"director",
"in",
"S20",
"-",
"E13",
"."
] |
[
{
"id": 10,
"type": "value",
"value": "assistant director"
},
{
"id": 2,
"type": "column",
"value": "organization"
},
{
"id": 7,
"type": "column",
"value": "episode_id"
},
{
"id": 4,
"type": "column",
"value": "credited"
},
{
"id": 8,
"type": "value",
"value": "S20-E13"
},
{
"id": 0,
"type": "column",
"value": "person"
},
{
"id": 3,
"type": "column",
"value": "result"
},
{
"id": 6,
"type": "table",
"value": "credit"
},
{
"id": 1,
"type": "column",
"value": "award"
},
{
"id": 5,
"type": "table",
"value": "award"
},
{
"id": 9,
"type": "column",
"value": "role"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
14,
15
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
985
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5091
|
Count the total number of bookings made.
|
SELECT count(*) FROM BOOKINGS
|
[
"Count",
"the",
"total",
"number",
"of",
"bookings",
"made",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "bookings"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"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",
"B-TABLE",
"O",
"O"
] |
986
|
race_track
|
spider:train_spider.json:784
|
What are the names and dates of races, and the names of the tracks where they are held?
|
SELECT T1.name , T1.date , T2.name FROM race AS T1 JOIN track AS T2 ON T1.track_id = T2.track_id
|
[
"What",
"are",
"the",
"names",
"and",
"dates",
"of",
"races",
",",
"and",
"the",
"names",
"of",
"the",
"tracks",
"where",
"they",
"are",
"held",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "track_id"
},
{
"id": 3,
"type": "table",
"value": "track"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 2,
"type": "table",
"value": "race"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
987
|
world
|
bird:train.json:7884
|
Which country has the smallest surface area and the most crowded city?
|
SELECT T2.Name FROM City AS T1 INNER JOIN Country AS T2 ON T1.CountryCode = T2.Code ORDER BY T1.Population DESC, T2.SurfaceArea DESC LIMIT 1
|
[
"Which",
"country",
"has",
"the",
"smallest",
"surface",
"area",
"and",
"the",
"most",
"crowded",
"city",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "surfacearea"
},
{
"id": 5,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
988
|
gas_company
|
spider:train_spider.json:2002
|
What is the minimum, maximum, and average market value for every company?
|
SELECT min(market_value) , max(market_value) , avg(market_value) FROM company
|
[
"What",
"is",
"the",
"minimum",
",",
"maximum",
",",
"and",
"average",
"market",
"value",
"for",
"every",
"company",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "market_value"
},
{
"id": 0,
"type": "table",
"value": "company"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
13
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
989
|
address_1
|
bird:test.json:837
|
What is the first name and last name of the student living furthest to Linda Smith?
|
SELECT T3.Fname , T3.Lname FROM Direct_distance AS T1 JOIN Student AS T2 ON T1.city1_code = T2.city_code JOIN Student AS T3 ON T1.city2_code = T3.city_code WHERE T2.Fname = "Linda" AND T2.Lname = "Smith" ORDER BY distance DESC LIMIT 1
|
[
"What",
"is",
"the",
"first",
"name",
"and",
"last",
"name",
"of",
"the",
"student",
"living",
"furthest",
"to",
"Linda",
"Smith",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "direct_distance"
},
{
"id": 5,
"type": "column",
"value": "city2_code"
},
{
"id": 9,
"type": "column",
"value": "city1_code"
},
{
"id": 6,
"type": "column",
"value": "city_code"
},
{
"id": 3,
"type": "column",
"value": "distance"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 7,
"type": "column",
"value": "Linda"
},
{
"id": 8,
"type": "column",
"value": "Smith"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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": [
14
]
},
{
"entity_id": 8,
"token_idxs": [
15
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
990
|
european_football_2
|
bird:dev.json:1094
|
How much higher in percentage is Ariel Borysiuk's overall rating than that of Paulin Puel?
|
SELECT (SUM(CASE WHEN t1.player_name = 'Ariel Borysiuk' THEN t2.overall_rating ELSE 0 END) * 1.0 - SUM(CASE WHEN t1.player_name = 'Paulin Puel' THEN t2.overall_rating ELSE 0 END)) * 100 / SUM(CASE WHEN t1.player_name = 'Paulin Puel' THEN t2.overall_rating ELSE 0 END) FROM Player AS t1 INNER JOIN Player_Attributes AS t2 ON t1.player_api_id = t2.player_api_id
|
[
"How",
"much",
"higher",
"in",
"percentage",
"is",
"Ariel",
"Borysiuk",
"'s",
"overall",
"rating",
"than",
"that",
"of",
"Paulin",
"Puel",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "player_attributes"
},
{
"id": 6,
"type": "column",
"value": "overall_rating"
},
{
"id": 9,
"type": "value",
"value": "Ariel Borysiuk"
},
{
"id": 2,
"type": "column",
"value": "player_api_id"
},
{
"id": 7,
"type": "column",
"value": "player_name"
},
{
"id": 8,
"type": "value",
"value": "Paulin Puel"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "1.0"
},
{
"id": 4,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9,
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
14,
15
]
},
{
"entity_id": 9,
"token_idxs": [
6,
7
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
991
|
works_cycles
|
bird:train.json:7231
|
What is the total cost for all the orders placed on 5/29/2013?
|
SELECT SUM(TotalDue) FROM PurchaseOrderHeader WHERE OrderDate LIKE '2013-05-29%'
|
[
"What",
"is",
"the",
"total",
"cost",
"for",
"all",
"the",
"orders",
"placed",
"on",
"5/29/2013",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "purchaseorderheader"
},
{
"id": 2,
"type": "value",
"value": "2013-05-29%"
},
{
"id": 1,
"type": "column",
"value": "orderdate"
},
{
"id": 3,
"type": "column",
"value": "totaldue"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
992
|
car_racing
|
bird:test.json:1610
|
Sort the driver names by age in ascending order.
|
SELECT Driver FROM driver ORDER BY Age ASC
|
[
"Sort",
"the",
"driver",
"names",
"by",
"age",
"in",
"ascending",
"order",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "driver"
},
{
"id": 1,
"type": "column",
"value": "driver"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
994
|
flight_1
|
spider:train_spider.json:381
|
How many flights do we have?
|
SELECT count(*) FROM Flight
|
[
"How",
"many",
"flights",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "flight"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
995
|
language_corpus
|
bird:train.json:5685
|
List all the Catalan language wikipedia page title with less than 10 number of different words in these pages.
|
SELECT title FROM pages WHERE words < 10
|
[
"List",
"all",
"the",
"Catalan",
"language",
"wikipedia",
"page",
"title",
"with",
"less",
"than",
"10",
"number",
"of",
"different",
"words",
"in",
"these",
"pages",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "pages"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "column",
"value": "words"
},
{
"id": 3,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
18
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
996
|
mondial_geo
|
bird:train.json:8439
|
Which country has three different religions-Anglicanism, Christianity, and Roman Catholicism and uses 100% English?
|
SELECT T2.Country FROM country AS T1 INNER JOIN religion AS T2 ON T1.Code = T2.Country INNER JOIN language AS T3 ON T3.Country = T2.Country WHERE (T2.Name = 'Anglican' OR T2.Name = 'Christian' OR T2.Name = 'Roman Catholic') AND T3.Name = 'English' AND T3.Percentage = 100 GROUP BY T1.Name HAVING COUNT(T1.Name) = 3
|
[
"Which",
"country",
"has",
"three",
"different",
"religions",
"-",
"Anglicanism",
",",
"Christianity",
",",
"and",
"Roman",
"Catholicism",
"and",
"uses",
"100",
"%",
"English",
"?"
] |
[
{
"id": 12,
"type": "value",
"value": "Roman Catholic"
},
{
"id": 7,
"type": "column",
"value": "percentage"
},
{
"id": 11,
"type": "value",
"value": "Christian"
},
{
"id": 2,
"type": "table",
"value": "language"
},
{
"id": 5,
"type": "table",
"value": "religion"
},
{
"id": 10,
"type": "value",
"value": "Anglican"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 4,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "value",
"value": "English"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "code"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 3,
"type": "value",
"value": "3"
}
] |
[
{
"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": [
1
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
18
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
16
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
7
]
},
{
"entity_id": 11,
"token_idxs": [
9
]
},
{
"entity_id": 12,
"token_idxs": [
12,
13
]
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
997
|
railway
|
spider:train_spider.json:5637
|
What are the names of managers in ascending order of level?
|
SELECT Name FROM manager ORDER BY LEVEL ASC
|
[
"What",
"are",
"the",
"names",
"of",
"managers",
"in",
"ascending",
"order",
"of",
"level",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "manager"
},
{
"id": 2,
"type": "column",
"value": "level"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
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10
]
},
{
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{
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{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
999
|
authors
|
bird:train.json:3601
|
List the title and author's name of papers published in the 2007 Neoplasia journal.
|
SELECT T1.Title, T2.Name FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId INNER JOIN Journal AS T3 ON T1.JournalId = T3.Id WHERE T3.FullName = 'Neoplasia' AND T1.Year = 2007
|
[
"List",
"the",
"title",
"and",
"author",
"'s",
"name",
"of",
"papers",
"published",
"in",
"the",
"2007",
"Neoplasia",
"journal",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "paperauthor"
},
{
"id": 5,
"type": "column",
"value": "journalid"
},
{
"id": 8,
"type": "value",
"value": "Neoplasia"
},
{
"id": 7,
"type": "column",
"value": "fullname"
},
{
"id": 2,
"type": "table",
"value": "journal"
},
{
"id": 11,
"type": "column",
"value": "paperid"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "2007"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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6
]
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{
"entity_id": 2,
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14
]
},
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"entity_id": 3,
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8
]
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]
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{
"entity_id": 5,
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"token_idxs": []
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"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"B-TABLE",
"O"
] |
1,000
|
college_3
|
spider:train_spider.json:4641
|
Which courses are taught on days MTW?
|
SELECT CName FROM COURSE WHERE Days = "MTW"
|
[
"Which",
"courses",
"are",
"taught",
"on",
"days",
"MTW",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "column",
"value": "cname"
},
{
"id": 2,
"type": "column",
"value": "days"
},
{
"id": 3,
"type": "column",
"value": "MTW"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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5
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},
{
"entity_id": 3,
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},
{
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},
{
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{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
1,001
|
boat_1
|
bird:test.json:902
|
What are the rating and average age for sailors who reserved red boats for each rating?
|
SELECT T1.rating , avg(T1.age) FROM Sailors AS T1 JOIN Reserves AS T2 ON T1.sid = T2.sid JOIN Boats AS T3 ON T3.bid = T2.bid WHERE T3.color = 'red' GROUP BY T1.rating
|
[
"What",
"are",
"the",
"rating",
"and",
"average",
"age",
"for",
"sailors",
"who",
"reserved",
"red",
"boats",
"for",
"each",
"rating",
"?"
] |
[
{
"id": 6,
"type": "table",
"value": "reserves"
},
{
"id": 5,
"type": "table",
"value": "sailors"
},
{
"id": 0,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "table",
"value": "boats"
},
{
"id": 2,
"type": "column",
"value": "color"
},
{
"id": 3,
"type": "value",
"value": "red"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 7,
"type": "column",
"value": "bid"
},
{
"id": 8,
"type": "column",
"value": "sid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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11
]
},
{
"entity_id": 4,
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6
]
},
{
"entity_id": 5,
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8
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},
{
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10
]
},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,002
|
voter_2
|
spider:train_spider.json:5514
|
Report the distinct advisors who have more than 2 students.
|
SELECT Advisor FROM STUDENT GROUP BY Advisor HAVING count(*) > 2
|
[
"Report",
"the",
"distinct",
"advisors",
"who",
"have",
"more",
"than",
"2",
"students",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 1,
"type": "column",
"value": "advisor"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
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"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
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},
{
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
1,003
|
mondial_geo
|
bird:train.json:8366
|
Which religion is most prevalent in Asia?
|
SELECT T4.Name FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T3.Code = T2.Country INNER JOIN religion AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Asia' GROUP BY T4.Name ORDER BY SUM(T4.Percentage) DESC LIMIT 1
|
[
"Which",
"religion",
"is",
"most",
"prevalent",
"in",
"Asia",
"?"
] |
[
{
"id": 8,
"type": "table",
"value": "encompasses"
},
{
"id": 6,
"type": "column",
"value": "percentage"
},
{
"id": 7,
"type": "table",
"value": "continent"
},
{
"id": 9,
"type": "column",
"value": "continent"
},
{
"id": 1,
"type": "table",
"value": "religion"
},
{
"id": 3,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "value",
"value": "Asia"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
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},
{
"entity_id": 1,
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1
]
},
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6
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},
{
"entity_id": 14,
"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,004
|
party_people
|
spider:train_spider.json:2048
|
Who are the ministers who took office after 1961 or before 1959?
|
SELECT minister FROM party WHERE took_office > 1961 OR took_office < 1959
|
[
"Who",
"are",
"the",
"ministers",
"who",
"took",
"office",
"after",
"1961",
"or",
"before",
"1959",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "took_office"
},
{
"id": 1,
"type": "column",
"value": "minister"
},
{
"id": 0,
"type": "table",
"value": "party"
},
{
"id": 3,
"type": "value",
"value": "1961"
},
{
"id": 4,
"type": "value",
"value": "1959"
}
] |
[
{
"entity_id": 0,
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},
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"entity_id": 1,
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3
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5,
6
]
},
{
"entity_id": 3,
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8
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{
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{
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},
{
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{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
1,005
|
professional_basketball
|
bird:train.json:2923
|
Which player had the most game presentatons in 2011 NBA season.
|
SELECT playerID FROM players_teams WHERE year = 2011 ORDER BY GP DESC LIMIT 1
|
[
"Which",
"player",
"had",
"the",
"most",
"game",
"presentatons",
"in",
"2011",
"NBA",
"season",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "players_teams"
},
{
"id": 1,
"type": "column",
"value": "playerid"
},
{
"id": 2,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "value",
"value": "2011"
},
{
"id": 4,
"type": "column",
"value": "gp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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1
]
},
{
"entity_id": 3,
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8
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,006
|
local_govt_mdm
|
spider:train_spider.json:2646
|
what are the details of the cmi masters that have the cross reference code 'Tax'?
|
SELECT T1.cmi_details FROM Customer_Master_Index AS T1 JOIN CMI_Cross_References AS T2 ON T1.master_customer_id = T2.master_customer_id WHERE T2.source_system_code = 'Tax'
|
[
"what",
"are",
"the",
"details",
"of",
"the",
"cmi",
"masters",
"that",
"have",
"the",
"cross",
"reference",
"code",
"'",
"Tax",
"'",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "customer_master_index"
},
{
"id": 2,
"type": "table",
"value": "cmi_cross_references"
},
{
"id": 3,
"type": "column",
"value": "source_system_code"
},
{
"id": 5,
"type": "column",
"value": "master_customer_id"
},
{
"id": 0,
"type": "column",
"value": "cmi_details"
},
{
"id": 4,
"type": "value",
"value": "Tax"
}
] |
[
{
"entity_id": 0,
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3
]
},
{
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},
{
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11,
12
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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15
]
},
{
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},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
1,007
|
talkingdata
|
bird:train.json:1064
|
Provide the app users IDs and time for the event ID of 82.
|
SELECT T1.app_id, T2.timestamp FROM app_events AS T1 INNER JOIN events AS T2 ON T2.event_id = T1.event_id WHERE T2.event_id = 82
|
[
"Provide",
"the",
"app",
"users",
"IDs",
"and",
"time",
"for",
"the",
"event",
"ID",
"of",
"82",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "app_events"
},
{
"id": 1,
"type": "column",
"value": "timestamp"
},
{
"id": 4,
"type": "column",
"value": "event_id"
},
{
"id": 0,
"type": "column",
"value": "app_id"
},
{
"id": 3,
"type": "table",
"value": "events"
},
{
"id": 5,
"type": "value",
"value": "82"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,008
|
railway
|
spider:train_spider.json:5652
|
Show the countries that have managers of age above 50 or below 46.
|
SELECT Country FROM manager WHERE Age > 50 OR Age < 46
|
[
"Show",
"the",
"countries",
"that",
"have",
"managers",
"of",
"age",
"above",
"50",
"or",
"below",
"46",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "manager"
},
{
"id": 1,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "value",
"value": "50"
},
{
"id": 4,
"type": "value",
"value": "46"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE",
"O"
] |
1,009
|
music_2
|
spider:train_spider.json:5215
|
How many different instruments does the musician with the last name "Heilo" use?
|
SELECT count(DISTINCT instrument) FROM instruments AS T1 JOIN Band AS T2 ON T1.bandmateid = T2.id WHERE T2.lastname = "Heilo"
|
[
"How",
"many",
"different",
"instruments",
"does",
"the",
"musician",
"with",
"the",
"last",
"name",
"\"",
"Heilo",
"\"",
"use",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "instruments"
},
{
"id": 4,
"type": "column",
"value": "instrument"
},
{
"id": 5,
"type": "column",
"value": "bandmateid"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 3,
"type": "column",
"value": "Heilo"
},
{
"id": 1,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
1,010
|
chicago_crime
|
bird:train.json:8621
|
How many crimes were committed at 018XX S KOMENSKY AVEin May 2018?
|
SELECT SUM(CASE WHEN date LIKE '5/%/2018%' THEN 1 ELSE 0 END) FROM Crime WHERE block = '018XX S KOMENSKY AVE'
|
[
"How",
"many",
"crimes",
"were",
"committed",
"at",
"018XX",
"S",
"KOMENSKY",
"AVEin",
"May",
"2018",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "018XX S KOMENSKY AVE"
},
{
"id": 6,
"type": "value",
"value": "5/%/2018%"
},
{
"id": 0,
"type": "table",
"value": "crime"
},
{
"id": 1,
"type": "column",
"value": "block"
},
{
"id": 5,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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6,
7,
8,
9
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
1,011
|
restaurant
|
bird:train.json:1771
|
How many cities are there in Monterey?
|
SELECT COUNT(DISTINCT city) FROM geographic WHERE region = 'monterey'
|
[
"How",
"many",
"cities",
"are",
"there",
"in",
"Monterey",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "geographic"
},
{
"id": 2,
"type": "value",
"value": "monterey"
},
{
"id": 1,
"type": "column",
"value": "region"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,012
|
retail_complains
|
bird:train.json:332
|
Which is the city where most of the 1 star reviews come from?
|
SELECT T2.city FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Stars = 1 GROUP BY T2.city ORDER BY COUNT(T2.city) DESC LIMIT 1
|
[
"Which",
"is",
"the",
"city",
"where",
"most",
"of",
"the",
"1",
"star",
"reviews",
"come",
"from",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "district_id"
},
{
"id": 2,
"type": "table",
"value": "district"
},
{
"id": 1,
"type": "table",
"value": "reviews"
},
{
"id": 3,
"type": "column",
"value": "stars"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O"
] |
1,013
|
public_review_platform
|
bird:train.json:3989
|
List all the users with average star less than 3 stars in 2012
|
SELECT user_id FROM Users WHERE user_yelping_since_year = 2012 AND user_average_stars < 3
|
[
"List",
"all",
"the",
"users",
"with",
"average",
"star",
"less",
"than",
"3",
"stars",
"in",
"2012"
] |
[
{
"id": 2,
"type": "column",
"value": "user_yelping_since_year"
},
{
"id": 4,
"type": "column",
"value": "user_average_stars"
},
{
"id": 1,
"type": "column",
"value": "user_id"
},
{
"id": 0,
"type": "table",
"value": "users"
},
{
"id": 3,
"type": "value",
"value": "2012"
},
{
"id": 5,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
4,
5,
6
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-VALUE"
] |
1,014
|
movie_3
|
bird:train.json:9222
|
How much percentage of the film did Mary Keitel perform more than Angela Witherspoon?
|
SELECT CAST((SUM(IIF(T1.first_name = 'ANGELA' AND T1.last_name = 'WITHERSPOON', 1, 0)) - SUM(IIF(T1.first_name = 'MARY' AND T1.last_name = 'KEITEL', 1, 0))) AS REAL) * 100 / SUM(IIF(T1.first_name = 'MARY' AND T1.last_name = 'KEITEL', 1, 0)) FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id
|
[
"How",
"much",
"percentage",
"of",
"the",
"film",
"did",
"Mary",
"Keitel",
"perform",
"more",
"than",
"Angela",
"Witherspoon",
"?"
] |
[
{
"id": 11,
"type": "value",
"value": "WITHERSPOON"
},
{
"id": 1,
"type": "table",
"value": "film_actor"
},
{
"id": 6,
"type": "column",
"value": "first_name"
},
{
"id": 8,
"type": "column",
"value": "last_name"
},
{
"id": 2,
"type": "column",
"value": "actor_id"
},
{
"id": 9,
"type": "value",
"value": "KEITEL"
},
{
"id": 10,
"type": "value",
"value": "ANGELA"
},
{
"id": 0,
"type": "table",
"value": "actor"
},
{
"id": 7,
"type": "value",
"value": "MARY"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "value",
"value": "1"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
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{
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{
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{
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{
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},
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7
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{
"entity_id": 13,
"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
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"token_idxs": []
},
{
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"token_idxs": []
},
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},
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"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
1,015
|
works_cycles
|
bird:train.json:7301
|
Please list the email adresses of the reviewers who have given the lowest rating to the product HL Mountain Pedal.
|
SELECT T1.EmailAddress FROM ProductReview AS T1 INNER JOIN Product AS T2 ON T1.ProductID = T2.ProductID WHERE T2.Name = 'HL Mountain Pedal' ORDER BY T1.Rating LIMIT 1
|
[
"Please",
"list",
"the",
"email",
"adresses",
"of",
"the",
"reviewers",
"who",
"have",
"given",
"the",
"lowest",
"rating",
"to",
"the",
"product",
"HL",
"Mountain",
"Pedal",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "HL Mountain Pedal"
},
{
"id": 1,
"type": "table",
"value": "productreview"
},
{
"id": 0,
"type": "column",
"value": "emailaddress"
},
{
"id": 6,
"type": "column",
"value": "productid"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 5,
"type": "column",
"value": "rating"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,016
|
public_review_platform
|
bird:train.json:3865
|
Please list the opening time on Mondays of all the Yelp_Businesses in Anthem that are still running.
|
SELECT T1.opening_time FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id WHERE T2.day_of_week LIKE 'Monday' AND T3.city LIKE 'Anthem' AND T3.active LIKE 'True' GROUP BY T1.opening_time
|
[
"Please",
"list",
"the",
"opening",
"time",
"on",
"Mondays",
"of",
"all",
"the",
"Yelp_Businesses",
"in",
"Anthem",
"that",
"are",
"still",
"running",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "business_hours"
},
{
"id": 0,
"type": "column",
"value": "opening_time"
},
{
"id": 4,
"type": "column",
"value": "business_id"
},
{
"id": 5,
"type": "column",
"value": "day_of_week"
},
{
"id": 1,
"type": "table",
"value": "business"
},
{
"id": 6,
"type": "value",
"value": "Monday"
},
{
"id": 8,
"type": "value",
"value": "Anthem"
},
{
"id": 9,
"type": "column",
"value": "active"
},
{
"id": 11,
"type": "column",
"value": "day_id"
},
{
"id": 3,
"type": "table",
"value": "days"
},
{
"id": 7,
"type": "column",
"value": "city"
},
{
"id": 10,
"type": "value",
"value": "True"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"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": [
12
]
},
{
"entity_id": 9,
"token_idxs": [
4
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
1,017
|
retail_world
|
bird:train.json:6428
|
Please list any three order numbers that have been shipped using Speedy Express.
|
SELECT T1.OrderID FROM Orders AS T1 INNER JOIN Shippers AS T2 ON T1.ShipVia = T2.ShipperID WHERE T2.CompanyName = 'Speedy Express' LIMIT 3
|
[
"Please",
"list",
"any",
"three",
"order",
"numbers",
"that",
"have",
"been",
"shipped",
"using",
"Speedy",
"Express",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "Speedy Express"
},
{
"id": 3,
"type": "column",
"value": "companyname"
},
{
"id": 6,
"type": "column",
"value": "shipperid"
},
{
"id": 2,
"type": "table",
"value": "shippers"
},
{
"id": 0,
"type": "column",
"value": "orderid"
},
{
"id": 5,
"type": "column",
"value": "shipvia"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
1,018
|
superhero
|
bird:dev.json:734
|
What is the publisher's name of Blue Beetle II?
|
SELECT T2.publisher_name FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id WHERE T1.superhero_name = 'Blue Beetle II'
|
[
"What",
"is",
"the",
"publisher",
"'s",
"name",
"of",
"Blue",
"Beetle",
"II",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 3,
"type": "column",
"value": "superhero_name"
},
{
"id": 4,
"type": "value",
"value": "Blue Beetle II"
},
{
"id": 5,
"type": "column",
"value": "publisher_id"
},
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 2,
"type": "table",
"value": "publisher"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7,
8,
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,019
|
ice_hockey_draft
|
bird:train.json:6926
|
Please list the names of all the players that are over 90 kg and are right-shooted.
|
SELECT T1.PlayerName FROM PlayerInfo AS T1 INNER JOIN weight_info AS T2 ON T1.weight = T2.weight_id WHERE T2.weight_in_kg > 90 AND T1.shoots = 'R'
|
[
"Please",
"list",
"the",
"names",
"of",
"all",
"the",
"players",
"that",
"are",
"over",
"90",
"kg",
"and",
"are",
"right",
"-",
"shooted",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "weight_in_kg"
},
{
"id": 2,
"type": "table",
"value": "weight_info"
},
{
"id": 0,
"type": "column",
"value": "playername"
},
{
"id": 1,
"type": "table",
"value": "playerinfo"
},
{
"id": 4,
"type": "column",
"value": "weight_id"
},
{
"id": 3,
"type": "column",
"value": "weight"
},
{
"id": 7,
"type": "column",
"value": "shoots"
},
{
"id": 6,
"type": "value",
"value": "90"
},
{
"id": 8,
"type": "value",
"value": "R"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
11
]
},
{
"entity_id": 7,
"token_idxs": [
17
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
1,021
|
video_game
|
bird:test.json:1966
|
What are the names of players who do not play any games?
|
SELECT Player_name FROM player WHERE Player_ID NOT IN (SELECT Player_ID FROM game_player)
|
[
"What",
"are",
"the",
"names",
"of",
"players",
"who",
"do",
"not",
"play",
"any",
"games",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "player_name"
},
{
"id": 3,
"type": "table",
"value": "game_player"
},
{
"id": 2,
"type": "column",
"value": "player_id"
},
{
"id": 0,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3,
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,022
|
movie_3
|
bird:train.json:9398
|
List all the description of the films starring Lucille Tracy?
|
SELECT T1.film_id FROM film_actor AS T1 INNER JOIN actor AS T2 ON T1.actor_id = T2.actor_id WHERE T2.first_name = 'LUCILLE' AND T2.last_name = 'TRACY'
|
[
"List",
"all",
"the",
"description",
"of",
"the",
"films",
"starring",
"Lucille",
"Tracy",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "film_actor"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "actor_id"
},
{
"id": 0,
"type": "column",
"value": "film_id"
},
{
"id": 5,
"type": "value",
"value": "LUCILLE"
},
{
"id": 2,
"type": "table",
"value": "actor"
},
{
"id": 7,
"type": "value",
"value": "TRACY"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
1,023
|
chicago_crime
|
bird:train.json:8653
|
List the location descriptions and aldermen's full names of the arson by explosive.
|
SELECT T2.location_description, T1.alderman_first_name, T1.alderman_last_name, T1.alderman_name_suffix FROM Ward AS T1 INNER JOIN Crime AS T2 ON T2.ward_no = T1.ward_no INNER JOIN IUCR AS T3 ON T3.iucr_no = T2.iucr_no WHERE T3.primary_description = 'ARSON' AND T3.secondary_description = 'BY EXPLOSIVE'
|
[
"List",
"the",
"location",
"descriptions",
"and",
"aldermen",
"'s",
"full",
"names",
"of",
"the",
"arson",
"by",
"explosive",
"."
] |
[
{
"id": 10,
"type": "column",
"value": "secondary_description"
},
{
"id": 0,
"type": "column",
"value": "location_description"
},
{
"id": 3,
"type": "column",
"value": "alderman_name_suffix"
},
{
"id": 1,
"type": "column",
"value": "alderman_first_name"
},
{
"id": 8,
"type": "column",
"value": "primary_description"
},
{
"id": 2,
"type": "column",
"value": "alderman_last_name"
},
{
"id": 11,
"type": "value",
"value": "BY EXPLOSIVE"
},
{
"id": 7,
"type": "column",
"value": "iucr_no"
},
{
"id": 12,
"type": "column",
"value": "ward_no"
},
{
"id": 6,
"type": "table",
"value": "crime"
},
{
"id": 9,
"type": "value",
"value": "ARSON"
},
{
"id": 4,
"type": "table",
"value": "iucr"
},
{
"id": 5,
"type": "table",
"value": "ward"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5,
6,
7,
8
]
},
{
"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": [
3
]
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
12,
13
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-COLUMN",
"O",
"B-VALUE",
"B-VALUE",
"I-VALUE",
"O"
] |
1,024
|
network_2
|
spider:train_spider.json:4478
|
Which person whose friends have the oldest average age?
|
SELECT T2.name , avg(T1.age) FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.friend GROUP BY T2.name ORDER BY avg(T1.age) DESC LIMIT 1
|
[
"Which",
"person",
"whose",
"friends",
"have",
"the",
"oldest",
"average",
"age",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "personfriend"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 4,
"type": "column",
"value": "friend"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,025
|
movielens
|
bird:train.json:2299
|
List all of the user ids and ages who rated movies with the id 1695219?
|
SELECT T2.userid, T2.age FROM u2base AS T1 INNER JOIN users AS T2 ON T1.userid = T2.userid WHERE T1.movieid = 1695219
|
[
"List",
"all",
"of",
"the",
"user",
"ids",
"and",
"ages",
"who",
"rated",
"movies",
"with",
"the",
"i",
"d",
"1695219",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "movieid"
},
{
"id": 5,
"type": "value",
"value": "1695219"
},
{
"id": 0,
"type": "column",
"value": "userid"
},
{
"id": 2,
"type": "table",
"value": "u2base"
},
{
"id": 3,
"type": "table",
"value": "users"
},
{
"id": 1,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4
]
},
{
"entity_id": 4,
"token_idxs": [
10
]
},
{
"entity_id": 5,
"token_idxs": [
15
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,026
|
student_loan
|
bird:train.json:4467
|
How many students are enlisted in the Peace Corps organization are enrolled in UCSD school?
|
SELECT COUNT(T1.name) FROM enlist AS T1 INNER JOIN enrolled AS T2 ON T1.name = T2.name WHERE T1.organ = 'peace_corps' AND T2.school = 'ucsd'
|
[
"How",
"many",
"students",
"are",
"enlisted",
"in",
"the",
"Peace",
"Corps",
"organization",
"are",
"enrolled",
"in",
"UCSD",
"school",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "peace_corps"
},
{
"id": 1,
"type": "table",
"value": "enrolled"
},
{
"id": 0,
"type": "table",
"value": "enlist"
},
{
"id": 5,
"type": "column",
"value": "school"
},
{
"id": 3,
"type": "column",
"value": "organ"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "ucsd"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
7,
8
]
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,027
|
mondial_geo
|
bird:train.json:8352
|
What province does the 4th most populous city in the United Kingdom belong to, and how many people live there?
|
SELECT T1.Province, T1.Population FROM city AS T1 INNER JOIN country AS T2 ON T1.Country = T2.Code WHERE T2.Name = 'United Kingdom' ORDER BY T1.Population DESC LIMIT 3, 1
|
[
"What",
"province",
"does",
"the",
"4th",
"most",
"populous",
"city",
"in",
"the",
"United",
"Kingdom",
"belong",
"to",
",",
"and",
"how",
"many",
"people",
"live",
"there",
"?"
] |
[
{
"id": 5,
"type": "value",
"value": "United Kingdom"
},
{
"id": 1,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "column",
"value": "province"
},
{
"id": 3,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "city"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 7,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,028
|
university_basketball
|
spider:train_spider.json:1011
|
Find the team names of the universities whose enrollments are smaller than the average enrollment size.
|
SELECT t2.team_name FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id WHERE enrollment < (SELECT avg(enrollment) FROM university)
|
[
"Find",
"the",
"team",
"names",
"of",
"the",
"universities",
"whose",
"enrollments",
"are",
"smaller",
"than",
"the",
"average",
"enrollment",
"size",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "basketball_match"
},
{
"id": 1,
"type": "table",
"value": "university"
},
{
"id": 3,
"type": "column",
"value": "enrollment"
},
{
"id": 0,
"type": "column",
"value": "team_name"
},
{
"id": 4,
"type": "column",
"value": "school_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"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",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,029
|
simpson_episodes
|
bird:train.json:4246
|
How old was composer of the show when he was nominated for Emmy's Outstanding Music Composition for a Series in 2009. Indicate his full name as well.
|
SELECT T1.year - T2.birthdate AS ageIn2009, T2.name FROM Award AS T1 INNER JOIN Person AS T2 ON T1.person = T2.name WHERE T1.role = 'composer' AND T1.organization = 'Primetime Emmy Awards' AND T1.award = 'Outstanding Music Composition for a Series (Original Dramatic Score)' AND T1.result = 'Nominee' AND T1.year = 2009;
|
[
"How",
"old",
"was",
"composer",
"of",
"the",
"show",
"when",
"he",
"was",
"nominated",
"for",
"Emmy",
"'s",
"Outstanding",
"Music",
"Composition",
"for",
"a",
"Series",
"in",
"2009",
".",
"Indicate",
"his",
"full",
"name",
"as",
"well",
"."
] |
[
{
"id": 11,
"type": "value",
"value": "Outstanding Music Composition for a Series (Original Dramatic Score)"
},
{
"id": 9,
"type": "value",
"value": "Primetime Emmy Awards"
},
{
"id": 8,
"type": "column",
"value": "organization"
},
{
"id": 4,
"type": "column",
"value": "birthdate"
},
{
"id": 7,
"type": "value",
"value": "composer"
},
{
"id": 13,
"type": "value",
"value": "Nominee"
},
{
"id": 2,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "column",
"value": "person"
},
{
"id": 12,
"type": "column",
"value": "result"
},
{
"id": 1,
"type": "table",
"value": "award"
},
{
"id": 10,
"type": "column",
"value": "award"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "column",
"value": "role"
},
{
"id": 14,
"type": "value",
"value": "2009"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
26
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
23
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
3
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": [
14,
15,
16,
17,
18,
19,
20
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": [
10
]
},
{
"entity_id": 14,
"token_idxs": [
21
]
},
{
"entity_id": 15,
"token_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",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
1,030
|
sales
|
bird:train.json:5407
|
Find the number of customers handled by each of the sales people.
|
SELECT COUNT(CustomerID) FROM Sales GROUP BY SalesPersonID
|
[
"Find",
"the",
"number",
"of",
"customers",
"handled",
"by",
"each",
"of",
"the",
"sales",
"people",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "salespersonid"
},
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "sales"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,031
|
mondial_geo
|
bird:train.json:8452
|
Which nations have a boundary with the Kalahari Desert?
|
SELECT T3.Name FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert INNER JOIN country AS T3 ON T3.Code = T2.Country WHERE T1.Name = 'Kalahari'
|
[
"Which",
"nations",
"have",
"a",
"boundary",
"with",
"the",
"Kalahari",
"Desert",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "geo_desert"
},
{
"id": 2,
"type": "value",
"value": "Kalahari"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "table",
"value": "desert"
},
{
"id": 7,
"type": "column",
"value": "desert"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
1,032
|
ship_1
|
spider:train_spider.json:6220
|
How many different captain ranks are there?
|
SELECT count(DISTINCT rank) FROM captain
|
[
"How",
"many",
"different",
"captain",
"ranks",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "captain"
},
{
"id": 1,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O"
] |
1,033
|
store_1
|
spider:train_spider.json:608
|
How many orders does Luca Mancini have in his invoices?
|
SELECT count(*) FROM customers AS T1 JOIN invoices AS T2 ON T1.id = T2.customer_id WHERE T1.first_name = "Lucas" AND T1.last_name = "Mancini";
|
[
"How",
"many",
"orders",
"does",
"Luca",
"Mancini",
"have",
"in",
"his",
"invoices",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 1,
"type": "table",
"value": "invoices"
},
{
"id": 7,
"type": "column",
"value": "Mancini"
},
{
"id": 5,
"type": "column",
"value": "Lucas"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4
]
},
{
"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",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
1,034
|
restaurant
|
bird:train.json:1683
|
What type of food is served at the restaurant located at 3140, Alpine Road at San Mateo County?
|
SELECT T2.food_type FROM location AS T1 INNER JOIN generalinfo AS T2 ON T1.id_restaurant = T2.id_restaurant INNER JOIN geographic AS T3 ON T2.city = T3.city WHERE T3.County = 'san mateo county' AND T1.street_name = 'alpine rd' AND T1.street_num = 3140
|
[
"What",
"type",
"of",
"food",
"is",
"served",
"at",
"the",
"restaurant",
"located",
"at",
"3140",
",",
"Alpine",
"Road",
"at",
"San",
"Mateo",
"County",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "san mateo county"
},
{
"id": 11,
"type": "column",
"value": "id_restaurant"
},
{
"id": 3,
"type": "table",
"value": "generalinfo"
},
{
"id": 7,
"type": "column",
"value": "street_name"
},
{
"id": 1,
"type": "table",
"value": "geographic"
},
{
"id": 9,
"type": "column",
"value": "street_num"
},
{
"id": 0,
"type": "column",
"value": "food_type"
},
{
"id": 8,
"type": "value",
"value": "alpine rd"
},
{
"id": 2,
"type": "table",
"value": "location"
},
{
"id": 5,
"type": "column",
"value": "county"
},
{
"id": 4,
"type": "column",
"value": "city"
},
{
"id": 10,
"type": "value",
"value": "3140"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
16,
17
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
13,
14
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
11
]
},
{
"entity_id": 11,
"token_idxs": [
8
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"B-COLUMN",
"O"
] |
1,035
|
scientist_1
|
spider:train_spider.json:6480
|
What is the name of the project with the most hours?
|
SELECT name FROM projects ORDER BY hours DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"project",
"with",
"the",
"most",
"hours",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "projects"
},
{
"id": 2,
"type": "column",
"value": "hours"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,036
|
planet_1
|
bird:test.json:1906
|
What are the number of shipments managed and names of each manager?
|
SELECT T2.Name , count(*) FROM Shipment AS T1 JOIN Employee AS T2 ON T1.Manager = T2.EmployeeID GROUP BY T1.Manager;
|
[
"What",
"are",
"the",
"number",
"of",
"shipments",
"managed",
"and",
"names",
"of",
"each",
"manager",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "employeeid"
},
{
"id": 2,
"type": "table",
"value": "shipment"
},
{
"id": 3,
"type": "table",
"value": "employee"
},
{
"id": 0,
"type": "column",
"value": "manager"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
1,037
|
tracking_orders
|
spider:train_spider.json:6922
|
Which orders have shipment after 2000-01-01? Give me the order ids.
|
SELECT order_id FROM shipments WHERE shipment_date > "2000-01-01"
|
[
"Which",
"orders",
"have",
"shipment",
"after",
"2000",
"-",
"01",
"-",
"01",
"?",
"Give",
"me",
"the",
"order",
"ids",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "shipment_date"
},
{
"id": 3,
"type": "column",
"value": "2000-01-01"
},
{
"id": 0,
"type": "table",
"value": "shipments"
},
{
"id": 1,
"type": "column",
"value": "order_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
14,
15
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
5,
6,
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
1,038
|
department_management
|
spider:train_spider.json:6
|
What are the distinct creation years of the departments managed by a secretary born in state 'Alabama'?
|
SELECT DISTINCT T1.creation FROM department AS T1 JOIN management AS T2 ON T1.department_id = T2.department_id JOIN head AS T3 ON T2.head_id = T3.head_id WHERE T3.born_state = 'Alabama'
|
[
"What",
"are",
"the",
"distinct",
"creation",
"years",
"of",
"the",
"departments",
"managed",
"by",
"a",
"secretary",
"born",
"in",
"state",
"'",
"Alabama",
"'",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "department_id"
},
{
"id": 2,
"type": "column",
"value": "born_state"
},
{
"id": 4,
"type": "table",
"value": "department"
},
{
"id": 5,
"type": "table",
"value": "management"
},
{
"id": 0,
"type": "column",
"value": "creation"
},
{
"id": 3,
"type": "value",
"value": "Alabama"
},
{
"id": 6,
"type": "column",
"value": "head_id"
},
{
"id": 1,
"type": "table",
"value": "head"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O"
] |
1,039
|
institution_sports
|
bird:test.json:1644
|
What are the names of institutions, ordered alphabetically?
|
SELECT Name FROM institution ORDER BY Name ASC
|
[
"What",
"are",
"the",
"names",
"of",
"institutions",
",",
"ordered",
"alphabetically",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "institution"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
1,041
|
flight_1
|
spider:train_spider.json:416
|
What is the name of each aircraft and how many flights does each one complete?
|
SELECT T2.name , count(*) FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid
|
[
"What",
"is",
"the",
"name",
"of",
"each",
"aircraft",
"and",
"how",
"many",
"flights",
"does",
"each",
"one",
"complete",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "table",
"value": "flight"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "aid"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
1,042
|
retail_complains
|
bird:train.json:334
|
Among the female clients, how many of them have a complaint with a priority of 1?
|
SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.sex = 'Female' AND T2.priority = 1
|
[
"Among",
"the",
"female",
"clients",
",",
"how",
"many",
"of",
"them",
"have",
"a",
"complaint",
"with",
"a",
"priority",
"of",
"1",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 3,
"type": "column",
"value": "rand client"
},
{
"id": 2,
"type": "column",
"value": "client_id"
},
{
"id": 6,
"type": "column",
"value": "priority"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 5,
"type": "value",
"value": "Female"
},
{
"id": 4,
"type": "column",
"value": "sex"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,043
|
cre_Theme_park
|
spider:train_spider.json:5947
|
Show the description and code of the attraction type most tourist attractions belong to.
|
SELECT T1.Attraction_Type_Description , T2.Attraction_Type_Code FROM Ref_Attraction_Types AS T1 JOIN Tourist_Attractions AS T2 ON T1.Attraction_Type_Code = T2.Attraction_Type_Code GROUP BY T2.Attraction_Type_Code ORDER BY COUNT(*) DESC LIMIT 1
|
[
"Show",
"the",
"description",
"and",
"code",
"of",
"the",
"attraction",
"type",
"most",
"tourist",
"attractions",
"belong",
"to",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "attraction_type_description"
},
{
"id": 0,
"type": "column",
"value": "attraction_type_code"
},
{
"id": 2,
"type": "table",
"value": "ref_attraction_types"
},
{
"id": 3,
"type": "table",
"value": "tourist_attractions"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
1,044
|
medicine_enzyme_interaction
|
spider:train_spider.json:962
|
What is the count of enzymes without any interactions?
|
SELECT count(*) FROM enzyme WHERE id NOT IN ( SELECT enzyme_id FROM medicine_enzyme_interaction );
|
[
"What",
"is",
"the",
"count",
"of",
"enzymes",
"without",
"any",
"interactions",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "medicine_enzyme_interaction"
},
{
"id": 3,
"type": "column",
"value": "enzyme_id"
},
{
"id": 0,
"type": "table",
"value": "enzyme"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
1,045
|
card_games
|
bird:dev.json:433
|
What is the percentage of the set of cards that have Chinese Simplified as the language and are only available for online games?
|
SELECT CAST(SUM(CASE WHEN T2.language = 'Chinese Simplified' AND T1.isOnlineOnly = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM sets AS T1 INNER JOIN set_translations AS T2 ON T1.code = T2.setCode
|
[
"What",
"is",
"the",
"percentage",
"of",
"the",
"set",
"of",
"cards",
"that",
"have",
"Chinese",
"Simplified",
"as",
"the",
"language",
"and",
"are",
"only",
"available",
"for",
"online",
"games",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Chinese Simplified"
},
{
"id": 1,
"type": "table",
"value": "set_translations"
},
{
"id": 9,
"type": "column",
"value": "isonlineonly"
},
{
"id": 7,
"type": "column",
"value": "language"
},
{
"id": 3,
"type": "column",
"value": "setcode"
},
{
"id": 0,
"type": "table",
"value": "sets"
},
{
"id": 2,
"type": "column",
"value": "code"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
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6
]
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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]
},
{
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},
{
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},
{
"entity_id": 6,
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},
{
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{
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{
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},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"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",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
1,046
|
mental_health_survey
|
bird:train.json:4585
|
Please list the IDs of the users who answered "Yes" to the question "Do you think that discussing a physical health issue with your employer would have negative consequences?" in 2014's survey.
|
SELECT T2.UserID FROM Question AS T1 INNER JOIN Answer AS T2 ON T1.questionid = T2.QuestionID WHERE T1.questiontext = 'Do you think that discussing a physical health issue with your employer would have negative consequences?' AND T2.AnswerText LIKE 'Yes' AND T2.SurveyID = 2014
|
[
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"\"",
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"have",
"negative",
"consequences",
"?",
"\"",
"in",
"2014",
"'s",
"survey",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Do you think that discussing a physical health issue with your employer would have negative consequences?"
},
{
"id": 4,
"type": "column",
"value": "questiontext"
},
{
"id": 3,
"type": "column",
"value": "questionid"
},
{
"id": 6,
"type": "column",
"value": "answertext"
},
{
"id": 1,
"type": "table",
"value": "question"
},
{
"id": 8,
"type": "column",
"value": "surveyid"
},
{
"id": 0,
"type": "column",
"value": "userid"
},
{
"id": 2,
"type": "table",
"value": "answer"
},
{
"id": 9,
"type": "value",
"value": "2014"
},
{
"id": 7,
"type": "value",
"value": "Yes"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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14
]
},
{
"entity_id": 2,
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8
]
},
{
"entity_id": 3,
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
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{
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37
]
},
{
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35
]
},
{
"entity_id": 10,
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},
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"token_idxs": []
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{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O"
] |
1,047
|
mondial_geo
|
bird:train.json:8251
|
Please list the depth of the lakes that are located in the Province of Albania.
|
SELECT T2.Depth FROM located AS T1 INNER JOIN lake AS T2 ON T1.Lake = T2.Name WHERE T1.Province = 'Albania'
|
[
"Please",
"list",
"the",
"depth",
"of",
"the",
"lakes",
"that",
"are",
"located",
"in",
"the",
"Province",
"of",
"Albania",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "province"
},
{
"id": 1,
"type": "table",
"value": "located"
},
{
"id": 4,
"type": "value",
"value": "Albania"
},
{
"id": 0,
"type": "column",
"value": "depth"
},
{
"id": 2,
"type": "table",
"value": "lake"
},
{
"id": 5,
"type": "column",
"value": "lake"
},
{
"id": 6,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
1,048
|
insurance_policies
|
spider:train_spider.json:3854
|
List the method, date and amount of all the payments, in ascending order of date.
|
SELECT Payment_Method_Code , Date_Payment_Made , Amount_Payment FROM Payments ORDER BY Date_Payment_Made ASC
|
[
"List",
"the",
"method",
",",
"date",
"and",
"amount",
"of",
"all",
"the",
"payments",
",",
"in",
"ascending",
"order",
"of",
"date",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "payment_method_code"
},
{
"id": 2,
"type": "column",
"value": "date_payment_made"
},
{
"id": 3,
"type": "column",
"value": "amount_payment"
},
{
"id": 0,
"type": "table",
"value": "payments"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
1,050
|
sakila_1
|
spider:train_spider.json:3005
|
Return the first names of customers who did not rented a film after the date '2005-08-23 02:06:01'.
|
SELECT first_name FROM customer WHERE customer_id NOT IN( SELECT customer_id FROM rental WHERE rental_date > '2005-08-23 02:06:01' )
|
[
"Return",
"the",
"first",
"names",
"of",
"customers",
"who",
"did",
"not",
"rented",
"a",
"film",
"after",
"the",
"date",
"'",
"2005",
"-",
"08",
"-",
"23",
"02:06:01",
"'",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "2005-08-23 02:06:01"
},
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "column",
"value": "rental_date"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 3,
"type": "table",
"value": "rental"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
16,
17,
18,
19,
20,
21
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
1,051
|
codebase_comments
|
bird:train.json:676
|
How many path does the github address "https://github.com/jeffdik/tachy.git" have?
|
SELECT COUNT(DISTINCT T2.Path) FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T1.Url = 'https://github.com/jeffdik/tachy.git'
|
[
"How",
"many",
"path",
"does",
"the",
"github",
"address",
"\"",
"https://github.com/jeffdik/tachy.git",
"\"",
"have",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "https://github.com/jeffdik/tachy.git"
},
{
"id": 1,
"type": "table",
"value": "solution"
},
{
"id": 6,
"type": "column",
"value": "repoid"
},
{
"id": 0,
"type": "table",
"value": "repo"
},
{
"id": 4,
"type": "column",
"value": "path"
},
{
"id": 2,
"type": "column",
"value": "url"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
1,053
|
books
|
bird:train.json:5943
|
What is the cost of the slowest and least expensive shipping method?
|
SELECT method_name FROM shipping_method ORDER BY cost ASC LIMIT 1
|
[
"What",
"is",
"the",
"cost",
"of",
"the",
"slowest",
"and",
"least",
"expensive",
"shipping",
"method",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "shipping_method"
},
{
"id": 1,
"type": "column",
"value": "method_name"
},
{
"id": 2,
"type": "column",
"value": "cost"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,054
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5098
|
What are the phone and email for customer Harold?
|
SELECT Customer_Phone , Customer_Email_Address FROM CUSTOMERS WHERE Customer_Name = "Harold"
|
[
"What",
"are",
"the",
"phone",
"and",
"email",
"for",
"customer",
"Harold",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customer_email_address"
},
{
"id": 1,
"type": "column",
"value": "customer_phone"
},
{
"id": 3,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 4,
"type": "column",
"value": "Harold"
}
] |
[
{
"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": [
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",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,055
|
social_media
|
bird:train.json:782
|
How many tweets in total were posted by a user in Argentina?
|
SELECT COUNT(T1.TweetID) FROM twitter AS T1 INNER JOIN location AS T2 ON T2.LocationID = T1.LocationID WHERE T2.Country = 'Argentina' LIMIT 1
|
[
"How",
"many",
"tweets",
"in",
"total",
"were",
"posted",
"by",
"a",
"user",
"in",
"Argentina",
"?"
] |
[
{
"id": 5,
"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": 4,
"type": "column",
"value": "tweetid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,056
|
university
|
bird:train.json:8136
|
List the names of universities with a score less than 28% of the average score of all universities in 2015.
|
SELECT T2.university_name FROM university_ranking_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T1.year = 2015 AND T1.score * 100 < ( SELECT AVG(score) * 28 FROM university_ranking_year WHERE year = 2015 )
|
[
"List",
"the",
"names",
"of",
"universities",
"with",
"a",
"score",
"less",
"than",
"28",
"%",
"of",
"the",
"average",
"score",
"of",
"all",
"universities",
"in",
"2015",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 7,
"type": "column",
"value": "score"
},
{
"id": 5,
"type": "column",
"value": "year"
},
{
"id": 6,
"type": "value",
"value": "2015"
},
{
"id": 8,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "28"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
20
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
10
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
1,057
|
e_learning
|
spider:train_spider.json:3794
|
List all the subject names.
|
SELECT subject_name FROM SUBJECTS
|
[
"List",
"all",
"the",
"subject",
"names",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "subject_name"
},
{
"id": 0,
"type": "table",
"value": "subjects"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
1,058
|
university
|
bird:train.json:8049
|
Provide the ranking system ID of the Center for World University Rankings.
|
SELECT id FROM ranking_system WHERE system_name = 'Center for World University Rankings'
|
[
"Provide",
"the",
"ranking",
"system",
"ID",
"of",
"the",
"Center",
"for",
"World",
"University",
"Rankings",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Center for World University Rankings"
},
{
"id": 0,
"type": "table",
"value": "ranking_system"
},
{
"id": 2,
"type": "column",
"value": "system_name"
},
{
"id": 1,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
7,
8,
9,
10,
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,059
|
soccer_2016
|
bird:train.json:1796
|
Please list the bowling skills of all the players from Australia.
|
SELECT T2.Bowling_Skill FROM Player AS T1 INNER JOIN Bowling_Style AS T2 ON T1.Bowling_skill = T2.Bowling_Id INNER JOIN Country AS T3 ON T1.Country_Name = T3.Country_Id WHERE T3.Country_Name = 'Australia' GROUP BY T2.Bowling_Skill
|
[
"Please",
"list",
"the",
"bowling",
"skills",
"of",
"all",
"the",
"players",
"from",
"Australia",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "bowling_skill"
},
{
"id": 5,
"type": "table",
"value": "bowling_style"
},
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 6,
"type": "column",
"value": "country_id"
},
{
"id": 7,
"type": "column",
"value": "bowling_id"
},
{
"id": 3,
"type": "value",
"value": "Australia"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "table",
"value": "player"
}
] |
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{
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{
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}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
1,060
|
election
|
spider:train_spider.json:2736
|
Show the county name and population of all counties.
|
SELECT County_name , Population FROM county
|
[
"Show",
"the",
"county",
"name",
"and",
"population",
"of",
"all",
"counties",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "county_name"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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5
]
},
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},
{
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{
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},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
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"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
1,061
|
beer_factory
|
bird:train.json:5343
|
What is the transaction ratio being made at Sac State American River Courtyard and Sac State Union?
|
SELECT CAST(COUNT(CASE WHEN T2.LocationName = 'Sac State American River Courtyard' THEN T1.TransactionID ELSE NULL END) AS REAL) * 100 / COUNT(CASE WHEN T2.LocationName = 'Sac State Union' THEN T1.TransactionID ELSE NULL END) FROM `transaction` AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID
|
[
"What",
"is",
"the",
"transaction",
"ratio",
"being",
"made",
"at",
"Sac",
"State",
"American",
"River",
"Courtyard",
"and",
"Sac",
"State",
"Union",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "Sac State American River Courtyard"
},
{
"id": 6,
"type": "value",
"value": "Sac State Union"
},
{
"id": 4,
"type": "column",
"value": "transactionid"
},
{
"id": 5,
"type": "column",
"value": "locationname"
},
{
"id": 0,
"type": "table",
"value": "transaction"
},
{
"id": 2,
"type": "column",
"value": "locationid"
},
{
"id": 1,
"type": "table",
"value": "location"
},
{
"id": 3,
"type": "value",
"value": "100"
}
] |
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3
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{
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"token_idxs": []
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"token_idxs": []
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"entity_id": 16,
"token_idxs": []
},
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
1,062
|
card_games
|
bird:dev.json:364
|
What is the status of card "Cloudchaser Eagle"?
|
SELECT DISTINCT T2.status FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T1.name = 'Cloudchaser Eagle'
|
[
"What",
"is",
"the",
"status",
"of",
"card",
"\"",
"Cloudchaser",
"Eagle",
"\"",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Cloudchaser Eagle"
},
{
"id": 2,
"type": "table",
"value": "legalities"
},
{
"id": 0,
"type": "column",
"value": "status"
},
{
"id": 1,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "uuid"
}
] |
[
{
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3
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},
{
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},
{
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7,
8
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},
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
1,063
|
game_1
|
spider:train_spider.json:6020
|
What is the sport with the most scholarship students?
|
SELECT sportname FROM Sportsinfo WHERE onscholarship = 'Y' GROUP BY sportname ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"sport",
"with",
"the",
"most",
"scholarship",
"students",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "onscholarship"
},
{
"id": 0,
"type": "table",
"value": "sportsinfo"
},
{
"id": 1,
"type": "column",
"value": "sportname"
},
{
"id": 3,
"type": "value",
"value": "Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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3
]
},
{
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7
]
},
{
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},
{
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},
{
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{
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},
{
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{
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 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",
"O"
] |
1,064
|
body_builder
|
spider:train_spider.json:1158
|
What is the name of the body builder with the greatest body weight?
|
SELECT T2.Name FROM body_builder AS T1 JOIN people AS T2 ON T1.People_ID = T2.People_ID ORDER BY T2.Weight DESC LIMIT 1
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"body",
"builder",
"with",
"the",
"greatest",
"body",
"weight",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "body_builder"
},
{
"id": 4,
"type": "column",
"value": "people_id"
},
{
"id": 2,
"type": "table",
"value": "people"
},
{
"id": 3,
"type": "column",
"value": "weight"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
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3
]
},
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6,
7
]
},
{
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},
{
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12
]
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 9,
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},
{
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},
{
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"token_idxs": []
},
{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
1,065
|
vehicle_driver
|
bird:test.json:173
|
Which car models have total production larger than 100 or top speed higher than 150?
|
SELECT model FROM vehicle WHERE total_production > 100 OR top_speed > 150
|
[
"Which",
"car",
"models",
"have",
"total",
"production",
"larger",
"than",
"100",
"or",
"top",
"speed",
"higher",
"than",
"150",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "total_production"
},
{
"id": 4,
"type": "column",
"value": "top_speed"
},
{
"id": 0,
"type": "table",
"value": "vehicle"
},
{
"id": 1,
"type": "column",
"value": "model"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "150"
}
] |
[
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{
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{
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{
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"entity_id": 19,
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}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
1,066
|
department_store
|
spider:train_spider.json:4754
|
What are the distinct ids of customers who made an order after any order that was Cancelled?
|
SELECT DISTINCT customer_id FROM Customer_Orders WHERE order_date > (SELECT min(order_date) FROM Customer_Orders WHERE order_status_code = "Cancelled")
|
[
"What",
"are",
"the",
"distinct",
"ids",
"of",
"customers",
"who",
"made",
"an",
"order",
"after",
"any",
"order",
"that",
"was",
"Cancelled",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "order_status_code"
},
{
"id": 0,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "column",
"value": "order_date"
},
{
"id": 4,
"type": "column",
"value": "Cancelled"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
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"entity_id": 1,
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6
]
},
{
"entity_id": 2,
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10,
11
]
},
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13,
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},
{
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16
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},
{
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{
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{
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},
{
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},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O"
] |
1,067
|
music_2
|
spider:train_spider.json:5252
|
Find all the songs that do 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",
"all",
"the",
"songs",
"that",
"do",
"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"
}
] |
[
{
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"token_idxs": []
},
{
"entity_id": 1,
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10
]
},
{
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3
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{
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9
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
1,068
|
donor
|
bird:train.json:3166
|
Which state have the highest number of PayPal donations for an honoree whose portion of a donation included corporate sponsored giftcard?
|
SELECT DISTINCT donor_state FROM donations WHERE for_honoree = 't' AND payment_included_campaign_gift_card = 't' AND payment_method = 'paypal' AND donor_state = ( SELECT donor_state FROM donations GROUP BY donor_state ORDER BY SUM(donation_total) DESC LIMIT 1 )
|
[
"Which",
"state",
"have",
"the",
"highest",
"number",
"of",
"PayPal",
"donations",
"for",
"an",
"honoree",
"whose",
"portion",
"of",
"a",
"donation",
"included",
"corporate",
"sponsored",
"giftcard",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "payment_included_campaign_gift_card"
},
{
"id": 5,
"type": "column",
"value": "payment_method"
},
{
"id": 7,
"type": "column",
"value": "donation_total"
},
{
"id": 1,
"type": "column",
"value": "donor_state"
},
{
"id": 2,
"type": "column",
"value": "for_honoree"
},
{
"id": 0,
"type": "table",
"value": "donations"
},
{
"id": 6,
"type": "value",
"value": "paypal"
},
{
"id": 3,
"type": "value",
"value": "t"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
18
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
16
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
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