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16.1k
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29
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1.25k
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62
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2,358
|
restaurant
|
bird:train.json:1676
|
List by its ID number all restaurants on 11th Street in Oakland.
|
SELECT id_restaurant FROM location WHERE city = 'oakland' AND street_name = '11th street'
|
[
"List",
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"its",
"ID",
"number",
"all",
"restaurants",
"on",
"11th",
"Street",
"in",
"Oakland",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "id_restaurant"
},
{
"id": 4,
"type": "column",
"value": "street_name"
},
{
"id": 5,
"type": "value",
"value": "11th street"
},
{
"id": 0,
"type": "table",
"value": "location"
},
{
"id": 3,
"type": "value",
"value": "oakland"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
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{
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"token_idxs": []
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{
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[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
2,359
|
cookbook
|
bird:train.json:8922
|
How many dairy recipes can serve more than 10 people?
|
SELECT COUNT(*) FROM Recipe AS T1 INNER JOIN Quantity AS T2 ON T1.recipe_id = T2.recipe_id INNER JOIN Ingredient AS T3 ON T3.ingredient_id = T2.ingredient_id WHERE T3.category = 'dairy' AND T1.servings > 10
|
[
"How",
"many",
"dairy",
"recipes",
"can",
"serve",
"more",
"than",
"10",
"people",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "ingredient_id"
},
{
"id": 0,
"type": "table",
"value": "ingredient"
},
{
"id": 8,
"type": "column",
"value": "recipe_id"
},
{
"id": 2,
"type": "table",
"value": "quantity"
},
{
"id": 4,
"type": "column",
"value": "category"
},
{
"id": 6,
"type": "column",
"value": "servings"
},
{
"id": 1,
"type": "table",
"value": "recipe"
},
{
"id": 5,
"type": "value",
"value": "dairy"
},
{
"id": 7,
"type": "value",
"value": "10"
}
] |
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{
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"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,360
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6449
|
Show the budget type code and description and the corresponding document id.
|
SELECT T2.budget_type_code , T2.budget_type_description , T1.document_id FROM Documents_with_expenses AS T1 JOIN Ref_budget_codes AS T2 ON T1.budget_type_code = T2.budget_type_code
|
[
"Show",
"the",
"budget",
"type",
"code",
"and",
"description",
"and",
"the",
"corresponding",
"document",
"i",
"d."
] |
[
{
"id": 1,
"type": "column",
"value": "budget_type_description"
},
{
"id": 3,
"type": "table",
"value": "documents_with_expenses"
},
{
"id": 0,
"type": "column",
"value": "budget_type_code"
},
{
"id": 4,
"type": "table",
"value": "ref_budget_codes"
},
{
"id": 2,
"type": "column",
"value": "document_id"
}
] |
[
{
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{
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10,
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4
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{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN"
] |
2,361
|
real_estate_rentals
|
bird:test.json:1455
|
Return the date stamp and property name for each property history event, sorted by date stamp.
|
SELECT T1.datestamp , T2.property_name FROM User_Property_History AS T1 JOIN Properties AS T2 ON T1.property_id = T2.property_id ORDER BY datestamp;
|
[
"Return",
"the",
"date",
"stamp",
"and",
"property",
"name",
"for",
"each",
"property",
"history",
"event",
",",
"sorted",
"by",
"date",
"stamp",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "user_property_history"
},
{
"id": 1,
"type": "column",
"value": "property_name"
},
{
"id": 4,
"type": "column",
"value": "property_id"
},
{
"id": 3,
"type": "table",
"value": "properties"
},
{
"id": 0,
"type": "column",
"value": "datestamp"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
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},
{
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{
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{
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,362
|
simpson_episodes
|
bird:train.json:4278
|
Please provide any two episodes' names that have the same keyword of "1930s to 2020s".
|
SELECT T1.title FROM Episode AS T1 INNER JOIN Keyword AS T2 ON T1.episode_id = T2.episode_id WHERE T2.keyword = '1930s to 2020s' LIMIT 2;
|
[
"Please",
"provide",
"any",
"two",
"episodes",
"'",
"names",
"that",
"have",
"the",
"same",
"keyword",
"of",
"\"",
"1930s",
"to",
"2020s",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "1930s to 2020s"
},
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 1,
"type": "table",
"value": "episode"
},
{
"id": 2,
"type": "table",
"value": "keyword"
},
{
"id": 3,
"type": "column",
"value": "keyword"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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4
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{
"entity_id": 2,
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},
{
"entity_id": 3,
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11
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{
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15,
16
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{
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
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{
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
2,363
|
public_review_platform
|
bird:train.json:3835
|
Please list any two user numbers that have an "Uber" number of cute compliments.
|
SELECT T1.user_id FROM Users_Compliments AS T1 INNER JOIN Compliments AS T2 ON T1.compliment_id = T2.compliment_id WHERE T1.number_of_compliments LIKE 'Uber' AND T2.compliment_type LIKE 'cute' LIMIT 2
|
[
"Please",
"list",
"any",
"two",
"user",
"numbers",
"that",
"have",
"an",
"\"",
"Uber",
"\"",
"number",
"of",
"cute",
"compliments",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "number_of_compliments"
},
{
"id": 1,
"type": "table",
"value": "users_compliments"
},
{
"id": 6,
"type": "column",
"value": "compliment_type"
},
{
"id": 3,
"type": "column",
"value": "compliment_id"
},
{
"id": 2,
"type": "table",
"value": "compliments"
},
{
"id": 0,
"type": "column",
"value": "user_id"
},
{
"id": 5,
"type": "value",
"value": "Uber"
},
{
"id": 7,
"type": "value",
"value": "cute"
}
] |
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{
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4
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{
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{
"entity_id": 2,
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{
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"token_idxs": []
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{
"entity_id": 16,
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"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"B-VALUE",
"B-TABLE",
"O"
] |
2,364
|
soccer_2016
|
bird:train.json:1880
|
List down names of teams that have played as second team against Pune Warriors.
|
SELECT T2.Team_Name FROM Match AS T1 INNER JOIN Team AS T2 ON T2.Team_Id = T1.Team_2 WHERE T1.Team_1 = ( SELECT Team_Id FROM Team WHERE Team_Name = 'Pune Warriors' ) GROUP BY T2.Team_Name
|
[
"List",
"down",
"names",
"of",
"teams",
"that",
"have",
"played",
"as",
"second",
"team",
"against",
"Pune",
"Warriors",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Pune Warriors"
},
{
"id": 0,
"type": "column",
"value": "team_name"
},
{
"id": 4,
"type": "column",
"value": "team_id"
},
{
"id": 3,
"type": "column",
"value": "team_1"
},
{
"id": 5,
"type": "column",
"value": "team_2"
},
{
"id": 1,
"type": "table",
"value": "match"
},
{
"id": 2,
"type": "table",
"value": "team"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
12,
13
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},
{
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"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,365
|
works_cycles
|
bird:train.json:7139
|
Where is the address 15873 located, in what city and state? Does that city belong to a province where the code exists?
|
SELECT T2.City, T1.Name, T1.IsOnlyStateProvinceFlag FROM StateProvince AS T1 INNER JOIN Address AS T2 ON T1.StateProvinceID = T2.StateProvinceID WHERE T2.AddressID = 15873
|
[
"Where",
"is",
"the",
"address",
"15873",
"located",
",",
"in",
"what",
"city",
"and",
"state",
"?",
"Does",
"that",
"city",
"belong",
"to",
"a",
"province",
"where",
"the",
"code",
"exists",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "isonlystateprovinceflag"
},
{
"id": 7,
"type": "column",
"value": "stateprovinceid"
},
{
"id": 3,
"type": "table",
"value": "stateprovince"
},
{
"id": 5,
"type": "column",
"value": "addressid"
},
{
"id": 4,
"type": "table",
"value": "address"
},
{
"id": 6,
"type": "value",
"value": "15873"
},
{
"id": 0,
"type": "column",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
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{
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,366
|
insurance_policies
|
spider:train_spider.json:3892
|
List the details of the customers who do not have any policies.
|
SELECT customer_details FROM Customers EXCEPT SELECT T1.customer_details FROM Customers AS T1 JOIN Customer_Policies AS T2 ON T1.customer_id = T2.customer_id
|
[
"List",
"the",
"details",
"of",
"the",
"customers",
"who",
"do",
"not",
"have",
"any",
"policies",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "customer_policies"
},
{
"id": 1,
"type": "column",
"value": "customer_details"
},
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"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",
"O",
"O",
"O",
"O",
"O"
] |
2,367
|
olympics
|
bird:train.json:5025
|
What is the percentage of champions at the age of over 30?
|
SELECT CAST(COUNT(CASE WHEN T2.age > 30 THEN 1 END) AS REAL) * 100 / COUNT(T2.person_id) FROM competitor_event AS T1 INNER JOIN games_competitor AS T2 ON T1.competitor_id = T2.id WHERE T1.medal_id = 1
|
[
"What",
"is",
"the",
"percentage",
"of",
"champions",
"at",
"the",
"age",
"of",
"over",
"30",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "competitor_event"
},
{
"id": 1,
"type": "table",
"value": "games_competitor"
},
{
"id": 4,
"type": "column",
"value": "competitor_id"
},
{
"id": 7,
"type": "column",
"value": "person_id"
},
{
"id": 2,
"type": "column",
"value": "medal_id"
},
{
"id": 6,
"type": "value",
"value": "100"
},
{
"id": 8,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "column",
"value": "id"
},
{
"id": 9,
"type": "value",
"value": "30"
},
{
"id": 3,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": [
11
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,368
|
customers_and_orders
|
bird:test.json:307
|
How many customers have ordered the product named Monitor?
|
SELECT count(DISTINCT T3.customer_id) FROM Order_items AS T1 JOIN Products AS T2 ON T1.product_id = T2.product_id JOIN Customer_orders AS T3 ON T3.order_id = T1.order_id WHERE T2.product_name = "Monitor"
|
[
"How",
"many",
"customers",
"have",
"ordered",
"the",
"product",
"named",
"Monitor",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customer_orders"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 3,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "order_items"
},
{
"id": 7,
"type": "column",
"value": "product_id"
},
{
"id": 5,
"type": "table",
"value": "products"
},
{
"id": 6,
"type": "column",
"value": "order_id"
},
{
"id": 2,
"type": "column",
"value": "Monitor"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": [
4
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,369
|
restaurant
|
bird:train.json:1775
|
In which region can you find the top 4 most popular restaurants?
|
SELECT T2.region FROM generalinfo AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city ORDER BY T1.review DESC LIMIT 4
|
[
"In",
"which",
"region",
"can",
"you",
"find",
"the",
"top",
"4",
"most",
"popular",
"restaurants",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "generalinfo"
},
{
"id": 2,
"type": "table",
"value": "geographic"
},
{
"id": 0,
"type": "column",
"value": "region"
},
{
"id": 3,
"type": "column",
"value": "review"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"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-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,370
|
ship_1
|
spider:train_spider.json:6234
|
Find the name of captains whose rank are either Midshipman or Lieutenant.
|
SELECT name FROM captain WHERE rank = 'Midshipman' OR rank = 'Lieutenant'
|
[
"Find",
"the",
"name",
"of",
"captains",
"whose",
"rank",
"are",
"either",
"Midshipman",
"or",
"Lieutenant",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Midshipman"
},
{
"id": 4,
"type": "value",
"value": "Lieutenant"
},
{
"id": 0,
"type": "table",
"value": "captain"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "rank"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,371
|
customers_and_addresses
|
spider:train_spider.json:6121
|
Find the customer name and date of the orders that have the status "Delivered".
|
SELECT t1.customer_name , t2.order_date FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id WHERE order_status = "Delivered"
|
[
"Find",
"the",
"customer",
"name",
"and",
"date",
"of",
"the",
"orders",
"that",
"have",
"the",
"status",
"\"",
"Delivered",
"\"",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "customer_orders"
},
{
"id": 0,
"type": "column",
"value": "customer_name"
},
{
"id": 4,
"type": "column",
"value": "order_status"
},
{
"id": 6,
"type": "column",
"value": "customer_id"
},
{
"id": 1,
"type": "column",
"value": "order_date"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 5,
"type": "column",
"value": "Delivered"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,372
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6439
|
How many budget types do we have?
|
SELECT count(*) FROM Ref_budget_codes
|
[
"How",
"many",
"budget",
"types",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "ref_budget_codes"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
2,373
|
book_press
|
bird:test.json:1995
|
Find the book series that have some book selling more than 1000 and some book less 500.
|
SELECT book_series FROM book WHERE sale_amount > 1000 INTERSECT SELECT book_series FROM book WHERE sale_amount < 500
|
[
"Find",
"the",
"book",
"series",
"that",
"have",
"some",
"book",
"selling",
"more",
"than",
"1000",
"and",
"some",
"book",
"less",
"500",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "book_series"
},
{
"id": 2,
"type": "column",
"value": "sale_amount"
},
{
"id": 0,
"type": "table",
"value": "book"
},
{
"id": 3,
"type": "value",
"value": "1000"
},
{
"id": 4,
"type": "value",
"value": "500"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
14
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,374
|
e_learning
|
spider:train_spider.json:3774
|
List the addresses of all the course authors or tutors.
|
SELECT address_line_1 FROM Course_Authors_and_Tutors
|
[
"List",
"the",
"addresses",
"of",
"all",
"the",
"course",
"authors",
"or",
"tutors",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 1,
"type": "column",
"value": "address_line_1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6,
7,
8,
9
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
2,375
|
flight_1
|
spider:train_spider.json:390
|
What are the departure and arrival dates of all flights from LA to Honolulu?
|
SELECT departure_date , arrival_date FROM Flight WHERE origin = "Los Angeles" AND destination = "Honolulu"
|
[
"What",
"are",
"the",
"departure",
"and",
"arrival",
"dates",
"of",
"all",
"flights",
"from",
"LA",
"to",
"Honolulu",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "departure_date"
},
{
"id": 2,
"type": "column",
"value": "arrival_date"
},
{
"id": 4,
"type": "column",
"value": "Los Angeles"
},
{
"id": 5,
"type": "column",
"value": "destination"
},
{
"id": 6,
"type": "column",
"value": "Honolulu"
},
{
"id": 0,
"type": "table",
"value": "flight"
},
{
"id": 3,
"type": "column",
"value": "origin"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
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3
]
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{
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5,
6
]
},
{
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{
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{
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{
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"entity_id": 14,
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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",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,376
|
books
|
bird:train.json:5942
|
What is the average number of pages of David Coward's books?
|
SELECT AVG(T1.num_pages) FROM book AS T1 INNER JOIN book_author AS T2 ON T1.book_id = T2.book_id INNER JOIN author AS T3 ON T3.author_id = T2.author_id WHERE T3.author_name = 'David Coward'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"pages",
"of",
"David",
"Coward",
"'s",
"books",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "David Coward"
},
{
"id": 1,
"type": "column",
"value": "author_name"
},
{
"id": 5,
"type": "table",
"value": "book_author"
},
{
"id": 3,
"type": "column",
"value": "num_pages"
},
{
"id": 6,
"type": "column",
"value": "author_id"
},
{
"id": 7,
"type": "column",
"value": "book_id"
},
{
"id": 0,
"type": "table",
"value": "author"
},
{
"id": 4,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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8,
9
]
},
{
"entity_id": 3,
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6
]
},
{
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11
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
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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-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-TABLE",
"O"
] |
2,377
|
regional_sales
|
bird:train.json:2692
|
In which city is the store with the highest sales order unit price located?
|
SELECT T2.`City Name` FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID WHERE REPLACE(T1.`Unit Price`, ',', '') = ( SELECT REPLACE(T1.`Unit Price`, ',', '') FROM `Sales Orders` AS T1 INNER JOIN `Store Locations` AS T2 ON T2.StoreID = T1._StoreID ORDER BY REPLACE(T1.`Unit Price`, ',', '') DESC LIMIT 1 ) ORDER BY REPLACE(T1.`Unit Price`, ',', '') DESC LIMIT 1
|
[
"In",
"which",
"city",
"is",
"the",
"store",
"with",
"the",
"highest",
"sales",
"order",
"unit",
"price",
"located",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "Store Locations"
},
{
"id": 1,
"type": "table",
"value": "Sales Orders"
},
{
"id": 5,
"type": "column",
"value": "Unit Price"
},
{
"id": 0,
"type": "column",
"value": "City Name"
},
{
"id": 4,
"type": "column",
"value": "_storeid"
},
{
"id": 3,
"type": "column",
"value": "storeid"
},
{
"id": 6,
"type": "value",
"value": ","
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
9,
10
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11,
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
2,378
|
behavior_monitoring
|
spider:train_spider.json:3091
|
What are the start and end dates for incidents with incident type code "NOISE"?
|
SELECT date_incident_start , date_incident_end FROM Behavior_Incident WHERE incident_type_code = "NOISE"
|
[
"What",
"are",
"the",
"start",
"and",
"end",
"dates",
"for",
"incidents",
"with",
"incident",
"type",
"code",
"\"",
"NOISE",
"\"",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "date_incident_start"
},
{
"id": 3,
"type": "column",
"value": "incident_type_code"
},
{
"id": 0,
"type": "table",
"value": "behavior_incident"
},
{
"id": 2,
"type": "column",
"value": "date_incident_end"
},
{
"id": 4,
"type": "column",
"value": "NOISE"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 10,
"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",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
2,379
|
flight_1
|
spider:train_spider.json:345
|
Show name and distance for all aircrafts.
|
SELECT name , distance FROM Aircraft
|
[
"Show",
"name",
"and",
"distance",
"for",
"all",
"aircrafts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "aircraft"
},
{
"id": 2,
"type": "column",
"value": "distance"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"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,
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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",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,380
|
university
|
bird:train.json:8064
|
Provide the ranking criteria and scores in 2005 that were received by Harvard University.
|
SELECT T1.criteria_name, T2.score FROM ranking_criteria AS T1 INNER JOIN university_ranking_year AS T2 ON T1.id = T2.ranking_criteria_id INNER JOIN university AS T3 ON T3.id = T2.university_id WHERE T3.university_name = 'Harvard University' AND T2.year = 2005
|
[
"Provide",
"the",
"ranking",
"criteria",
"and",
"scores",
"in",
"2005",
"that",
"were",
"received",
"by",
"Harvard",
"University",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "university_ranking_year"
},
{
"id": 11,
"type": "column",
"value": "ranking_criteria_id"
},
{
"id": 8,
"type": "value",
"value": "Harvard University"
},
{
"id": 3,
"type": "table",
"value": "ranking_criteria"
},
{
"id": 7,
"type": "column",
"value": "university_name"
},
{
"id": 0,
"type": "column",
"value": "criteria_name"
},
{
"id": 6,
"type": "column",
"value": "university_id"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 1,
"type": "column",
"value": "score"
},
{
"id": 9,
"type": "column",
"value": "year"
},
{
"id": 10,
"type": "value",
"value": "2005"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
2
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": [
12
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
7
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,381
|
network_2
|
spider:train_spider.json:4421
|
How old is each gender, on average?
|
SELECT avg(age) , gender FROM Person GROUP BY gender
|
[
"How",
"old",
"is",
"each",
"gender",
",",
"on",
"average",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "gender"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
2,382
|
music_platform_2
|
bird:train.json:7930
|
Which podcast was reviewed the latest? State the date of creation, podcast tile and rating.
|
SELECT T1.podcast_id, T2.created_at, T2.title, T2.rating FROM podcasts AS T1 INNER JOIN reviews AS T2 ON T2.podcast_id = T1.podcast_id ORDER BY T2.created_at DESC LIMIT 1
|
[
"Which",
"podcast",
"was",
"reviewed",
"the",
"latest",
"?",
"State",
"the",
"date",
"of",
"creation",
",",
"podcast",
"tile",
"and",
"rating",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "podcast_id"
},
{
"id": 1,
"type": "column",
"value": "created_at"
},
{
"id": 4,
"type": "table",
"value": "podcasts"
},
{
"id": 5,
"type": "table",
"value": "reviews"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 2,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11,
12
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
16
]
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O"
] |
2,383
|
e_learning
|
spider:train_spider.json:3847
|
What are the login names used both by some course authors and some students?
|
SELECT login_name FROM Course_Authors_and_Tutors INTERSECT SELECT login_name FROM Students
|
[
"What",
"are",
"the",
"login",
"names",
"used",
"both",
"by",
"some",
"course",
"authors",
"and",
"some",
"students",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "course_authors_and_tutors"
},
{
"id": 2,
"type": "column",
"value": "login_name"
},
{
"id": 1,
"type": "table",
"value": "students"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9,
10,
11
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": [
3,
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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-TABLE",
"O"
] |
2,384
|
workshop_paper
|
spider:train_spider.json:5843
|
Which authors did not submit to any workshop?
|
SELECT Author FROM submission WHERE Submission_ID NOT IN (SELECT Submission_ID FROM acceptance)
|
[
"Which",
"authors",
"did",
"not",
"submit",
"to",
"any",
"workshop",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "submission_id"
},
{
"id": 0,
"type": "table",
"value": "submission"
},
{
"id": 3,
"type": "table",
"value": "acceptance"
},
{
"id": 1,
"type": "column",
"value": "author"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
2,385
|
thrombosis_prediction
|
bird:dev.json:1262
|
How many patients with a normal level of complement 3 have a P pattern observed in the sheet of ANA examination?
|
SELECT COUNT(DISTINCT T1.ID) FROM Examination AS T1 INNER JOIN Laboratory AS T2 ON T1.ID = T2.ID WHERE T2.C3 > 35 AND T1.`ANA Pattern` = 'P'
|
[
"How",
"many",
"patients",
"with",
"a",
"normal",
"level",
"of",
"complement",
"3",
"have",
"a",
"P",
"pattern",
"observed",
"in",
"the",
"sheet",
"of",
"ANA",
"examination",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "examination"
},
{
"id": 5,
"type": "column",
"value": "ANA Pattern"
},
{
"id": 1,
"type": "table",
"value": "laboratory"
},
{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 3,
"type": "column",
"value": "c3"
},
{
"id": 4,
"type": "value",
"value": "35"
},
{
"id": 6,
"type": "value",
"value": "P"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
20
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": [
11,
13
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,386
|
book_publishing_company
|
bird:train.json:199
|
What is the publisher's information of New Moon Books?
|
SELECT T1.pr_info FROM pub_info AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'New Moon Books'
|
[
"What",
"is",
"the",
"publisher",
"'s",
"information",
"of",
"New",
"Moon",
"Books",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "New Moon Books"
},
{
"id": 2,
"type": "table",
"value": "publishers"
},
{
"id": 1,
"type": "table",
"value": "pub_info"
},
{
"id": 3,
"type": "column",
"value": "pub_name"
},
{
"id": 0,
"type": "column",
"value": "pr_info"
},
{
"id": 5,
"type": "column",
"value": "pub_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3,
4
]
},
{
"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",
"I-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,387
|
student_loan
|
bird:train.json:4397
|
How many male students have no due payments?
|
SELECT COUNT(T1.name) FROM no_payment_due AS T1 INNER JOIN male AS T2 ON T1.name = T2.name WHERE T1.bool = 'neg'
|
[
"How",
"many",
"male",
"students",
"have",
"no",
"due",
"payments",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "no_payment_due"
},
{
"id": 1,
"type": "table",
"value": "male"
},
{
"id": 2,
"type": "column",
"value": "bool"
},
{
"id": 4,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "neg"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"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",
"B-TABLE",
"O"
] |
2,388
|
hr_1
|
spider:train_spider.json:3409
|
Display the first name, and department number for all employees whose last name is "McEwen".
|
SELECT first_name , department_id FROM employees WHERE last_name = 'McEwen'
|
[
"Display",
"the",
"first",
"name",
",",
"and",
"department",
"number",
"for",
"all",
"employees",
"whose",
"last",
"name",
"is",
"\"",
"McEwen",
"\"",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "department_id"
},
{
"id": 1,
"type": "column",
"value": "first_name"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "last_name"
},
{
"id": 4,
"type": "value",
"value": "McEwen"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
12,
13
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,389
|
movies_4
|
bird:train.json:554
|
How many adventure movies are there that were released in 2000?
|
SELECT COUNT(T1.movie_id) FROM movie AS T1 INNER JOIN movie_genres AS T2 ON T1.movie_id = T2.movie_id INNER JOIN genre AS T3 ON T2.genre_id = T3.genre_id WHERE T3.genre_name = 'Adventure' AND CAST(STRFTIME('%Y', T1.release_date) AS INT) = 2000
|
[
"How",
"many",
"adventure",
"movies",
"are",
"there",
"that",
"were",
"released",
"in",
"2000",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "movie_genres"
},
{
"id": 9,
"type": "column",
"value": "release_date"
},
{
"id": 5,
"type": "column",
"value": "genre_name"
},
{
"id": 6,
"type": "value",
"value": "Adventure"
},
{
"id": 1,
"type": "column",
"value": "movie_id"
},
{
"id": 4,
"type": "column",
"value": "genre_id"
},
{
"id": 0,
"type": "table",
"value": "genre"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 7,
"type": "value",
"value": "2000"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"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": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
8
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,390
|
club_1
|
spider:train_spider.json:4272
|
Find all the male members of club "Hopkins Student Enterprises". Show the first name and last name.
|
SELECT t3.fname , t3.lname FROM club AS t1 JOIN member_of_club AS t2 ON t1.clubid = t2.clubid JOIN student AS t3 ON t2.stuid = t3.stuid WHERE t1.clubname = "Hopkins Student Enterprises" AND t3.sex = "M"
|
[
"Find",
"all",
"the",
"male",
"members",
"of",
"club",
"\"",
"Hopkins",
"Student",
"Enterprises",
"\"",
".",
"Show",
"the",
"first",
"name",
"and",
"last",
"name",
"."
] |
[
{
"id": 7,
"type": "column",
"value": "Hopkins Student Enterprises"
},
{
"id": 4,
"type": "table",
"value": "member_of_club"
},
{
"id": 6,
"type": "column",
"value": "clubname"
},
{
"id": 2,
"type": "table",
"value": "student"
},
{
"id": 10,
"type": "column",
"value": "clubid"
},
{
"id": 0,
"type": "column",
"value": "fname"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 5,
"type": "column",
"value": "stuid"
},
{
"id": 3,
"type": "table",
"value": "club"
},
{
"id": 8,
"type": "column",
"value": "sex"
},
{
"id": 9,
"type": "column",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
16
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
8,
10
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
2,391
|
retail_complains
|
bird:train.json:345
|
What is the first name of clients who have the highest priority?
|
SELECT T1.first FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.priority = ( SELECT MAX(priority) FROM callcenterlogs )
|
[
"What",
"is",
"the",
"first",
"name",
"of",
"clients",
"who",
"have",
"the",
"highest",
"priority",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 5,
"type": "column",
"value": "rand client"
},
{
"id": 4,
"type": "column",
"value": "client_id"
},
{
"id": 3,
"type": "column",
"value": "priority"
},
{
"id": 1,
"type": "table",
"value": "client"
},
{
"id": 0,
"type": "column",
"value": "first"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
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11
]
},
{
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},
{
"entity_id": 5,
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5
]
},
{
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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",
"B-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,392
|
e_government
|
spider:train_spider.json:6312
|
Find the name of the most popular party form.
|
SELECT t1.form_name FROM forms AS t1 JOIN party_forms AS t2 ON t1.form_id = t2.form_id GROUP BY t2.form_id ORDER BY count(*) DESC LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"most",
"popular",
"party",
"form",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "party_forms"
},
{
"id": 1,
"type": "column",
"value": "form_name"
},
{
"id": 0,
"type": "column",
"value": "form_id"
},
{
"id": 2,
"type": "table",
"value": "forms"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
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},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
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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",
"O",
"B-TABLE",
"B-TABLE",
"O"
] |
2,393
|
formula_1
|
bird:dev.json:995
|
What is the average score of Lewis Hamilton among all the Turkish Grand Prix?
|
SELECT AVG(T2.points) FROM drivers AS T1 INNER JOIN driverStandings AS T2 ON T1.driverId = T2.driverId INNER JOIN races AS T3 ON T3.raceId = T2.raceId WHERE T1.forename = 'Lewis' AND T1.surname = 'Hamilton' AND T3.name = 'Turkish Grand Prix'
|
[
"What",
"is",
"the",
"average",
"score",
"of",
"Lewis",
"Hamilton",
"among",
"all",
"the",
"Turkish",
"Grand",
"Prix",
"?"
] |
[
{
"id": 10,
"type": "value",
"value": "Turkish Grand Prix"
},
{
"id": 3,
"type": "table",
"value": "driverstandings"
},
{
"id": 5,
"type": "column",
"value": "forename"
},
{
"id": 8,
"type": "value",
"value": "Hamilton"
},
{
"id": 11,
"type": "column",
"value": "driverid"
},
{
"id": 2,
"type": "table",
"value": "drivers"
},
{
"id": 7,
"type": "column",
"value": "surname"
},
{
"id": 1,
"type": "column",
"value": "points"
},
{
"id": 4,
"type": "column",
"value": "raceid"
},
{
"id": 0,
"type": "table",
"value": "races"
},
{
"id": 6,
"type": "value",
"value": "Lewis"
},
{
"id": 9,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
11,
12,
13
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,394
|
election
|
spider:train_spider.json:2783
|
Which county has the largest population? Give me the name of the county.
|
SELECT County_name FROM county ORDER BY Population DESC LIMIT 1
|
[
"Which",
"county",
"has",
"the",
"largest",
"population",
"?",
"Give",
"me",
"the",
"name",
"of",
"the",
"county",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "county_name"
},
{
"id": 2,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "county"
}
] |
[
{
"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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"token_idxs": []
},
{
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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,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,395
|
simpson_episodes
|
bird:train.json:4176
|
List down all the roles of Matt Groening on the episode titled 'In the Name of the Grandfather' along with the episode number and series number.
|
SELECT T2.role, T1.episode, T1.number_in_series FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id WHERE T2.person = 'Matt Groening' AND T1.title = 'In the Name of the Grandfather';
|
[
"List",
"down",
"all",
"the",
"roles",
"of",
"Matt",
"Groening",
"on",
"the",
"episode",
"titled",
"'",
"In",
"the",
"Name",
"of",
"the",
"Grandfather",
"'",
"along",
"with",
"the",
"episode",
"number",
"and",
"series",
"number",
"."
] |
[
{
"id": 9,
"type": "value",
"value": "In the Name of the Grandfather"
},
{
"id": 2,
"type": "column",
"value": "number_in_series"
},
{
"id": 7,
"type": "value",
"value": "Matt Groening"
},
{
"id": 5,
"type": "column",
"value": "episode_id"
},
{
"id": 1,
"type": "column",
"value": "episode"
},
{
"id": 3,
"type": "table",
"value": "episode"
},
{
"id": 4,
"type": "table",
"value": "credit"
},
{
"id": 6,
"type": "column",
"value": "person"
},
{
"id": 8,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "role"
}
] |
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"token_idxs": [
4
]
},
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{
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24,
25,
26
]
},
{
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23
]
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{
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6,
7
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11
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13,
14,
15,
16,
17,
18
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{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O"
] |
2,396
|
world_development_indicators
|
bird:train.json:2236
|
Which country's indicator for Adolescent fertility rate is the highest in 1960, please give its special notes.
|
SELECT DISTINCT T1.CountryCode, T1.SpecialNotes FROM Country AS T1 INNER JOIN Indicators AS T2 ON T1.CountryCode = T2.CountryCode WHERE T2.Value = ( SELECT Value FROM Indicators WHERE IndicatorName = 'Adolescent fertility rate (births per 1,000 women ages 15-19)' AND Year = 1960 ORDER BY Value DESC LIMIT 1 )
|
[
"Which",
"country",
"'s",
"indicator",
"for",
"Adolescent",
"fertility",
"rate",
"is",
"the",
"highest",
"in",
"1960",
",",
"please",
"give",
"its",
"special",
"notes",
"."
] |
[
{
"id": 6,
"type": "value",
"value": "Adolescent fertility rate (births per 1,000 women ages 15-19)"
},
{
"id": 5,
"type": "column",
"value": "indicatorname"
},
{
"id": 1,
"type": "column",
"value": "specialnotes"
},
{
"id": 0,
"type": "column",
"value": "countrycode"
},
{
"id": 3,
"type": "table",
"value": "indicators"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "value"
},
{
"id": 7,
"type": "column",
"value": "year"
},
{
"id": 8,
"type": "value",
"value": "1960"
}
] |
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"token_idxs": []
},
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17,
18
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},
{
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"token_idxs": [
1
]
},
{
"entity_id": 3,
"token_idxs": [
3
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},
{
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},
{
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{
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5,
6,
7,
8,
9,
10,
11
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"token_idxs": []
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"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
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{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,397
|
image_and_language
|
bird:train.json:7576
|
Calculate the percentage of object samples that are related to street lights.
|
SELECT CAST(SUM(CASE WHEN T2.OBJ_CLASS = 'street lights' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.OBJ_SAMPLE_ID) FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID
|
[
"Calculate",
"the",
"percentage",
"of",
"object",
"samples",
"that",
"are",
"related",
"to",
"street",
"lights",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "obj_sample_id"
},
{
"id": 8,
"type": "value",
"value": "street lights"
},
{
"id": 2,
"type": "column",
"value": "obj_class_id"
},
{
"id": 1,
"type": "table",
"value": "obj_classes"
},
{
"id": 7,
"type": "column",
"value": "obj_class"
},
{
"id": 0,
"type": "table",
"value": "img_obj"
},
{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "0"
},
{
"id": 6,
"type": "value",
"value": "1"
}
] |
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{
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},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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"entity_id": 4,
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4,
5
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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",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,398
|
food_inspection_2
|
bird:train.json:6151
|
What is the assumed name of the business that has the highest total fine in 2014?
|
SELECT T.dba_name FROM ( SELECT T1.dba_name, SUM(T3.fine) FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no INNER JOIN violation AS T3 ON T2.inspection_id = T3.inspection_id WHERE strftime('%Y', T2.inspection_date) = '2014' GROUP BY T1.dba_name ORDER BY SUM(T3.fine) DESC LIMIT 1 ) AS T
|
[
"What",
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"the",
"assumed",
"name",
"of",
"the",
"business",
"that",
"has",
"the",
"highest",
"total",
"fine",
"in",
"2014",
"?"
] |
[
{
"id": 8,
"type": "column",
"value": "inspection_date"
},
{
"id": 4,
"type": "table",
"value": "establishment"
},
{
"id": 6,
"type": "column",
"value": "inspection_id"
},
{
"id": 5,
"type": "table",
"value": "inspection"
},
{
"id": 9,
"type": "column",
"value": "license_no"
},
{
"id": 1,
"type": "table",
"value": "violation"
},
{
"id": 0,
"type": "column",
"value": "dba_name"
},
{
"id": 2,
"type": "value",
"value": "2014"
},
{
"id": 3,
"type": "column",
"value": "fine"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
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"token_idxs": [
4
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15
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{
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13
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
14
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-VALUE",
"O"
] |
2,399
|
airline
|
bird:train.json:5843
|
How many flights from American Airlines were cancelled due to a type A cancellation code?
|
SELECT COUNT(*) FROM Airlines AS T1 INNER JOIN `Air Carriers` AS T2 ON T1.OP_CARRIER_AIRLINE_ID = T2.Code WHERE T1.CANCELLATION_CODE = 'A' AND T2.Description = 'American Airlines Inc.: AA' AND T1.CANCELLED = 1
|
[
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"many",
"flights",
"from",
"American",
"Airlines",
"were",
"cancelled",
"due",
"to",
"a",
"type",
"A",
"cancellation",
"code",
"?"
] |
[
{
"id": 7,
"type": "value",
"value": "American Airlines Inc.: AA"
},
{
"id": 2,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 4,
"type": "column",
"value": "cancellation_code"
},
{
"id": 1,
"type": "table",
"value": "Air Carriers"
},
{
"id": 6,
"type": "column",
"value": "description"
},
{
"id": 8,
"type": "column",
"value": "cancelled"
},
{
"id": 0,
"type": "table",
"value": "airlines"
},
{
"id": 3,
"type": "column",
"value": "code"
},
{
"id": 5,
"type": "value",
"value": "A"
},
{
"id": 9,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
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]
},
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"entity_id": 2,
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{
"entity_id": 3,
"token_idxs": [
14
]
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"entity_id": 4,
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13
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10
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{
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4
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7
]
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{
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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": []
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"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,400
|
codebase_comments
|
bird:train.json:580
|
What is the average processed time of the solution paths inside the "https://github.com/zphingphong/DiscardCustomerApp.git"?
|
SELECT CAST(SUM(T2.ProcessedTime) AS REAL) / COUNT(T2.RepoId) FROM Repo AS T1 INNER JOIN Solution AS T2 ON T1.Id = T2.RepoId WHERE T1.Url = 'https://github.com/zphingphong/DiscardCustomerApp.git'
|
[
"What",
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"processed",
"time",
"of",
"the",
"solution",
"paths",
"inside",
"the",
"\"",
"https://github.com/zphingphong/DiscardCustomerApp.git",
"\"",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "https://github.com/zphingphong/DiscardCustomerApp.git"
},
{
"id": 6,
"type": "column",
"value": "processedtime"
},
{
"id": 1,
"type": "table",
"value": "solution"
},
{
"id": 5,
"type": "column",
"value": "repoid"
},
{
"id": 0,
"type": "table",
"value": "repo"
},
{
"id": 2,
"type": "column",
"value": "url"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
4,
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
2,401
|
world_development_indicators
|
bird:train.json:2154
|
List out the series code and country code of the poor countries that located in Latin American & Carribbean.
|
SELECT T2.SeriesCode, T2.CountryCode FROM Country AS T1 INNER JOIN CountryNotes AS T2 ON T1.CountryCode = T2.Countrycode WHERE T1.Region = 'Latin America & Caribbean' AND t1.incomegroup = 'Low income'
|
[
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"code",
"of",
"the",
"poor",
"countries",
"that",
"located",
"in",
"Latin",
"American",
"&",
"Carribbean",
"."
] |
[
{
"id": 5,
"type": "value",
"value": "Latin America & Caribbean"
},
{
"id": 3,
"type": "table",
"value": "countrynotes"
},
{
"id": 1,
"type": "column",
"value": "countrycode"
},
{
"id": 6,
"type": "column",
"value": "incomegroup"
},
{
"id": 0,
"type": "column",
"value": "seriescode"
},
{
"id": 7,
"type": "value",
"value": "Low income"
},
{
"id": 2,
"type": "table",
"value": "country"
},
{
"id": 4,
"type": "column",
"value": "region"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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7
]
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"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": [
15,
16,
17,
18
]
},
{
"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": []
},
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"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
2,402
|
toxicology
|
bird:dev.json:265
|
List down the molecule id for non carcinogenic molecules.
|
SELECT T.molecule_id FROM molecule AS T WHERE T.label = '-'
|
[
"List",
"down",
"the",
"molecule",
"i",
"d",
"for",
"non",
"carcinogenic",
"molecules",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "molecule_id"
},
{
"id": 0,
"type": "table",
"value": "molecule"
},
{
"id": 2,
"type": "column",
"value": "label"
},
{
"id": 3,
"type": "value",
"value": "-"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
4,
5
]
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{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
2,403
|
beer_factory
|
bird:train.json:5339
|
How many bottles of beer have been bought by Jim Breech?
|
SELECT COUNT(T3.ContainerType) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T2.CustomerID = T1.CustomerID INNER JOIN rootbeer AS T3 ON T3.RootBeerID = T2.RootBeerID WHERE T3.ContainerType = 'Bottle' AND T1.First = 'Jim' AND T1.Last = 'Breech'
|
[
"How",
"many",
"bottles",
"of",
"beer",
"have",
"been",
"bought",
"by",
"Jim",
"Breech",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "containertype"
},
{
"id": 3,
"type": "table",
"value": "transaction"
},
{
"id": 4,
"type": "column",
"value": "rootbeerid"
},
{
"id": 10,
"type": "column",
"value": "customerid"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 0,
"type": "table",
"value": "rootbeer"
},
{
"id": 5,
"type": "value",
"value": "Bottle"
},
{
"id": 9,
"type": "value",
"value": "Breech"
},
{
"id": 6,
"type": "column",
"value": "first"
},
{
"id": 8,
"type": "column",
"value": "last"
},
{
"id": 7,
"type": "value",
"value": "Jim"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
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},
{
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"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"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",
"B-VALUE",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
2,404
|
hr_1
|
spider:train_spider.json:3512
|
What are total salaries and department id for each department that has more than 2 employees?
|
SELECT department_id , SUM(salary) FROM employees GROUP BY department_id HAVING count(*) >= 2
|
[
"What",
"are",
"total",
"salaries",
"and",
"department",
"i",
"d",
"for",
"each",
"department",
"that",
"has",
"more",
"than",
"2",
"employees",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "department_id"
},
{
"id": 0,
"type": "table",
"value": "employees"
},
{
"id": 3,
"type": "column",
"value": "salary"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
16
]
},
{
"entity_id": 1,
"token_idxs": [
5,
6,
7
]
},
{
"entity_id": 2,
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15
]
},
{
"entity_id": 3,
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3
]
},
{
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},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
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"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
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},
{
"entity_id": 12,
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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-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,405
|
soccer_2016
|
bird:train.json:1791
|
How many players are from Australia?
|
SELECT COUNT(CASE WHEN T2.Country_Name = 'Australia' THEN T1.Player_Id ELSE NULL END) FROM Player AS T1 INNER JOIN Country AS T2 ON T1.Country_Name = T2.Country_Id
|
[
"How",
"many",
"players",
"are",
"from",
"Australia",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "country_name"
},
{
"id": 3,
"type": "column",
"value": "country_id"
},
{
"id": 4,
"type": "column",
"value": "player_id"
},
{
"id": 5,
"type": "value",
"value": "Australia"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 0,
"type": "table",
"value": "player"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
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},
{
"entity_id": 5,
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5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,406
|
college_completion
|
bird:train.json:3692
|
Compare the graduate cohort for Auburn University from 2011 to 2013?
|
SELECT SUM(CASE WHEN T2.year = 2011 THEN T2.grad_cohort ELSE 0 END), SUM(CASE WHEN T2.year = 2012 THEN T2.grad_cohort ELSE 0 END), SUM(CASE WHEN T2.year = 2013 THEN T2.grad_cohort ELSE 0 END) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T1.unitid = T2.unitid WHERE T2.gender = 'B' AND T2.race = 'X' AND T1.chronname = 'Auburn University'
|
[
"Compare",
"the",
"graduate",
"cohort",
"for",
"Auburn",
"University",
"from",
"2011",
"to",
"2013",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "institution_details"
},
{
"id": 1,
"type": "table",
"value": "institution_grads"
},
{
"id": 8,
"type": "value",
"value": "Auburn University"
},
{
"id": 10,
"type": "column",
"value": "grad_cohort"
},
{
"id": 7,
"type": "column",
"value": "chronname"
},
{
"id": 2,
"type": "column",
"value": "unitid"
},
{
"id": 3,
"type": "column",
"value": "gender"
},
{
"id": 5,
"type": "column",
"value": "race"
},
{
"id": 11,
"type": "column",
"value": "year"
},
{
"id": 12,
"type": "value",
"value": "2011"
},
{
"id": 13,
"type": "value",
"value": "2012"
},
{
"id": 14,
"type": "value",
"value": "2013"
},
{
"id": 4,
"type": "value",
"value": "B"
},
{
"id": 6,
"type": "value",
"value": "X"
},
{
"id": 9,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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},
{
"entity_id": 2,
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},
{
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},
{
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},
{
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{
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},
{
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},
{
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5,
6
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},
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},
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2,
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]
},
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},
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},
{
"entity_id": 13,
"token_idxs": [
8
]
},
{
"entity_id": 14,
"token_idxs": [
10
]
},
{
"entity_id": 15,
"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-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
2,407
|
chicago_crime
|
bird:train.json:8616
|
How many different neighborhoods are there in Roseland community?
|
SELECT SUM(CASE WHEN T1.community_area_name = 'Roseland' THEN 1 ELSE 0 END) FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T1.community_area_no = T2.community_area_no
|
[
"How",
"many",
"different",
"neighborhoods",
"are",
"there",
"in",
"Roseland",
"community",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "community_area_name"
},
{
"id": 2,
"type": "column",
"value": "community_area_no"
},
{
"id": 0,
"type": "table",
"value": "community_area"
},
{
"id": 1,
"type": "table",
"value": "neighborhood"
},
{
"id": 6,
"type": "value",
"value": "Roseland"
},
{
"id": 3,
"type": "value",
"value": "0"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
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3
]
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
"entity_id": 4,
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O"
] |
2,408
|
social_media
|
bird:train.json:831
|
State the country where the most positive sentiment tweets were posted.
|
SELECT T.Country FROM ( SELECT T2.Country, SUM(T1.Sentiment) AS num FROM twitter AS T1 INNER JOIN location AS T2 ON T1.LocationID = T2.LocationID WHERE T1.Sentiment > 0 GROUP BY T2.Country ) T ORDER BY T.num DESC LIMIT 1
|
[
"State",
"the",
"country",
"where",
"the",
"most",
"positive",
"sentiment",
"tweets",
"were",
"posted",
"."
] |
[
{
"id": 6,
"type": "column",
"value": "locationid"
},
{
"id": 4,
"type": "column",
"value": "sentiment"
},
{
"id": 3,
"type": "table",
"value": "location"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "table",
"value": "twitter"
},
{
"id": 1,
"type": "column",
"value": "num"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,409
|
movie_3
|
bird:train.json:9239
|
List the titles of the films starred by Elvis Marx.
|
SELECT T3.title FROM actor AS T1 INNER JOIN film_actor AS T2 ON T1.actor_id = T2.actor_id INNER JOIN film AS T3 ON T2.film_id = T3.film_id WHERE T3.length BETWEEN 110 AND 150 AND T1.first_name = 'Russell' AND T1.last_name = 'Close'
|
[
"List",
"the",
"titles",
"of",
"the",
"films",
"starred",
"by",
"Elvis",
"Marx",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "film_actor"
},
{
"id": 8,
"type": "column",
"value": "first_name"
},
{
"id": 10,
"type": "column",
"value": "last_name"
},
{
"id": 12,
"type": "column",
"value": "actor_id"
},
{
"id": 4,
"type": "column",
"value": "film_id"
},
{
"id": 9,
"type": "value",
"value": "Russell"
},
{
"id": 5,
"type": "column",
"value": "length"
},
{
"id": 0,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "actor"
},
{
"id": 11,
"type": "value",
"value": "Close"
},
{
"id": 1,
"type": "table",
"value": "film"
},
{
"id": 6,
"type": "value",
"value": "110"
},
{
"id": 7,
"type": "value",
"value": "150"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
2,410
|
bike_share_1
|
bird:train.json:9068
|
Among the bike trips started on the days with a fog in 2013, how many of those trips started from the station "2nd at Townsend"?
|
SELECT COUNT(T1.start_station_name) FROM trip AS T1 INNER JOIN weather AS T2 ON T2.zip_code = T1.zip_code WHERE T2.date LIKE '%2013%' AND T2.events = 'Fog' AND T1.start_station_name = '2nd at Townsend' AND T2.zip_code = 94107
|
[
"Among",
"the",
"bike",
"trips",
"started",
"on",
"the",
"days",
"with",
"a",
"fog",
"in",
"2013",
",",
"how",
"many",
"of",
"those",
"trips",
"started",
"from",
"the",
"station",
"\"",
"2nd",
"at",
"Townsend",
"\"",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "start_station_name"
},
{
"id": 8,
"type": "value",
"value": "2nd at Townsend"
},
{
"id": 3,
"type": "column",
"value": "zip_code"
},
{
"id": 1,
"type": "table",
"value": "weather"
},
{
"id": 5,
"type": "value",
"value": "%2013%"
},
{
"id": 6,
"type": "column",
"value": "events"
},
{
"id": 9,
"type": "value",
"value": "94107"
},
{
"id": 0,
"type": "table",
"value": "trip"
},
{
"id": 4,
"type": "column",
"value": "date"
},
{
"id": 7,
"type": "value",
"value": "Fog"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
25
]
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": [
24,
26
]
},
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-VALUE",
"O",
"O"
] |
2,411
|
wrestler
|
spider:train_spider.json:1875
|
Which locations are shared by more than two wrestlers?
|
SELECT LOCATION FROM wrestler GROUP BY LOCATION HAVING COUNT(*) > 2
|
[
"Which",
"locations",
"are",
"shared",
"by",
"more",
"than",
"two",
"wrestlers",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "wrestler"
},
{
"id": 1,
"type": "column",
"value": "location"
},
{
"id": 2,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,412
|
customers_and_invoices
|
spider:train_spider.json:1584
|
Return the average, minimum, maximum, and total transaction amounts.
|
SELECT avg(transaction_amount) , min(transaction_amount) , max(transaction_amount) , sum(transaction_amount) FROM Financial_transactions
|
[
"Return",
"the",
"average",
",",
"minimum",
",",
"maximum",
",",
"and",
"total",
"transaction",
"amounts",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "financial_transactions"
},
{
"id": 1,
"type": "column",
"value": "transaction_amount"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8,
9
]
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"I-COLUMN",
"O"
] |
2,413
|
california_schools
|
bird:dev.json:67
|
What is the total amount of Community College District closure in 1989 in the city of San Francisco?
|
SELECT COUNT(School) FROM schools WHERE strftime('%Y', ClosedDate) = '1989' AND City = 'San Francisco' AND DOCType = 'Community College District'
|
[
"What",
"is",
"the",
"total",
"amount",
"of",
"Community",
"College",
"District",
"closure",
"in",
"1989",
"in",
"the",
"city",
"of",
"San",
"Francisco",
"?"
] |
[
{
"id": 6,
"type": "value",
"value": "Community College District"
},
{
"id": 4,
"type": "value",
"value": "San Francisco"
},
{
"id": 8,
"type": "column",
"value": "closeddate"
},
{
"id": 0,
"type": "table",
"value": "schools"
},
{
"id": 5,
"type": "column",
"value": "doctype"
},
{
"id": 1,
"type": "column",
"value": "school"
},
{
"id": 2,
"type": "value",
"value": "1989"
},
{
"id": 3,
"type": "column",
"value": "city"
},
{
"id": 7,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"entity_id": 4,
"token_idxs": [
16,
17
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": [
6,
7,
8
]
},
{
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},
{
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9
]
},
{
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,415
|
cre_Students_Information_Systems
|
bird:test.json:443
|
List the details of the teachers who teach some class whose detail has the substring 'data' but do not teach a class whose detail contains the prefix 'net'
|
SELECT T1.teacher_details FROM Teachers AS T1 JOIN Classes AS T2 ON T1.teacher_id = T2.teacher_id WHERE T2.class_details LIKE '%data%' EXCEPT SELECT T1.teacher_details FROM Teachers AS T1 JOIN Classes AS T2 ON T1.teacher_id = T2.teacher_id WHERE T2.class_details LIKE 'net%'
|
[
"List",
"the",
"details",
"of",
"the",
"teachers",
"who",
"teach",
"some",
"class",
"whose",
"detail",
"has",
"the",
"substring",
"'",
"data",
"'",
"but",
"do",
"not",
"teach",
"a",
"class",
"whose",
"detail",
"contains",
"the",
"prefix",
"'",
"net",
"'"
] |
[
{
"id": 0,
"type": "column",
"value": "teacher_details"
},
{
"id": 3,
"type": "column",
"value": "class_details"
},
{
"id": 6,
"type": "column",
"value": "teacher_id"
},
{
"id": 1,
"type": "table",
"value": "teachers"
},
{
"id": 2,
"type": "table",
"value": "classes"
},
{
"id": 4,
"type": "value",
"value": "%data%"
},
{
"id": 5,
"type": "value",
"value": "net%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1,
2
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
23
]
},
{
"entity_id": 3,
"token_idxs": [
24,
25
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": [
30
]
},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,416
|
formula_1
|
spider:train_spider.json:2211
|
What is the id and last name of the driver who participated in the most races after 2010?
|
SELECT T1.driverid , T1.surname FROM drivers AS T1 JOIN results AS T2 ON T1.driverid = T2.driverid JOIN races AS T3 ON T2.raceid = T3.raceid WHERE T3.year > 2010 GROUP BY T1.driverid ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"i",
"d",
"and",
"last",
"name",
"of",
"the",
"driver",
"who",
"participated",
"in",
"the",
"most",
"races",
"after",
"2010",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "driverid"
},
{
"id": 1,
"type": "column",
"value": "surname"
},
{
"id": 5,
"type": "table",
"value": "drivers"
},
{
"id": 6,
"type": "table",
"value": "results"
},
{
"id": 7,
"type": "column",
"value": "raceid"
},
{
"id": 2,
"type": "table",
"value": "races"
},
{
"id": 3,
"type": "column",
"value": "year"
},
{
"id": 4,
"type": "value",
"value": "2010"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
16
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
18
]
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
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},
{
"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,
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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",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,418
|
retail_complains
|
bird:train.json:360
|
Write down the date received of complaints sent via Fax.
|
SELECT T1.`Date received` FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.`Submitted via` = 'Fax'
|
[
"Write",
"down",
"the",
"date",
"received",
"of",
"complaints",
"sent",
"via",
"Fax",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 0,
"type": "column",
"value": "Date received"
},
{
"id": 3,
"type": "column",
"value": "Submitted via"
},
{
"id": 5,
"type": "column",
"value": "Complaint ID"
},
{
"id": 2,
"type": "table",
"value": "events"
},
{
"id": 4,
"type": "value",
"value": "Fax"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"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",
"I-COLUMN",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,419
|
olympics
|
bird:train.json:5007
|
What is Vijay Singh Chauhan's region name?
|
SELECT T1.region_name FROM noc_region AS T1 INNER JOIN person_region AS T2 ON T1.id = T2.region_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T3.full_name = 'Vijay Singh Chauhan'
|
[
"What",
"is",
"Vijay",
"Singh",
"Chauhan",
"'s",
"region",
"name",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "Vijay Singh Chauhan"
},
{
"id": 5,
"type": "table",
"value": "person_region"
},
{
"id": 0,
"type": "column",
"value": "region_name"
},
{
"id": 4,
"type": "table",
"value": "noc_region"
},
{
"id": 2,
"type": "column",
"value": "full_name"
},
{
"id": 6,
"type": "column",
"value": "person_id"
},
{
"id": 8,
"type": "column",
"value": "region_id"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
6
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,420
|
university_basketball
|
spider:train_spider.json:1001
|
Find the total student enrollment for different affiliation type schools.
|
SELECT sum(enrollment) , affiliation FROM university GROUP BY affiliation
|
[
"Find",
"the",
"total",
"student",
"enrollment",
"for",
"different",
"affiliation",
"type",
"schools",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "affiliation"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "column",
"value": "enrollment"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O"
] |
2,421
|
works_cycles
|
bird:train.json:7327
|
Name the sales person for store Area Bike Accessories. Which territory is he / she in?
|
SELECT T4.Name FROM Store AS T1 INNER JOIN SalesPerson AS T2 ON T1.SalesPersonID = T2.BusinessEntityID INNER JOIN Person AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID INNER JOIN SalesTerritory AS T4 ON T2.TerritoryID = T4.TerritoryID WHERE T1.Name = 'Area Bike Accessories'
|
[
"Name",
"the",
"sales",
"person",
"for",
"store",
"Area",
"Bike",
"Accessories",
".",
"Which",
"territory",
"is",
"he",
"/",
"she",
"in",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "Area Bike Accessories"
},
{
"id": 7,
"type": "column",
"value": "businessentityid"
},
{
"id": 1,
"type": "table",
"value": "salesterritory"
},
{
"id": 8,
"type": "column",
"value": "salespersonid"
},
{
"id": 4,
"type": "column",
"value": "territoryid"
},
{
"id": 6,
"type": "table",
"value": "salesperson"
},
{
"id": 3,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "table",
"value": "store"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
0
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,422
|
retail_complains
|
bird:train.json:289
|
List by their ID number the 3 longest complaints.
|
SELECT `Complaint ID` FROM callcenterlogs ORDER BY ser_time DESC LIMIT 3
|
[
"List",
"by",
"their",
"ID",
"number",
"the",
"3",
"longest",
"complaints",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "callcenterlogs"
},
{
"id": 1,
"type": "column",
"value": "Complaint ID"
},
{
"id": 2,
"type": "column",
"value": "ser_time"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,423
|
news_report
|
spider:train_spider.json:2815
|
Show the names of journalists that have reported more than one event.
|
SELECT T3.Name FROM news_report AS T1 JOIN event AS T2 ON T1.Event_ID = T2.Event_ID JOIN journalist AS T3 ON T1.journalist_ID = T3.journalist_ID GROUP BY T3.Name HAVING COUNT(*) > 1
|
[
"Show",
"the",
"names",
"of",
"journalists",
"that",
"have",
"reported",
"more",
"than",
"one",
"event",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "journalist_id"
},
{
"id": 3,
"type": "table",
"value": "news_report"
},
{
"id": 1,
"type": "table",
"value": "journalist"
},
{
"id": 6,
"type": "column",
"value": "event_id"
},
{
"id": 4,
"type": "table",
"value": "event"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,424
|
superstore
|
bird:train.json:2375
|
How much is the total quantity of items from the East region shipped on 3/25/2015? Name the products.
|
SELECT SUM(T1.Quantity), T2.`Product Name` FROM east_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T1.`Ship Date` = '2015-03-25' AND T2.Region = 'East'
|
[
"How",
"much",
"is",
"the",
"total",
"quantity",
"of",
"items",
"from",
"the",
"East",
"region",
"shipped",
"on",
"3/25/2015",
"?",
"Name",
"the",
"products",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "east_superstore"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 4,
"type": "column",
"value": "Product ID"
},
{
"id": 6,
"type": "value",
"value": "2015-03-25"
},
{
"id": 5,
"type": "column",
"value": "Ship Date"
},
{
"id": 3,
"type": "column",
"value": "quantity"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 7,
"type": "column",
"value": "region"
},
{
"id": 8,
"type": "value",
"value": "East"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
18
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
12
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
11
]
},
{
"entity_id": 8,
"token_idxs": [
10
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,425
|
product_catalog
|
spider:train_spider.json:339
|
How many products are there in the records?
|
SELECT count(*) FROM catalog_contents
|
[
"How",
"many",
"products",
"are",
"there",
"in",
"the",
"records",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "catalog_contents"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_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"
] |
2,427
|
book_1
|
bird:test.json:539
|
Show the book title corresponding to the book with the most number of orders.
|
SELECT T2.title FROM Books_Order AS T1 JOIN Book AS T2 ON T1.isbn = T2.isbn GROUP BY T1.isbn ORDER BY count(*) DESC LIMIT 1
|
[
"Show",
"the",
"book",
"title",
"corresponding",
"to",
"the",
"book",
"with",
"the",
"most",
"number",
"of",
"orders",
"."
] |
[
{
"id": 2,
"type": "table",
"value": "books_order"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "isbn"
},
{
"id": 3,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12,
13
]
},
{
"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,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,428
|
university
|
bird:train.json:8045
|
What are the top three universities with the most international students?
|
SELECT DISTINCT T2.university_name FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id GROUP BY T2.university_name ORDER BY SUM(T1.num_students * T1.pct_international_students / 100) DESC LIMIT 3
|
[
"What",
"are",
"the",
"top",
"three",
"universities",
"with",
"the",
"most",
"international",
"students",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "pct_international_students"
},
{
"id": 0,
"type": "column",
"value": "university_name"
},
{
"id": 1,
"type": "table",
"value": "university_year"
},
{
"id": 3,
"type": "column",
"value": "university_id"
},
{
"id": 6,
"type": "column",
"value": "num_students"
},
{
"id": 2,
"type": "table",
"value": "university"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"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",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,429
|
address
|
bird:train.json:5082
|
What is the total number of households in Arecibo county?
|
SELECT SUM(T1.households) FROM zip_data AS T1 INNER JOIN country AS T2 ON T1.zip_code = T2.zip_code WHERE T2.county = 'ARECIBO'
|
[
"What",
"is",
"the",
"total",
"number",
"of",
"households",
"in",
"Arecibo",
"county",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "households"
},
{
"id": 0,
"type": "table",
"value": "zip_data"
},
{
"id": 5,
"type": "column",
"value": "zip_code"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "value",
"value": "ARECIBO"
},
{
"id": 2,
"type": "column",
"value": "county"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
8
]
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
2,430
|
book_1
|
bird:test.json:568
|
What are the titles of books that have a sale price equal to the lowest sale price across all books ?
|
select title from book order by saleprice asc limit 1
|
[
"What",
"are",
"the",
"titles",
"of",
"books",
"that",
"have",
"a",
"sale",
"price",
"equal",
"to",
"the",
"lowest",
"sale",
"price",
"across",
"all",
"books",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "saleprice"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "table",
"value": "book"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
19
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15,
16
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O"
] |
2,431
|
product_catalog
|
spider:train_spider.json:310
|
Which catalog publishers have substring "Murray" in their names?
|
SELECT distinct(catalog_publisher) FROM catalogs WHERE catalog_publisher LIKE "%Murray%"
|
[
"Which",
"catalog",
"publishers",
"have",
"substring",
"\"",
"Murray",
"\"",
"in",
"their",
"names",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "catalog_publisher"
},
{
"id": 0,
"type": "table",
"value": "catalogs"
},
{
"id": 2,
"type": "column",
"value": "%Murray%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
1
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
2,432
|
language_corpus
|
bird:train.json:5725
|
How many total occurrences are there in the three-letter words?
|
SELECT SUM(occurrences) FROM words WHERE LENGTH(word) = 3
|
[
"How",
"many",
"total",
"occurrences",
"are",
"there",
"in",
"the",
"three",
"-",
"letter",
"words",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "occurrences"
},
{
"id": 0,
"type": "table",
"value": "words"
},
{
"id": 3,
"type": "column",
"value": "word"
},
{
"id": 1,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"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",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,433
|
chicago_crime
|
bird:train.json:8769
|
Which district commander was responsible for more incidents in January, 2018, Robert A. Rubio or Glenn White?
|
SELECT T1.commander FROM District AS T1 INNER JOIN Crime AS T2 ON T1.district_no = T2.district_no WHERE T1.commander IN ('Robert A. Rubio', 'Glenn White') AND SUBSTR(T2.date, 1, 1) = '1' AND SUBSTR(T2.date, 5, 4) = '2018' GROUP BY T1.commander
|
[
"Which",
"district",
"commander",
"was",
"responsible",
"for",
"more",
"incidents",
"in",
"January",
",",
"2018",
",",
"Robert",
"A.",
"Rubio",
"or",
"Glenn",
"White",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Robert A. Rubio"
},
{
"id": 3,
"type": "column",
"value": "district_no"
},
{
"id": 5,
"type": "value",
"value": "Glenn White"
},
{
"id": 0,
"type": "column",
"value": "commander"
},
{
"id": 1,
"type": "table",
"value": "district"
},
{
"id": 2,
"type": "table",
"value": "crime"
},
{
"id": 7,
"type": "value",
"value": "2018"
},
{
"id": 8,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 9,
"type": "value",
"value": "5"
},
{
"id": 10,
"type": "value",
"value": "4"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
14,
15
]
},
{
"entity_id": 5,
"token_idxs": [
17,
18
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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11
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
2,434
|
bakery_1
|
bird:test.json:1515
|
What is the receipt number and date of the receipt in which the most expensive item was bought?
|
SELECT T1.ReceiptNumber , T1.Date FROM receipts AS T1 JOIN items AS T2 ON T1.ReceiptNumber = T2.receipt JOIN goods AS T3 ON T2.item = T3.id ORDER BY T3.price DESC LIMIT 1
|
[
"What",
"is",
"the",
"receipt",
"number",
"and",
"date",
"of",
"the",
"receipt",
"in",
"which",
"the",
"most",
"expensive",
"item",
"was",
"bought",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "receiptnumber"
},
{
"id": 4,
"type": "table",
"value": "receipts"
},
{
"id": 8,
"type": "column",
"value": "receipt"
},
{
"id": 2,
"type": "table",
"value": "goods"
},
{
"id": 3,
"type": "column",
"value": "price"
},
{
"id": 5,
"type": "table",
"value": "items"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 6,
"type": "column",
"value": "item"
},
{
"id": 7,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
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{
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{
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{
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{
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{
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{
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]
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
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"entity_id": 11,
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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",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,435
|
mondial_geo
|
bird:train.json:8393
|
In which country is the city of Grozny? Give the full name of the country.
|
SELECT T1.Name FROM country AS T1 INNER JOIN province AS T2 ON T1.Code = T2.Country INNER JOIN city AS T3 ON T3.Province = T2.Name WHERE T3.Name = 'Grozny'
|
[
"In",
"which",
"country",
"is",
"the",
"city",
"of",
"Grozny",
"?",
"Give",
"the",
"full",
"name",
"of",
"the",
"country",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "province"
},
{
"id": 5,
"type": "column",
"value": "province"
},
{
"id": 3,
"type": "table",
"value": "country"
},
{
"id": 7,
"type": "column",
"value": "country"
},
{
"id": 2,
"type": "value",
"value": "Grozny"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 6,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
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5
]
},
{
"entity_id": 2,
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7
]
},
{
"entity_id": 3,
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{
"entity_id": 4,
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{
"entity_id": 5,
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{
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"token_idxs": []
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"token_idxs": []
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"token_idxs": []
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"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
2,436
|
music_1
|
spider:train_spider.json:3616
|
What is the id of every song that has a resolution higher than that of a song with a rating below 8?
|
SELECT f_id FROM song WHERE resolution > (SELECT max(resolution) FROM song WHERE rating < 8)
|
[
"What",
"is",
"the",
"i",
"d",
"of",
"every",
"song",
"that",
"has",
"a",
"resolution",
"higher",
"than",
"that",
"of",
"a",
"song",
"with",
"a",
"rating",
"below",
"8",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "resolution"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "song"
},
{
"id": 1,
"type": "column",
"value": "f_id"
},
{
"id": 4,
"type": "value",
"value": "8"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
17
]
},
{
"entity_id": 1,
"token_idxs": [
3,
4
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
20
]
},
{
"entity_id": 4,
"token_idxs": [
22
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
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},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,437
|
hockey
|
bird:train.json:7744
|
How many teams did the team with the most victories in 1915 play against?
Indicate the name of the team who won the most games in 1915, as well as the names of the opposing team.
|
SELECT COUNT(DISTINCT oppID), T2.tmID, T2.oppID FROM Teams AS T1 INNER JOIN TeamVsTeam AS T2 ON T1.year = T2.year AND T1.tmID = T2.tmID WHERE T2.year = 1915 GROUP BY T2.tmID, T2.oppID ORDER BY SUM(T2.W) DESC LIMIT 1
|
[
"How",
"many",
"teams",
"did",
"the",
"team",
"with",
"the",
"most",
"victories",
"in",
"1915",
"play",
"against",
"?",
"\n",
"Indicate",
"the",
"name",
"of",
"the",
"team",
"who",
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"the",
"most",
"games",
"in",
"1915",
",",
"as",
"well",
"as",
"the",
"names",
"of",
"the",
"opposing",
"team",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "teamvsteam"
},
{
"id": 1,
"type": "column",
"value": "oppid"
},
{
"id": 2,
"type": "table",
"value": "teams"
},
{
"id": 0,
"type": "column",
"value": "tmid"
},
{
"id": 4,
"type": "column",
"value": "year"
},
{
"id": 5,
"type": "value",
"value": "1915"
},
{
"id": 6,
"type": "column",
"value": "w"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
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37
]
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{
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},
{
"entity_id": 3,
"token_idxs": [
20,
21
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
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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",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
2,438
|
retail_world
|
bird:train.json:6389
|
List the name, address, and phone number of companies that supply products for more than thirty dollars per unit.
|
SELECT T2.CompanyName, T2.Address, T2.Phone FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T1.UnitPrice > 30
|
[
"List",
"the",
"name",
",",
"address",
",",
"and",
"phone",
"number",
"of",
"companies",
"that",
"supply",
"products",
"for",
"more",
"than",
"thirty",
"dollars",
"per",
"unit",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "companyname"
},
{
"id": 7,
"type": "column",
"value": "supplierid"
},
{
"id": 4,
"type": "table",
"value": "suppliers"
},
{
"id": 5,
"type": "column",
"value": "unitprice"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 1,
"type": "column",
"value": "address"
},
{
"id": 2,
"type": "column",
"value": "phone"
},
{
"id": 6,
"type": "value",
"value": "30"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
10
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
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{
"entity_id": 12,
"token_idxs": []
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{
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"token_idxs": []
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{
"entity_id": 14,
"token_idxs": []
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{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
2,439
|
book_1
|
bird:test.json:552
|
What are the names of all the clients, and the total amount of books ordered by each?
|
SELECT T2.name , sum(T3.amount) FROM Orders AS T1 JOIN Client AS T2 ON T1.idClient = T2.idClient JOIN Books_Order AS T3 ON T3.idOrder = T1.idOrder GROUP BY T1.idClient
|
[
"What",
"are",
"the",
"names",
"of",
"all",
"the",
"clients",
",",
"and",
"the",
"total",
"amount",
"of",
"books",
"ordered",
"by",
"each",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "books_order"
},
{
"id": 0,
"type": "column",
"value": "idclient"
},
{
"id": 6,
"type": "column",
"value": "idorder"
},
{
"id": 3,
"type": "column",
"value": "amount"
},
{
"id": 4,
"type": "table",
"value": "orders"
},
{
"id": 5,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
15
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O"
] |
2,440
|
sales
|
bird:train.json:5386
|
Has Alex purchased product with id 498?
|
SELECT IIF(T1.ProductID = 498, 'YES', 'NO') FROM Sales AS T1 INNER JOIN Customers AS T2 ON T1.CustomerID = T2.CustomerID WHERE T2.FirstName = 'Alex'
|
[
"Has",
"Alex",
"purchased",
"product",
"with",
"i",
"d",
"498",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "column",
"value": "firstname"
},
{
"id": 7,
"type": "column",
"value": "productid"
},
{
"id": 0,
"type": "table",
"value": "sales"
},
{
"id": 3,
"type": "value",
"value": "Alex"
},
{
"id": 4,
"type": "value",
"value": "YES"
},
{
"id": 8,
"type": "value",
"value": "498"
},
{
"id": 5,
"type": "value",
"value": "NO"
}
] |
[
{
"entity_id": 0,
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},
{
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},
{
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},
{
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1
]
},
{
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},
{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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3
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},
{
"entity_id": 8,
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7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
2,441
|
cre_Drama_Workshop_Groups
|
spider:train_spider.json:5103
|
What are the minimum, average, and maximum quantities ordered? Check all the invoices.
|
SELECT min(Order_Quantity) , avg(Order_Quantity) , max(Order_Quantity) FROM INVOICES
|
[
"What",
"are",
"the",
"minimum",
",",
"average",
",",
"and",
"maximum",
"quantities",
"ordered",
"?",
"Check",
"all",
"the",
"invoices",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "order_quantity"
},
{
"id": 0,
"type": "table",
"value": "invoices"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
2,443
|
student_loan
|
bird:train.json:4560
|
How many female students have enlisted for the Army?
|
SELECT SUM(IIF(T3.name IS NULL, 1, 0)) AS "result" FROM enlist AS T1 INNER JOIN person AS T2 ON T1.name = T2.name LEFT JOIN male AS T3 ON T2.name = T3.name WHERE T1.organ = 'army'
|
[
"How",
"many",
"female",
"students",
"have",
"enlisted",
"for",
"the",
"Army",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "enlist"
},
{
"id": 4,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "organ"
},
{
"id": 0,
"type": "table",
"value": "male"
},
{
"id": 2,
"type": "value",
"value": "army"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,444
|
insurance_and_eClaims
|
spider:train_spider.json:1531
|
Find the names of the customers who have an deputy policy.
|
SELECT DISTINCT t2.customer_details FROM policies AS t1 JOIN customers AS t2 ON t1.customer_id = t2.customer_id WHERE t1.policy_type_code = "Deputy"
|
[
"Find",
"the",
"names",
"of",
"the",
"customers",
"who",
"have",
"an",
"deputy",
"policy",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "customer_details"
},
{
"id": 3,
"type": "column",
"value": "policy_type_code"
},
{
"id": 5,
"type": "column",
"value": "customer_id"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "table",
"value": "policies"
},
{
"id": 4,
"type": "column",
"value": "Deputy"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
2,445
|
works_cycles
|
bird:train.json:7276
|
Among the sales with a tax applied to retail transaction, how many of them are charged by multiple types of taxes?
|
SELECT COUNT(SalesTaxRateID) FROM SalesTaxRate WHERE Name LIKE '%+%'
|
[
"Among",
"the",
"sales",
"with",
"a",
"tax",
"applied",
"to",
"retail",
"transaction",
",",
"how",
"many",
"of",
"them",
"are",
"charged",
"by",
"multiple",
"types",
"of",
"taxes",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "salestaxrateid"
},
{
"id": 0,
"type": "table",
"value": "salestaxrate"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "value",
"value": "%+%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
3,
4,
5,
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,446
|
image_and_language
|
bird:train.json:7484
|
Please list all the predicted relation classes of object sample no.14 in image no.1.
|
SELECT T1.PRED_CLASS FROM PRED_CLASSES AS T1 INNER JOIN IMG_REL AS T2 ON T1.PRED_CLASS_ID = T2.PRED_CLASS_ID WHERE T2.OBJ1_SAMPLE_ID = 14 AND T2.OBJ2_SAMPLE_ID = 14
|
[
"Please",
"list",
"all",
"the",
"predicted",
"relation",
"classes",
"of",
"object",
"sample",
"no.14",
"in",
"image",
"no.1",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "obj1_sample_id"
},
{
"id": 6,
"type": "column",
"value": "obj2_sample_id"
},
{
"id": 3,
"type": "column",
"value": "pred_class_id"
},
{
"id": 1,
"type": "table",
"value": "pred_classes"
},
{
"id": 0,
"type": "column",
"value": "pred_class"
},
{
"id": 2,
"type": "table",
"value": "img_rel"
},
{
"id": 5,
"type": "value",
"value": "14"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
8,
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O"
] |
2,447
|
customers_and_orders
|
bird:test.json:295
|
What is the customer id, name, phone, and email for the customer with most orders?
|
SELECT T1.customer_id , T2.customer_name , T2.customer_phone , T2.customer_email FROM Customer_orders AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id GROUP BY T1.customer_id ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"customer",
"i",
"d",
",",
"name",
",",
"phone",
",",
"and",
"email",
"for",
"the",
"customer",
"with",
"most",
"orders",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "customer_orders"
},
{
"id": 2,
"type": "column",
"value": "customer_phone"
},
{
"id": 3,
"type": "column",
"value": "customer_email"
},
{
"id": 1,
"type": "column",
"value": "customer_name"
},
{
"id": 0,
"type": "column",
"value": "customer_id"
},
{
"id": 5,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4,
5
]
},
{
"entity_id": 1,
"token_idxs": [
6,
7
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16,
17,
18
]
},
{
"entity_id": 5,
"token_idxs": [
3
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"I-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
2,448
|
retails
|
bird:train.json:6688
|
Among all the customers, what is the percentage of the customer's nation being Germany?
|
SELECT CAST(SUM(IIF(T2.n_name = 'GERMANY', 1, 0)) AS REAL) * 100 / COUNT(T1.c_custkey) FROM customer AS T1 INNER JOIN nation AS T2 ON T1.c_nationkey = T2.n_nationkey
|
[
"Among",
"all",
"the",
"customers",
",",
"what",
"is",
"the",
"percentage",
"of",
"the",
"customer",
"'s",
"nation",
"being",
"Germany",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "c_nationkey"
},
{
"id": 3,
"type": "column",
"value": "n_nationkey"
},
{
"id": 5,
"type": "column",
"value": "c_custkey"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 9,
"type": "value",
"value": "GERMANY"
},
{
"id": 1,
"type": "table",
"value": "nation"
},
{
"id": 8,
"type": "column",
"value": "n_name"
},
{
"id": 4,
"type": "value",
"value": "100"
},
{
"id": 6,
"type": "value",
"value": "1"
},
{
"id": 7,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
11
]
},
{
"entity_id": 1,
"token_idxs": [
13
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
15
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
2,449
|
customers_card_transactions
|
spider:train_spider.json:674
|
Give the full name and phone of the customer who has the account name 162.
|
SELECT T2.customer_first_name , T2.customer_last_name , T2.customer_phone FROM Accounts AS T1 JOIN Customers AS T2 ON T1.customer_id = T2.customer_id WHERE T1.account_name = "162"
|
[
"Give",
"the",
"full",
"name",
"and",
"phone",
"of",
"the",
"customer",
"who",
"has",
"the",
"account",
"name",
"162",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "customer_first_name"
},
{
"id": 1,
"type": "column",
"value": "customer_last_name"
},
{
"id": 2,
"type": "column",
"value": "customer_phone"
},
{
"id": 5,
"type": "column",
"value": "account_name"
},
{
"id": 7,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "table",
"value": "customers"
},
{
"id": 3,
"type": "table",
"value": "accounts"
},
{
"id": 6,
"type": "column",
"value": "162"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
10,
11
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
2,450
|
works_cycles
|
bird:train.json:7315
|
What is the job title of the oldest employee in the company? In which department is he in?
|
SELECT T2.JobTitle, T4.Name FROM Person AS T1 INNER JOIN Employee AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID INNER JOIN EmployeeDepartmentHistory AS T3 ON T2.BusinessEntityID = T3.BusinessEntityID INNER JOIN Department AS T4 ON T3.DepartmentID = T4.DepartmentID ORDER BY T2.HireDate LIMIT 1
|
[
"What",
"is",
"the",
"job",
"title",
"of",
"the",
"oldest",
"employee",
"in",
"the",
"company",
"?",
"In",
"which",
"department",
"is",
"he",
"in",
"?"
] |
[
{
"id": 4,
"type": "table",
"value": "employeedepartmenthistory"
},
{
"id": 8,
"type": "column",
"value": "businessentityid"
},
{
"id": 5,
"type": "column",
"value": "departmentid"
},
{
"id": 2,
"type": "table",
"value": "department"
},
{
"id": 0,
"type": "column",
"value": "jobtitle"
},
{
"id": 3,
"type": "column",
"value": "hiredate"
},
{
"id": 7,
"type": "table",
"value": "employee"
},
{
"id": 6,
"type": "table",
"value": "person"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"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",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"B-TABLE",
"O",
"O",
"O"
] |
2,451
|
superhero
|
bird:dev.json:798
|
What is the publisher for Hawkman, Karate Kid and Speedy?
|
SELECT T2.publisher_name FROM superhero AS T1 INNER JOIN publisher AS T2 ON T1.publisher_id = T2.id WHERE T1.superhero_name IN ('Hawkman', 'Karate Kid', 'Speedy')
|
[
"What",
"is",
"the",
"publisher",
"for",
"Hawkman",
",",
"Karate",
"Kid",
"and",
"Speedy",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "publisher_name"
},
{
"id": 3,
"type": "column",
"value": "superhero_name"
},
{
"id": 7,
"type": "column",
"value": "publisher_id"
},
{
"id": 5,
"type": "value",
"value": "Karate Kid"
},
{
"id": 1,
"type": "table",
"value": "superhero"
},
{
"id": 2,
"type": "table",
"value": "publisher"
},
{
"id": 4,
"type": "value",
"value": "Hawkman"
},
{
"id": 6,
"type": "value",
"value": "Speedy"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"entity_id": 6,
"token_idxs": [
10
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
8
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
2,452
|
retail_world
|
bird:train.json:6506
|
In 1996, how many orders were from customers in the UK?
|
SELECT COUNT(T1.CustomerID) FROM Customers AS T1 INNER JOIN Orders AS T2 ON T1.CustomerID = T2.CustomerID WHERE STRFTIME('%Y', T2.OrderDate) = '1996' AND T1.Country = 'UK'
|
[
"In",
"1996",
",",
"how",
"many",
"orders",
"were",
"from",
"customers",
"in",
"the",
"UK",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 7,
"type": "column",
"value": "orderdate"
},
{
"id": 4,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "orders"
},
{
"id": 3,
"type": "value",
"value": "1996"
},
{
"id": 5,
"type": "value",
"value": "UK"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O"
] |
2,453
|
beer_factory
|
bird:train.json:5278
|
How many Henry Weinhard's were bought by Nicholas Sparks?
|
SELECT COUNT(T1.CustomerID) FROM customers AS T1 INNER JOIN `transaction` AS T2 ON T1.CustomerID = T2.CustomerID INNER JOIN rootbeer AS T3 ON T2.RootBeerID = T3.RootBeerID INNER JOIN rootbeerbrand AS T4 ON T3.BrandID = T4.BrandID WHERE T1.First = 'Nicholas' AND T1.Last = 'Sparks' AND T4.BrandName LIKE 'Henry Weinhard%s'
|
[
"How",
"many",
"Henry",
"Weinhard",
"'s",
"were",
"bought",
"by",
"Nicholas",
"Sparks",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "Henry Weinhard%s"
},
{
"id": 0,
"type": "table",
"value": "rootbeerbrand"
},
{
"id": 11,
"type": "table",
"value": "transaction"
},
{
"id": 1,
"type": "column",
"value": "customerid"
},
{
"id": 12,
"type": "column",
"value": "rootbeerid"
},
{
"id": 8,
"type": "column",
"value": "brandname"
},
{
"id": 10,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "table",
"value": "rootbeer"
},
{
"id": 5,
"type": "value",
"value": "Nicholas"
},
{
"id": 3,
"type": "column",
"value": "brandid"
},
{
"id": 7,
"type": "value",
"value": "Sparks"
},
{
"id": 4,
"type": "column",
"value": "first"
},
{
"id": 6,
"type": "column",
"value": "last"
}
] |
[
{
"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": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
2,
3,
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",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
2,454
|
products_gen_characteristics
|
spider:train_spider.json:5566
|
Find the number of characteristics that the product "flax" has.
|
SELECT count(*) FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN CHARACTERISTICS AS t3 ON t2.characteristic_id = t3.characteristic_id WHERE t1.product_name = "flax"
|
[
"Find",
"the",
"number",
"of",
"characteristics",
"that",
"the",
"product",
"\"",
"flax",
"\"",
"has",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "product_characteristics"
},
{
"id": 5,
"type": "column",
"value": "characteristic_id"
},
{
"id": 0,
"type": "table",
"value": "characteristics"
},
{
"id": 1,
"type": "column",
"value": "product_name"
},
{
"id": 6,
"type": "column",
"value": "product_id"
},
{
"id": 3,
"type": "table",
"value": "products"
},
{
"id": 2,
"type": "column",
"value": "flax"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O"
] |
2,455
|
music_1
|
spider:train_spider.json:3615
|
What is ids of the songs whose resolution is higher than the resolution of any songs with rating lower than 8?
|
SELECT f_id FROM song WHERE resolution > (SELECT max(resolution) FROM song WHERE rating < 8)
|
[
"What",
"is",
"ids",
"of",
"the",
"songs",
"whose",
"resolution",
"is",
"higher",
"than",
"the",
"resolution",
"of",
"any",
"songs",
"with",
"rating",
"lower",
"than",
"8",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "resolution"
},
{
"id": 3,
"type": "column",
"value": "rating"
},
{
"id": 0,
"type": "table",
"value": "song"
},
{
"id": 1,
"type": "column",
"value": "f_id"
},
{
"id": 4,
"type": "value",
"value": "8"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": [
20
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,456
|
advertising_agencies
|
bird:test.json:2136
|
Return the number of distinct staff who have attended a meeting?
|
SELECT count(DISTINCT staff_id) FROM Staff_in_meetings
|
[
"Return",
"the",
"number",
"of",
"distinct",
"staff",
"who",
"have",
"attended",
"a",
"meeting",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "staff_in_meetings"
},
{
"id": 1,
"type": "column",
"value": "staff_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9,
10
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O"
] |
2,457
|
address
|
bird:train.json:5133
|
How many states are in the central time zone? Write their full names.
|
SELECT SUM(CASE WHEN T1.time_zone = 'Central' THEN 1 ELSE 0 END) AS count FROM zip_data AS T1 INNER JOIN state AS T2 ON T2.abbreviation = T1.state WHERE T1.time_zone = 'Central'
|
[
"How",
"many",
"states",
"are",
"in",
"the",
"central",
"time",
"zone",
"?",
"Write",
"their",
"full",
"names",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "abbreviation"
},
{
"id": 2,
"type": "column",
"value": "time_zone"
},
{
"id": 0,
"type": "table",
"value": "zip_data"
},
{
"id": 3,
"type": "value",
"value": "Central"
},
{
"id": 1,
"type": "table",
"value": "state"
},
{
"id": 5,
"type": "column",
"value": "state"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
2,458
|
works_cycles
|
bird:train.json:7462
|
List the locations ids, compartments and containers for the Lock Ring
|
SELECT T2.LocationID, T2.Shelf, T2.Bin FROM Product AS T1 INNER JOIN ProductInventory AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Name LIKE 'Lock Ring'
|
[
"List",
"the",
"locations",
"ids",
",",
"compartments",
"and",
"containers",
"for",
"the",
"Lock",
"Ring"
] |
[
{
"id": 4,
"type": "table",
"value": "productinventory"
},
{
"id": 0,
"type": "column",
"value": "locationid"
},
{
"id": 6,
"type": "value",
"value": "Lock Ring"
},
{
"id": 7,
"type": "column",
"value": "productid"
},
{
"id": 3,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "column",
"value": "shelf"
},
{
"id": 5,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "bin"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
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},
{
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},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
10,
11
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE"
] |
2,459
|
cars
|
bird:train.json:3108
|
How many of the cars from Japan weighed less than 3000?
|
SELECT COUNT(*) FROM price AS T1 INNER JOIN production AS T2 ON T1.ID = T2.ID INNER JOIN country AS T3 ON T3.origin = T2.country INNER JOIN data AS T4 ON T4.ID = T1.ID WHERE T3.country = 'Japan' AND T4.weight < 3000
|
[
"How",
"many",
"of",
"the",
"cars",
"from",
"Japan",
"weighed",
"less",
"than",
"3000",
"?"
] |
[
{
"id": 8,
"type": "table",
"value": "production"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "country"
},
{
"id": 5,
"type": "column",
"value": "weight"
},
{
"id": 9,
"type": "column",
"value": "origin"
},
{
"id": 4,
"type": "value",
"value": "Japan"
},
{
"id": 7,
"type": "table",
"value": "price"
},
{
"id": 0,
"type": "table",
"value": "data"
},
{
"id": 6,
"type": "value",
"value": "3000"
},
{
"id": 2,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
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},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
6
]
},
{
"entity_id": 5,
"token_idxs": [
7
]
},
{
"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",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
2,460
|
protein_institute
|
spider:train_spider.json:1910
|
How many buildings are there?
|
SELECT count(*) FROM building
|
[
"How",
"many",
"buildings",
"are",
"there",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "building"
}
] |
[
{
"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"
] |
2,461
|
cs_semester
|
bird:train.json:863
|
Among the students who got a B in the course Machine Learning Theory, how many of them have a gpa of over 3?
|
SELECT COUNT(student_id) FROM registration WHERE grade = 'B' AND student_id IN ( SELECT student_id FROM student WHERE gpa > 3 AND course_id IN ( SELECT course_id FROM course WHERE name = 'Machine Learning Theory' ) )
|
[
"Among",
"the",
"students",
"who",
"got",
"a",
"B",
"in",
"the",
"course",
"Machine",
"Learning",
"Theory",
",",
"how",
"many",
"of",
"them",
"have",
"a",
"gpa",
"of",
"over",
"3",
"?"
] |
[
{
"id": 10,
"type": "value",
"value": "Machine Learning Theory"
},
{
"id": 0,
"type": "table",
"value": "registration"
},
{
"id": 1,
"type": "column",
"value": "student_id"
},
{
"id": 7,
"type": "column",
"value": "course_id"
},
{
"id": 4,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "table",
"value": "course"
},
{
"id": 2,
"type": "column",
"value": "grade"
},
{
"id": 9,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "gpa"
},
{
"id": 3,
"type": "value",
"value": "B"
},
{
"id": 6,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": [
2
]
},
{
"entity_id": 5,
"token_idxs": [
20
]
},
{
"entity_id": 6,
"token_idxs": [
23
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
9
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
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