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15,953
|
regional_sales
|
bird:train.json:2693
|
How many online purchases did Ole Group make in May 2019?
|
SELECT SUM(CASE WHEN T1.`Sales Channel` = 'Online' AND T2.`Customer Names` = 'Ole Group' AND T1.OrderDate LIKE '5/%/19' THEN 1 ELSE 0 END) FROM `Sales Orders` AS T1 INNER JOIN Customers AS T2 ON T2.CustomerID = T1._CustomerID
|
[
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"?"
] |
[
{
"id": 8,
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"value": "Customer Names"
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{
"id": 6,
"type": "column",
"value": "Sales Channel"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 3,
"type": "column",
"value": "_customerid"
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{
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"type": "column",
"value": "customerid"
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{
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"value": "customers"
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{
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"value": "Ole Group"
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{
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"type": "column",
"value": "orderdate"
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{
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"value": "Online"
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"type": "value",
"value": "5/%/19"
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"type": "value",
"value": "0"
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{
"id": 5,
"type": "value",
"value": "1"
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"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"O",
"O",
"O"
] |
15,954
|
twitter_1
|
spider:train_spider.json:290
|
Find the name of the user who has the largest number of followers.
|
SELECT name FROM user_profiles ORDER BY followers DESC LIMIT 1
|
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"."
] |
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{
"id": 1,
"type": "column",
"value": "name"
}
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[
"O",
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"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,955
|
manufactory_1
|
spider:train_spider.json:5350
|
Select the code of the product that is cheapest in each product category.
|
SELECT code , name , min(price) FROM products GROUP BY name
|
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"."
] |
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{
"id": 0,
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{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 2,
"type": "column",
"value": "code"
}
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"O",
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"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,956
|
card_games
|
bird:dev.json:361
|
How many cards of legalities whose status is restricted have text boxes?
|
SELECT COUNT(DISTINCT T1.id) FROM cards AS T1 INNER JOIN legalities AS T2 ON T1.uuid = T2.uuid WHERE T2.status = 'Restricted' AND T1.isTextless = 0
|
[
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"whose",
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"text",
"boxes",
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] |
[
{
"id": 1,
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"value": "legalities"
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{
"id": 5,
"type": "value",
"value": "Restricted"
},
{
"id": 6,
"type": "column",
"value": "istextless"
},
{
"id": 4,
"type": "column",
"value": "status"
},
{
"id": 0,
"type": "table",
"value": "cards"
},
{
"id": 3,
"type": "column",
"value": "uuid"
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{
"id": 2,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "0"
}
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}
] |
[
"O",
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"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,957
|
debit_card_specializing
|
bird:dev.json:1493
|
In February 2012, what percentage of customers consumed more than 528.3?
|
SELECT CAST(SUM(IIF(Consumption > 528.3, 1, 0)) AS FLOAT) * 100 / COUNT(CustomerID) FROM yearmonth WHERE Date = '201202'
|
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] |
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{
"id": 7,
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"value": "consumption"
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{
"id": 4,
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"value": "customerid"
},
{
"id": 0,
"type": "table",
"value": "yearmonth"
},
{
"id": 2,
"type": "value",
"value": "201202"
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{
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"value": "528.3"
},
{
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"value": "date"
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{
"id": 3,
"type": "value",
"value": "100"
},
{
"id": 5,
"type": "value",
"value": "1"
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{
"id": 6,
"type": "value",
"value": "0"
}
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"O",
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"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
15,958
|
student_club
|
bird:dev.json:1389
|
Which event has the lowest cost?
|
SELECT T1.event_name FROM event AS T1 INNER JOIN budget AS T2 ON T1.event_id = T2.link_to_event INNER JOIN expense AS T3 ON T2.budget_id = T3.link_to_budget ORDER BY T3.cost LIMIT 1
|
[
"Which",
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"has",
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"lowest",
"cost",
"?"
] |
[
{
"id": 6,
"type": "column",
"value": "link_to_budget"
},
{
"id": 8,
"type": "column",
"value": "link_to_event"
},
{
"id": 0,
"type": "column",
"value": "event_name"
},
{
"id": 5,
"type": "column",
"value": "budget_id"
},
{
"id": 7,
"type": "column",
"value": "event_id"
},
{
"id": 1,
"type": "table",
"value": "expense"
},
{
"id": 4,
"type": "table",
"value": "budget"
},
{
"id": 3,
"type": "table",
"value": "event"
},
{
"id": 2,
"type": "column",
"value": "cost"
}
] |
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[
"O",
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"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,959
|
bakery_1
|
bird:test.json:1579
|
Find all the items that have chocolate flavor but were not bought more than 10 times.
|
SELECT DISTINCT T1.item FROM items AS T1 JOIN goods AS T2 ON T1.item = T2.id WHERE T2.flavor = "Chocolate" GROUP BY item HAVING count(*) <= 10
|
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"."
] |
[
{
"id": 4,
"type": "column",
"value": "Chocolate"
},
{
"id": 3,
"type": "column",
"value": "flavor"
},
{
"id": 1,
"type": "table",
"value": "items"
},
{
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"value": "goods"
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{
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"type": "column",
"value": "item"
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{
"id": 5,
"type": "value",
"value": "10"
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{
"id": 6,
"type": "column",
"value": "id"
}
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"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,960
|
card_games
|
bird:dev.json:486
|
What is the percentage of the cards with a converted mana cost of 7 in the set Coldsnap?
|
SELECT CAST(SUM(CASE WHEN T1.convertedManaCost = 7 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id) FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T2.name = 'Coldsnap'
|
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"?"
] |
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{
"id": 10,
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{
"id": 3,
"type": "value",
"value": "Coldsnap"
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{
"id": 5,
"type": "column",
"value": "setcode"
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{
"id": 0,
"type": "table",
"value": "cards"
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{
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{
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"value": "name"
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{
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"value": "code"
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{
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"type": "value",
"value": "100"
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{
"id": 7,
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"value": "id"
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{
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{
"id": 9,
"type": "value",
"value": "1"
},
{
"id": 11,
"type": "value",
"value": "7"
}
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"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O"
] |
15,961
|
music_2
|
spider:train_spider.json:5236
|
What are the albums produced in year 2010?
|
SELECT * FROM Albums WHERE YEAR = 2010
|
[
"What",
"are",
"the",
"albums",
"produced",
"in",
"year",
"2010",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "albums"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 2,
"type": "value",
"value": "2010"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"B-VALUE",
"O"
] |
15,962
|
talkingdata
|
bird:train.json:1059
|
How many events were there on 30th April, 2016?
|
SELECT COUNT(event_id) FROM events WHERE SUBSTR(`timestamp`, 1, 10) = '2016-04-30'
|
[
"How",
"many",
"events",
"were",
"there",
"on",
"30th",
"April",
",",
"2016",
"?"
] |
[
{
"id": 1,
"type": "value",
"value": "2016-04-30"
},
{
"id": 3,
"type": "column",
"value": "timestamp"
},
{
"id": 2,
"type": "column",
"value": "event_id"
},
{
"id": 0,
"type": "table",
"value": "events"
},
{
"id": 5,
"type": "value",
"value": "10"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,963
|
institution_sports
|
bird:test.json:1664
|
What are the names of institutions that have 1 or more championships?
|
SELECT T2.Name FROM championship AS T1 JOIN institution AS T2 ON T1.Institution_ID = T2.Institution_ID WHERE T1.Number_of_Championships >= 1
|
[
"What",
"are",
"the",
"names",
"of",
"institutions",
"that",
"have",
"1",
"or",
"more",
"championships",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "number_of_championships"
},
{
"id": 5,
"type": "column",
"value": "institution_id"
},
{
"id": 1,
"type": "table",
"value": "championship"
},
{
"id": 2,
"type": "table",
"value": "institution"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"B-TABLE",
"O"
] |
15,964
|
restaurant
|
bird:train.json:1678
|
At what numbers on 9th Avenue of San Francisco there are restaurants?
|
SELECT id_restaurant FROM location WHERE City = 'san francisco' AND street_name = '9th avenue'
|
[
"At",
"what",
"numbers",
"on",
"9th",
"Avenue",
"of",
"San",
"Francisco",
"there",
"are",
"restaurants",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "id_restaurant"
},
{
"id": 3,
"type": "value",
"value": "san francisco"
},
{
"id": 4,
"type": "column",
"value": "street_name"
},
{
"id": 5,
"type": "value",
"value": "9th avenue"
},
{
"id": 0,
"type": "table",
"value": "location"
},
{
"id": 2,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7,
8
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
4,
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"O"
] |
15,965
|
retail_world
|
bird:train.json:6374
|
What is the most ordered products by customers?
|
SELECT T1.ProductID FROM Products AS T1 INNER JOIN `Order Details` AS T2 ON T1.ProductID = T2.ProductID GROUP BY T1.ProductID ORDER BY COUNT(*) DESC LIMIT 1
|
[
"What",
"is",
"the",
"most",
"ordered",
"products",
"by",
"customers",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "Order Details"
},
{
"id": 0,
"type": "column",
"value": "productid"
},
{
"id": 1,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"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-TABLE",
"B-TABLE",
"O",
"O",
"O"
] |
15,966
|
image_and_language
|
bird:train.json:7574
|
State the width and height of the object with the class of 'van' in image 1.
|
SELECT T1.H, T1.W FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 1 AND T2.OBJ_CLASS = 'van'
|
[
"State",
"the",
"width",
"and",
"height",
"of",
"the",
"object",
"with",
"the",
"class",
"of",
"'",
"van",
"'",
"in",
"image",
"1",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "obj_class_id"
},
{
"id": 3,
"type": "table",
"value": "obj_classes"
},
{
"id": 7,
"type": "column",
"value": "obj_class"
},
{
"id": 2,
"type": "table",
"value": "img_obj"
},
{
"id": 5,
"type": "column",
"value": "img_id"
},
{
"id": 8,
"type": "value",
"value": "van"
},
{
"id": 0,
"type": "column",
"value": "h"
},
{
"id": 1,
"type": "column",
"value": "w"
},
{
"id": 6,
"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": [
17
]
},
{
"entity_id": 7,
"token_idxs": [
10
]
},
{
"entity_id": 8,
"token_idxs": [
13
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,967
|
insurance_policies
|
spider:train_spider.json:3858
|
Among all the claims, what is the amount claimed in the claim with the least amount settled? List both the settlement amount and claim amount.
|
SELECT Amount_Settled , Amount_Claimed FROM Claims ORDER BY Amount_Settled ASC LIMIT 1
|
[
"Among",
"all",
"the",
"claims",
",",
"what",
"is",
"the",
"amount",
"claimed",
"in",
"the",
"claim",
"with",
"the",
"least",
"amount",
"settled",
"?",
"List",
"both",
"the",
"settlement",
"amount",
"and",
"claim",
"amount",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "amount_settled"
},
{
"id": 2,
"type": "column",
"value": "amount_claimed"
},
{
"id": 0,
"type": "table",
"value": "claims"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
16,
17
]
},
{
"entity_id": 2,
"token_idxs": [
8,
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,968
|
vehicle_driver
|
bird:test.json:179
|
What are the vehicle ids and models of the vehicle which have been driven by two drivers or been manufactured by 'Ziyang'.
|
SELECT T1.vehicle_id , T1.model FROM vehicle AS T1 JOIN vehicle_driver AS T2 ON T1.vehicle_id = T2.vehicle_id GROUP BY T2.vehicle_id HAVING count(*) = 2 OR T1.builder = 'Ziyang'
|
[
"What",
"are",
"the",
"vehicle",
"ids",
"and",
"models",
"of",
"the",
"vehicle",
"which",
"have",
"been",
"driven",
"by",
"two",
"drivers",
"or",
"been",
"manufactured",
"by",
"'",
"Ziyang",
"'",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "vehicle_driver"
},
{
"id": 0,
"type": "column",
"value": "vehicle_id"
},
{
"id": 2,
"type": "table",
"value": "vehicle"
},
{
"id": 5,
"type": "column",
"value": "builder"
},
{
"id": 6,
"type": "value",
"value": "Ziyang"
},
{
"id": 1,
"type": "column",
"value": "model"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
22
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,969
|
college_2
|
spider:train_spider.json:1421
|
What are the names of courses without prerequisites?
|
SELECT title FROM course WHERE course_id NOT IN (SELECT course_id FROM prereq)
|
[
"What",
"are",
"the",
"names",
"of",
"courses",
"without",
"prerequisites",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "course_id"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 3,
"type": "table",
"value": "prereq"
},
{
"id": 1,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"O"
] |
15,970
|
chicago_crime
|
bird:train.json:8755
|
What is the full name of the alderman of ward no.21?
|
SELECT alderman_first_name, alderman_last_name, alderman_name_suffix FROM Ward WHERE ward_no = 21
|
[
"What",
"is",
"the",
"full",
"name",
"of",
"the",
"alderman",
"of",
"ward",
"no.21",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "alderman_name_suffix"
},
{
"id": 1,
"type": "column",
"value": "alderman_first_name"
},
{
"id": 2,
"type": "column",
"value": "alderman_last_name"
},
{
"id": 4,
"type": "column",
"value": "ward_no"
},
{
"id": 0,
"type": "table",
"value": "ward"
},
{
"id": 5,
"type": "value",
"value": "21"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
8
]
},
{
"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",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"B-TABLE",
"O",
"O"
] |
15,971
|
art_1
|
bird:test.json:1212
|
Find the first and last names of all artists who were born after 1850.
|
SELECT lname , fname FROM artists WHERE birthYear > 1850
|
[
"Find",
"the",
"first",
"and",
"last",
"names",
"of",
"all",
"artists",
"who",
"were",
"born",
"after",
"1850",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "birthyear"
},
{
"id": 0,
"type": "table",
"value": "artists"
},
{
"id": 1,
"type": "column",
"value": "lname"
},
{
"id": 2,
"type": "column",
"value": "fname"
},
{
"id": 4,
"type": "value",
"value": "1850"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
15,972
|
city_record
|
spider:train_spider.json:6285
|
What is the city with the smallest GDP? Return the city and its GDP.
|
SELECT city , GDP FROM city ORDER BY GDP LIMIT 1
|
[
"What",
"is",
"the",
"city",
"with",
"the",
"smallest",
"GDP",
"?",
"Return",
"the",
"city",
"and",
"its",
"GDP",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "city"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "column",
"value": "gdp"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
11
]
},
{
"entity_id": 2,
"token_idxs": [
14
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O"
] |
15,973
|
soccer_2
|
spider:train_spider.json:4972
|
Find the players whose names contain letter 'a'.
|
SELECT DISTINCT pName FROM Player WHERE pName LIKE '%a%'
|
[
"Find",
"the",
"players",
"whose",
"names",
"contain",
"letter",
"'",
"a",
"'",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 1,
"type": "column",
"value": "pname"
},
{
"id": 2,
"type": "value",
"value": "%a%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,975
|
book_publishing_company
|
bird:train.json:206
|
In which country is the publisher of the book "Life Without Fear" located?
|
SELECT T2.country FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.title = 'Life Without Fear'
|
[
"In",
"which",
"country",
"is",
"the",
"publisher",
"of",
"the",
"book",
"\"",
"Life",
"Without",
"Fear",
"\"",
"located",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Life Without Fear"
},
{
"id": 2,
"type": "table",
"value": "publishers"
},
{
"id": 0,
"type": "column",
"value": "country"
},
{
"id": 1,
"type": "table",
"value": "titles"
},
{
"id": 5,
"type": "column",
"value": "pub_id"
},
{
"id": 3,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"O"
] |
15,976
|
riding_club
|
spider:train_spider.json:1723
|
Show the names of sponsors of players whose residence is either "Brandon" or "Birtle".
|
SELECT Sponsor_name FROM player WHERE Residence = "Brandon" OR Residence = "Birtle"
|
[
"Show",
"the",
"names",
"of",
"sponsors",
"of",
"players",
"whose",
"residence",
"is",
"either",
"\"",
"Brandon",
"\"",
"or",
"\"",
"Birtle",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "sponsor_name"
},
{
"id": 2,
"type": "column",
"value": "residence"
},
{
"id": 3,
"type": "column",
"value": "Brandon"
},
{
"id": 0,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "column",
"value": "Birtle"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
16
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
15,977
|
retails
|
bird:train.json:6910
|
Who is the clerk in charge of handling the item with the highest amount of extended price?
|
SELECT T1.o_clerk FROM orders AS T1 INNER JOIN lineitem AS T2 ON T1.o_orderkey = T2.l_orderkey ORDER BY T2.l_extendedprice DESC LIMIT 1
|
[
"Who",
"is",
"the",
"clerk",
"in",
"charge",
"of",
"handling",
"the",
"item",
"with",
"the",
"highest",
"amount",
"of",
"extended",
"price",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "l_extendedprice"
},
{
"id": 4,
"type": "column",
"value": "o_orderkey"
},
{
"id": 5,
"type": "column",
"value": "l_orderkey"
},
{
"id": 2,
"type": "table",
"value": "lineitem"
},
{
"id": 0,
"type": "column",
"value": "o_clerk"
},
{
"id": 1,
"type": "table",
"value": "orders"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
15,
16
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,978
|
movies_4
|
bird:train.json:502
|
Among the zero-budget movie titles, which one has made the highest revenue?
|
SELECT title FROM movie WHERE budget = 0 ORDER BY revenue DESC LIMIT 1
|
[
"Among",
"the",
"zero",
"-",
"budget",
"movie",
"titles",
",",
"which",
"one",
"has",
"made",
"the",
"highest",
"revenue",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "revenue"
},
{
"id": 2,
"type": "column",
"value": "budget"
},
{
"id": 0,
"type": "table",
"value": "movie"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,979
|
cre_Docs_and_Epenses
|
spider:train_spider.json:6450
|
Return the budget type codes, budget type descriptions and document ids for documents with expenses.
|
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
|
[
"Return",
"the",
"budget",
"type",
"codes",
",",
"budget",
"type",
"descriptions",
"and",
"document",
"ids",
"for",
"documents",
"with",
"expenses",
"."
] |
[
{
"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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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"I-TABLE",
"I-TABLE",
"O"
] |
15,980
|
news_report
|
spider:train_spider.json:2811
|
Show the dates, places, and names of events in descending order of the attendance.
|
SELECT Date , Name , venue FROM event ORDER BY Event_Attendance DESC
|
[
"Show",
"the",
"dates",
",",
"places",
",",
"and",
"names",
"of",
"events",
"in",
"descending",
"order",
"of",
"the",
"attendance",
"."
] |
[
{
"id": 4,
"type": "column",
"value": "event_attendance"
},
{
"id": 0,
"type": "table",
"value": "event"
},
{
"id": 3,
"type": "column",
"value": "venue"
},
{
"id": 1,
"type": "column",
"value": "date"
},
{
"id": 2,
"type": "column",
"value": "name"
}
] |
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"entity_id": 0,
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]
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7
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},
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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,
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,981
|
university
|
bird:train.json:8110
|
What is the ID of university with the largest percentage of international students?
|
SELECT university_id FROM university_year ORDER BY pct_international_students DESC LIMIT 1
|
[
"What",
"is",
"the",
"ID",
"of",
"university",
"with",
"the",
"largest",
"percentage",
"of",
"international",
"students",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "pct_international_students"
},
{
"id": 0,
"type": "table",
"value": "university_year"
},
{
"id": 1,
"type": "column",
"value": "university_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
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11,
12
]
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
"entity_id": 8,
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},
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"token_idxs": []
},
{
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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",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,982
|
hospital_1
|
spider:train_spider.json:3986
|
Find the name of physicians who are affiliated with both Surgery and Psychiatry departments.
|
SELECT T1.name FROM physician AS T1 JOIN affiliated_with AS T2 ON T1.EmployeeID = T2.physician JOIN department AS T3 ON T2.department = T3.DepartmentID WHERE T3.name = 'Surgery' INTERSECT SELECT T1.name FROM physician AS T1 JOIN affiliated_with AS T2 ON T1.EmployeeID = T2.physician JOIN department AS T3 ON T2.department = T3.DepartmentID WHERE T3.name = 'Psychiatry'
|
[
"Find",
"the",
"name",
"of",
"physicians",
"who",
"are",
"affiliated",
"with",
"both",
"Surgery",
"and",
"Psychiatry",
"departments",
"."
] |
[
{
"id": 5,
"type": "table",
"value": "affiliated_with"
},
{
"id": 7,
"type": "column",
"value": "departmentid"
},
{
"id": 1,
"type": "table",
"value": "department"
},
{
"id": 3,
"type": "value",
"value": "Psychiatry"
},
{
"id": 6,
"type": "column",
"value": "department"
},
{
"id": 8,
"type": "column",
"value": "employeeid"
},
{
"id": 4,
"type": "table",
"value": "physician"
},
{
"id": 9,
"type": "column",
"value": "physician"
},
{
"id": 2,
"type": "value",
"value": "Surgery"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
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2
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10
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{
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},
{
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7,
8
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},
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{
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},
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4
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"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
15,983
|
olympics
|
bird:train.json:5056
|
How many competitors over the age of 30 participated in the 1992 Winter Olympics?
|
SELECT COUNT(T2.person_id) FROM games AS T1 INNER JOIN games_competitor AS T2 ON T1.id = T2.games_id WHERE T1.games_name = '1992 Winter' AND T2.age > 30
|
[
"How",
"many",
"competitors",
"over",
"the",
"age",
"of",
"30",
"participated",
"in",
"the",
"1992",
"Winter",
"Olympics",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "games_competitor"
},
{
"id": 6,
"type": "value",
"value": "1992 Winter"
},
{
"id": 5,
"type": "column",
"value": "games_name"
},
{
"id": 2,
"type": "column",
"value": "person_id"
},
{
"id": 4,
"type": "column",
"value": "games_id"
},
{
"id": 0,
"type": "table",
"value": "games"
},
{
"id": 7,
"type": "column",
"value": "age"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 8,
"type": "value",
"value": "30"
}
] |
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{
"entity_id": 0,
"token_idxs": []
},
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2
]
},
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},
{
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{
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7
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{
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},
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"entity_id": 12,
"token_idxs": []
},
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"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O"
] |
15,984
|
toxicology
|
bird:dev.json:334
|
What is the element with the atom ID of TR004_7 in molecule that is not carcinogenic?
|
SELECT T1.element FROM atom AS T1 INNER JOIN molecule AS T2 ON T1.molecule_id = T2.molecule_id WHERE T1.atom_id = 'TR004_7' AND T2.label = '-'
|
[
"What",
"is",
"the",
"element",
"with",
"the",
"atom",
"ID",
"of",
"TR004_7",
"in",
"molecule",
"that",
"is",
"not",
"carcinogenic",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "molecule_id"
},
{
"id": 2,
"type": "table",
"value": "molecule"
},
{
"id": 0,
"type": "column",
"value": "element"
},
{
"id": 4,
"type": "column",
"value": "atom_id"
},
{
"id": 5,
"type": "value",
"value": "TR004_7"
},
{
"id": 6,
"type": "column",
"value": "label"
},
{
"id": 1,
"type": "table",
"value": "atom"
},
{
"id": 7,
"type": "value",
"value": "-"
}
] |
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3
]
},
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6
]
},
{
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11
]
},
{
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},
{
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7
]
},
{
"entity_id": 5,
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9
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},
{
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},
{
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{
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},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O"
] |
15,985
|
department_management
|
spider:train_spider.json:3
|
What are the maximum and minimum budget of the departments?
|
SELECT max(budget_in_billions) , min(budget_in_billions) FROM department
|
[
"What",
"are",
"the",
"maximum",
"and",
"minimum",
"budget",
"of",
"the",
"departments",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "budget_in_billions"
},
{
"id": 0,
"type": "table",
"value": "department"
}
] |
[
{
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9
]
},
{
"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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},
{
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},
{
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},
{
"entity_id": 11,
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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",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
15,986
|
pilot_1
|
bird:test.json:1153
|
What is the average age of pilots for different types of planes?
|
SELECT avg(age) , plane_name FROM pilotskills GROUP BY plane_name
|
[
"What",
"is",
"the",
"average",
"age",
"of",
"pilots",
"for",
"different",
"types",
"of",
"planes",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "pilotskills"
},
{
"id": 1,
"type": "column",
"value": "plane_name"
},
{
"id": 2,
"type": "column",
"value": "age"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
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11
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
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},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
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},
{
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},
{
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},
{
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"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",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,987
|
loan_1
|
spider:train_spider.json:3077
|
What are the names and cities of bank branches that offer loans for business?
|
SELECT T1.bname , T1.city FROM bank AS T1 JOIN loan AS T2 ON T1.branch_id = T2.branch_id WHERE T2.loan_type = 'Business'
|
[
"What",
"are",
"the",
"names",
"and",
"cities",
"of",
"bank",
"branches",
"that",
"offer",
"loans",
"for",
"business",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "loan_type"
},
{
"id": 6,
"type": "column",
"value": "branch_id"
},
{
"id": 5,
"type": "value",
"value": "Business"
},
{
"id": 0,
"type": "column",
"value": "bname"
},
{
"id": 1,
"type": "column",
"value": "city"
},
{
"id": 2,
"type": "table",
"value": "bank"
},
{
"id": 3,
"type": "table",
"value": "loan"
}
] |
[
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3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
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11
]
},
{
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"token_idxs": []
},
{
"entity_id": 5,
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13
]
},
{
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8
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},
{
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},
{
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},
{
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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",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
15,988
|
chinook_1
|
spider:train_spider.json:875
|
Please list the name and id of all artists that have at least 3 albums in alphabetical order.
|
SELECT T2.Name , T1.ArtistId FROM ALBUM AS T1 JOIN ARTIST AS T2 ON T1.ArtistId = T2.ArtistID GROUP BY T1.ArtistId HAVING COUNT(*) >= 3 ORDER BY T2.Name
|
[
"Please",
"list",
"the",
"name",
"and",
"i",
"d",
"of",
"all",
"artists",
"that",
"have",
"at",
"least",
"3",
"albums",
"in",
"alphabetical",
"order",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "artistid"
},
{
"id": 3,
"type": "table",
"value": "artist"
},
{
"id": 2,
"type": "table",
"value": "album"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "value",
"value": "3"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
15
]
},
{
"entity_id": 3,
"token_idxs": [
9
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
15,989
|
superstore
|
bird:train.json:2454
|
Among the orders from 2016 in the Central region, what is the product with the lowest profit?
|
SELECT T2.`Product Name` FROM central_superstore AS T1 INNER JOIN product AS T2 ON T1.`Product ID` = T2.`Product ID` WHERE T2.Region = 'Central' AND STRFTIME('%Y', T1.`Order Date`) = '2016' ORDER BY T1.Profit ASC LIMIT 1
|
[
"Among",
"the",
"orders",
"from",
"2016",
"in",
"the",
"Central",
"region",
",",
"what",
"is",
"the",
"product",
"with",
"the",
"lowest",
"profit",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "central_superstore"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 4,
"type": "column",
"value": "Product ID"
},
{
"id": 9,
"type": "column",
"value": "Order Date"
},
{
"id": 2,
"type": "table",
"value": "product"
},
{
"id": 6,
"type": "value",
"value": "Central"
},
{
"id": 3,
"type": "column",
"value": "profit"
},
{
"id": 5,
"type": "column",
"value": "region"
},
{
"id": 7,
"type": "value",
"value": "2016"
},
{
"id": 8,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
17
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8
]
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
4
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
2
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-VALUE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,990
|
bakery_1
|
bird:test.json:1526
|
What are the flavors of cakes that cost more than 10 dollars?
|
SELECT flavor FROM goods WHERE food = "Cake" AND price > 10
|
[
"What",
"are",
"the",
"flavors",
"of",
"cakes",
"that",
"cost",
"more",
"than",
"10",
"dollars",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "flavor"
},
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 4,
"type": "column",
"value": "price"
},
{
"id": 2,
"type": "column",
"value": "food"
},
{
"id": 3,
"type": "column",
"value": "Cake"
},
{
"id": 5,
"type": "value",
"value": "10"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
15,991
|
club_1
|
spider:train_spider.json:4303
|
Count the number of members in club "Bootup Baltimore" whose age is below 18.
|
SELECT count(*) 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 = "Bootup Baltimore" AND t3.age < 18
|
[
"Count",
"the",
"number",
"of",
"members",
"in",
"club",
"\"",
"Bootup",
"Baltimore",
"\"",
"whose",
"age",
"is",
"below",
"18",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "Bootup Baltimore"
},
{
"id": 2,
"type": "table",
"value": "member_of_club"
},
{
"id": 4,
"type": "column",
"value": "clubname"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 8,
"type": "column",
"value": "clubid"
},
{
"id": 3,
"type": "column",
"value": "stuid"
},
{
"id": 1,
"type": "table",
"value": "club"
},
{
"id": 6,
"type": "column",
"value": "age"
},
{
"id": 7,
"type": "value",
"value": "18"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
8,
9
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
15,992
|
cre_Doc_Control_Systems
|
spider:train_spider.json:2105
|
What is the description of role code ED?
|
SELECT role_description FROM ROLES WHERE role_code = "ED";
|
[
"What",
"is",
"the",
"description",
"of",
"role",
"code",
"ED",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "role_description"
},
{
"id": 2,
"type": "column",
"value": "role_code"
},
{
"id": 0,
"type": "table",
"value": "roles"
},
{
"id": 3,
"type": "column",
"value": "ED"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
6
]
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"B-COLUMN",
"B-COLUMN",
"O"
] |
15,993
|
mondial_geo
|
bird:train.json:8392
|
Which non capital city has the most people of all?
|
SELECT T3.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 <> T1.Capital ORDER BY T3.Population DESC LIMIT 1
|
[
"Which",
"non",
"capital",
"city",
"has",
"the",
"most",
"people",
"of",
"all",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "population"
},
{
"id": 5,
"type": "table",
"value": "province"
},
{
"id": 6,
"type": "column",
"value": "province"
},
{
"id": 2,
"type": "column",
"value": "capital"
},
{
"id": 4,
"type": "table",
"value": "country"
},
{
"id": 8,
"type": "column",
"value": "country"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 1,
"type": "table",
"value": "city"
},
{
"id": 7,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
15,994
|
bakery_1
|
bird:test.json:1521
|
What is the average price for each food type?
|
SELECT avg(price) , food FROM goods GROUP BY food
|
[
"What",
"is",
"the",
"average",
"price",
"for",
"each",
"food",
"type",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "goods"
},
{
"id": 2,
"type": "column",
"value": "price"
},
{
"id": 1,
"type": "column",
"value": "food"
}
] |
[
{
"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"
] |
15,995
|
food_inspection_2
|
bird:train.json:6184
|
List the types and results of the inspections done on Riverwalk café.
|
SELECT T2.inspection_type, T2.results FROM establishment AS T1 INNER JOIN inspection AS T2 ON T1.license_no = T2.license_no WHERE T1.facility_type = 'RIVERWALK CAFE'
|
[
"List",
"the",
"types",
"and",
"results",
"of",
"the",
"inspections",
"done",
"on",
"Riverwalk",
"café",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "inspection_type"
},
{
"id": 5,
"type": "value",
"value": "RIVERWALK CAFE"
},
{
"id": 2,
"type": "table",
"value": "establishment"
},
{
"id": 4,
"type": "column",
"value": "facility_type"
},
{
"id": 3,
"type": "table",
"value": "inspection"
},
{
"id": 6,
"type": "column",
"value": "license_no"
},
{
"id": 1,
"type": "column",
"value": "results"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
7
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
10,
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
15,996
|
authors
|
bird:train.json:3561
|
Write down homepage URL of journal for paper "364: Induction of Mixed Chimerism and Transplantation Tolerance in a Non-Human Primate Lung Allograft Model: Early Results".
|
SELECT T2.HomePage FROM Paper AS T1 INNER JOIN Journal AS T2 ON T1.JournalId = T2.Id WHERE T1.Title = '364: Induction of Mixed Chimerism and Transplantation Tolerance in a Non-Human Primate Lung Allograft Model: Early Results'
|
[
"Write",
"down",
"homepage",
"URL",
"of",
"journal",
"for",
"paper",
"\"",
"364",
":",
"Induction",
"of",
"Mixed",
"Chimerism",
"and",
"Transplantation",
"Tolerance",
"in",
"a",
"Non",
"-",
"Human",
"Primate",
"Lung",
"Allograft",
"Model",
":",
"Early",
"Results",
"\"",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "364: Induction of Mixed Chimerism and Transplantation Tolerance in a Non-Human Primate Lung Allograft Model: Early Results"
},
{
"id": 5,
"type": "column",
"value": "journalid"
},
{
"id": 0,
"type": "column",
"value": "homepage"
},
{
"id": 2,
"type": "table",
"value": "journal"
},
{
"id": 1,
"type": "table",
"value": "paper"
},
{
"id": 3,
"type": "column",
"value": "title"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29
]
},
{
"entity_id": 5,
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},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"B-TABLE",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
15,997
|
airline
|
bird:train.json:5892
|
List the air carrier description and code of the flight with the shortest arrival time.
|
SELECT T1.Description, T1.Code FROM `Air Carriers` AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.OP_CARRIER_AIRLINE_ID ORDER BY T2.ARR_TIME ASC LIMIT 1
|
[
"List",
"the",
"air",
"carrier",
"description",
"and",
"code",
"of",
"the",
"flight",
"with",
"the",
"shortest",
"arrival",
"time",
"."
] |
[
{
"id": 5,
"type": "column",
"value": "op_carrier_airline_id"
},
{
"id": 2,
"type": "table",
"value": "Air Carriers"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 3,
"type": "table",
"value": "airlines"
},
{
"id": 4,
"type": "column",
"value": "arr_time"
},
{
"id": 1,
"type": "column",
"value": "code"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
2,
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"I-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
15,998
|
epinions_1
|
spider:train_spider.json:1704
|
Find the name of the item with the lowest average rating.
|
SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rating) LIMIT 1
|
[
"Find",
"the",
"name",
"of",
"the",
"item",
"with",
"the",
"lowest",
"average",
"rating",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "review"
},
{
"id": 4,
"type": "column",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 0,
"type": "column",
"value": "i_id"
},
{
"id": 2,
"type": "table",
"value": "item"
}
] |
[
{
"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": [
10
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
15,999
|
loan_1
|
spider:train_spider.json:3024
|
Find the state, account type, and credit score of the customer whose number of loan is 0.
|
SELECT state , acc_type , credit_score FROM customer WHERE no_of_loans = 0
|
[
"Find",
"the",
"state",
",",
"account",
"type",
",",
"and",
"credit",
"score",
"of",
"the",
"customer",
"whose",
"number",
"of",
"loan",
"is",
"0",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "credit_score"
},
{
"id": 4,
"type": "column",
"value": "no_of_loans"
},
{
"id": 0,
"type": "table",
"value": "customer"
},
{
"id": 2,
"type": "column",
"value": "acc_type"
},
{
"id": 1,
"type": "column",
"value": "state"
},
{
"id": 5,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
12
]
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
15,
16
]
},
{
"entity_id": 5,
"token_idxs": [
18
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-VALUE",
"O"
] |
16,000
|
retail_complains
|
bird:train.json:391
|
In 2015, how many complaints about Billing disputes were sent by clients in Portland?
|
SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.city = 'Portland' AND T2.`Date received` LIKE '2015%' AND T2.Issue = 'Billing disputes'
|
[
"In",
"2015",
",",
"how",
"many",
"complaints",
"about",
"Billing",
"disputes",
"were",
"sent",
"by",
"clients",
"in",
"Portland",
"?"
] |
[
{
"id": 8,
"type": "value",
"value": "Billing disputes"
},
{
"id": 5,
"type": "column",
"value": "Date received"
},
{
"id": 2,
"type": "column",
"value": "client_id"
},
{
"id": 4,
"type": "value",
"value": "Portland"
},
{
"id": 0,
"type": "table",
"value": "client"
},
{
"id": 1,
"type": "table",
"value": "events"
},
{
"id": 6,
"type": "value",
"value": "2015%"
},
{
"id": 7,
"type": "column",
"value": "issue"
},
{
"id": 3,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
1
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"O"
] |
16,001
|
retails
|
bird:train.json:6736
|
Calculate the total profit made by chocolate floral blue coral cyan.
|
SELECT SUM(T3.l_extendedprice * (1 - T3.l_discount) - T2.ps_supplycost * T3.l_quantity) FROM part AS T1 INNER JOIN partsupp AS T2 ON T1.p_partkey = T2.ps_partkey INNER JOIN lineitem AS T3 ON T2.ps_partkey = T3.l_partkey AND T2.ps_suppkey = T3.l_suppkey WHERE T1.p_name = 'chocolate floral blue coral cyan'
|
[
"Calculate",
"the",
"total",
"profit",
"made",
"by",
"chocolate",
"floral",
"blue",
"coral",
"cyan",
"."
] |
[
{
"id": 2,
"type": "value",
"value": "chocolate floral blue coral cyan"
},
{
"id": 10,
"type": "column",
"value": "l_extendedprice"
},
{
"id": 11,
"type": "column",
"value": "ps_supplycost"
},
{
"id": 6,
"type": "column",
"value": "ps_partkey"
},
{
"id": 8,
"type": "column",
"value": "ps_suppkey"
},
{
"id": 12,
"type": "column",
"value": "l_quantity"
},
{
"id": 14,
"type": "column",
"value": "l_discount"
},
{
"id": 5,
"type": "column",
"value": "p_partkey"
},
{
"id": 7,
"type": "column",
"value": "l_partkey"
},
{
"id": 9,
"type": "column",
"value": "l_suppkey"
},
{
"id": 0,
"type": "table",
"value": "lineitem"
},
{
"id": 4,
"type": "table",
"value": "partsupp"
},
{
"id": 1,
"type": "column",
"value": "p_name"
},
{
"id": 3,
"type": "table",
"value": "part"
},
{
"id": 13,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
6,
7,
8,
9,
10
]
},
{
"entity_id": 3,
"token_idxs": [
3
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
16,002
|
beer_factory
|
bird:train.json:5258
|
Which customer has the most reviews? State the full name.
|
SELECT T1.First, T1.Last FROM customers AS T1 INNER JOIN rootbeerreview AS T2 ON T1.CustomerID = T2.CustomerID GROUP BY T1.CustomerID ORDER BY COUNT(T2.CustomerID) DESC LIMIT 1
|
[
"Which",
"customer",
"has",
"the",
"most",
"reviews",
"?",
"State",
"the",
"full",
"name",
"."
] |
[
{
"id": 4,
"type": "table",
"value": "rootbeerreview"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 3,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "first"
},
{
"id": 2,
"type": "column",
"value": "last"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"entity_id": 4,
"token_idxs": [
4,
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,003
|
network_2
|
spider:train_spider.json:4460
|
Find the male friend of Alice whose job is a doctor?
|
SELECT T2.friend FROM Person AS T1 JOIN PersonFriend AS T2 ON T1.name = T2.friend WHERE T2.name = 'Alice' AND T1.gender = 'male' AND T1.job = 'doctor'
|
[
"Find",
"the",
"male",
"friend",
"of",
"Alice",
"whose",
"job",
"is",
"a",
"doctor",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "personfriend"
},
{
"id": 0,
"type": "column",
"value": "friend"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 5,
"type": "column",
"value": "gender"
},
{
"id": 8,
"type": "value",
"value": "doctor"
},
{
"id": 4,
"type": "value",
"value": "Alice"
},
{
"id": 3,
"type": "column",
"value": "name"
},
{
"id": 6,
"type": "value",
"value": "male"
},
{
"id": 7,
"type": "column",
"value": "job"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
2
]
},
{
"entity_id": 7,
"token_idxs": [
7
]
},
{
"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",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
16,004
|
regional_sales
|
bird:train.json:2695
|
What is the least purchased product by stores in the city of Santa Clarita?
|
SELECT T1.`Product Name` FROM Products AS T1 INNER JOIN `Sales Orders` AS T2 ON T2._ProductID = T1.ProductID INNER JOIN `Store Locations` AS T3 ON T3.StoreID = T2._StoreID WHERE T3.`City Name` = 'Santa Clarita' GROUP BY T1.`Product Name` ORDER BY COUNT(T1.`Product Name`) ASC LIMIT 1
|
[
"What",
"is",
"the",
"least",
"purchased",
"product",
"by",
"stores",
"in",
"the",
"city",
"of",
"Santa",
"Clarita",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "Store Locations"
},
{
"id": 3,
"type": "value",
"value": "Santa Clarita"
},
{
"id": 0,
"type": "column",
"value": "Product Name"
},
{
"id": 5,
"type": "table",
"value": "Sales Orders"
},
{
"id": 8,
"type": "column",
"value": "_productid"
},
{
"id": 2,
"type": "column",
"value": "City Name"
},
{
"id": 9,
"type": "column",
"value": "productid"
},
{
"id": 4,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "column",
"value": "_storeid"
},
{
"id": 6,
"type": "column",
"value": "storeid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
5
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
7
]
},
{
"entity_id": 7,
"token_idxs": [
8
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-VALUE",
"O"
] |
16,005
|
soccer_2016
|
bird:train.json:2027
|
How many times did SC Ganguly be the man of the match?
|
SELECT COUNT(T2.Man_of_the_Match) FROM Player AS T1 INNER JOIN Match AS T2 ON T1.Player_Id = T2.Man_of_the_Match INNER JOIN Player_Match AS T3 ON T3.Player_Id = T1.Player_Id WHERE T1.Player_Name = 'SC Ganguly'
|
[
"How",
"many",
"times",
"did",
"SC",
"Ganguly",
"be",
"the",
"man",
"of",
"the",
"match",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "man_of_the_match"
},
{
"id": 0,
"type": "table",
"value": "player_match"
},
{
"id": 1,
"type": "column",
"value": "player_name"
},
{
"id": 2,
"type": "value",
"value": "SC Ganguly"
},
{
"id": 6,
"type": "column",
"value": "player_id"
},
{
"id": 4,
"type": "table",
"value": "player"
},
{
"id": 5,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4,
5
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9,
10
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"B-TABLE",
"O"
] |
16,006
|
app_store
|
bird:train.json:2568
|
Indicate the number of installs and include the percentage of positive sentiments of FREEDOME VPN Unlimited anonymous Wifi Security.
|
SELECT T1.Installs , CAST(SUM(CASE WHEN T2.Sentiment = 'Positive' THEN 1 ELSE 0 END) * 100 / SUM(CASE WHEN T2.Sentiment IS NOT NULL THEN 1.0 ELSE 0 END) AS REAL) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T1.App = 'FREEDOME VPN Unlimited anonymous Wifi Security'
|
[
"Indicate",
"the",
"number",
"of",
"installs",
"and",
"include",
"the",
"percentage",
"of",
"positive",
"sentiments",
"of",
"FREEDOME",
"VPN",
"Unlimited",
"anonymous",
"Wifi",
"Security",
"."
] |
[
{
"id": 4,
"type": "value",
"value": "FREEDOME VPN Unlimited anonymous Wifi Security"
},
{
"id": 2,
"type": "table",
"value": "user_reviews"
},
{
"id": 1,
"type": "table",
"value": "playstore"
},
{
"id": 9,
"type": "column",
"value": "sentiment"
},
{
"id": 0,
"type": "column",
"value": "installs"
},
{
"id": 10,
"type": "value",
"value": "Positive"
},
{
"id": 3,
"type": "column",
"value": "app"
},
{
"id": 5,
"type": "value",
"value": "100"
},
{
"id": 7,
"type": "value",
"value": "1.0"
},
{
"id": 6,
"type": "value",
"value": "0"
},
{
"id": 8,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
13,
14,
15,
16,
17,
18
]
},
{
"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": [
11
]
},
{
"entity_id": 10,
"token_idxs": [
10
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O"
] |
16,007
|
university
|
bird:train.json:8006
|
What are the names of the top 5 universities with the highest number of international students?
|
SELECT DISTINCT T2.university_name FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id ORDER BY (CAST(T1.num_students * T1.pct_international_students AS REAL) / 100) DESC LIMIT 5
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"top",
"5",
"universities",
"with",
"the",
"highest",
"number",
"of",
"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": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
15
]
},
{
"entity_id": 7,
"token_idxs": [
14
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
16,008
|
music_2
|
spider:train_spider.json:5254
|
Which vocal type has the band mate with first name "Solveig" played the most?
|
SELECT TYPE FROM vocals AS T1 JOIN band AS T2 ON T1.bandmate = T2.id WHERE firstname = "Solveig" GROUP BY TYPE ORDER BY count(*) DESC LIMIT 1
|
[
"Which",
"vocal",
"type",
"has",
"the",
"band",
"mate",
"with",
"first",
"name",
"\"",
"Solveig",
"\"",
"played",
"the",
"most",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "bandmate"
},
{
"id": 4,
"type": "column",
"value": "Solveig"
},
{
"id": 1,
"type": "table",
"value": "vocals"
},
{
"id": 0,
"type": "column",
"value": "type"
},
{
"id": 2,
"type": "table",
"value": "band"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": [
8,
9
]
},
{
"entity_id": 4,
"token_idxs": [
11
]
},
{
"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",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O"
] |
16,009
|
voter_2
|
spider:train_spider.json:5486
|
How many male (sex is M) students have class senator votes in the fall election cycle?
|
SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.Sex = "M" AND T2.Election_Cycle = "Fall"
|
[
"How",
"many",
"male",
"(",
"sex",
"is",
"M",
")",
"students",
"have",
"class",
"senator",
"votes",
"in",
"the",
"fall",
"election",
"cycle",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "class_senator_vote"
},
{
"id": 6,
"type": "column",
"value": "election_cycle"
},
{
"id": 1,
"type": "table",
"value": "voting_record"
},
{
"id": 0,
"type": "table",
"value": "student"
},
{
"id": 2,
"type": "column",
"value": "stuid"
},
{
"id": 7,
"type": "column",
"value": "Fall"
},
{
"id": 4,
"type": "column",
"value": "sex"
},
{
"id": 5,
"type": "column",
"value": "M"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
10,
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": [
6
]
},
{
"entity_id": 6,
"token_idxs": [
16,
17
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"B-COLUMN",
"I-COLUMN",
"O"
] |
16,010
|
cre_Students_Information_Systems
|
bird:test.json:484
|
Which teacher teaches the most courses? Give me the id of the teacher and the number of courses he or she teaches.
|
SELECT count(*) , teacher_id FROM Classes GROUP BY teacher_id ORDER BY count(*) DESC LIMIT 1
|
[
"Which",
"teacher",
"teaches",
"the",
"most",
"courses",
"?",
"Give",
"me",
"the",
"i",
"d",
"of",
"the",
"teacher",
"and",
"the",
"number",
"of",
"courses",
"he",
"or",
"she",
"teaches",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "teacher_id"
},
{
"id": 0,
"type": "table",
"value": "classes"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
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14
]
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{
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{
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},
{
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},
{
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},
{
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"token_idxs": []
},
{
"entity_id": 10,
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},
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"entity_id": 11,
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},
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},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,012
|
works_cycles
|
bird:train.json:7208
|
What is the name of the product with the id "475"?
|
SELECT Name FROM Product WHERE ProductID = 475
|
[
"What",
"is",
"the",
"name",
"of",
"the",
"product",
"with",
"the",
"i",
"d",
"\"",
"475",
"\"",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "productid"
},
{
"id": 0,
"type": "table",
"value": "product"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "475"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O"
] |
16,013
|
software_company
|
bird:train.json:8571
|
List the marital status and response of female customers with an level of education of 8 and above.
|
SELECT DISTINCT T1.MARITAL_STATUS, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.EDUCATIONNUM > 8 AND T1.SEX = 'Female'
|
[
"List",
"the",
"marital",
"status",
"and",
"response",
"of",
"female",
"customers",
"with",
"an",
"level",
"of",
"education",
"of",
"8",
"and",
"above",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "marital_status"
},
{
"id": 6,
"type": "column",
"value": "educationnum"
},
{
"id": 3,
"type": "table",
"value": "mailings1_2"
},
{
"id": 2,
"type": "table",
"value": "customers"
},
{
"id": 1,
"type": "column",
"value": "response"
},
{
"id": 9,
"type": "value",
"value": "Female"
},
{
"id": 5,
"type": "column",
"value": "refid"
},
{
"id": 8,
"type": "column",
"value": "sex"
},
{
"id": 4,
"type": "column",
"value": "id"
},
{
"id": 7,
"type": "value",
"value": "8"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
15
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
7
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
16,015
|
apartment_rentals
|
spider:train_spider.json:1223
|
Return the booking start date and end date for the apartments that have type code "Duplex".
|
SELECT T1.booking_start_date , T1.booking_start_date FROM Apartment_Bookings AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id WHERE T2.apt_type_code = "Duplex"
|
[
"Return",
"the",
"booking",
"start",
"date",
"and",
"end",
"date",
"for",
"the",
"apartments",
"that",
"have",
"type",
"code",
"\"",
"Duplex",
"\"",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "booking_start_date"
},
{
"id": 1,
"type": "table",
"value": "apartment_bookings"
},
{
"id": 3,
"type": "column",
"value": "apt_type_code"
},
{
"id": 2,
"type": "table",
"value": "apartments"
},
{
"id": 4,
"type": "column",
"value": "Duplex"
},
{
"id": 5,
"type": "column",
"value": "apt_id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
13,
14
]
},
{
"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",
"I-COLUMN",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O"
] |
16,016
|
movie_3
|
bird:train.json:9268
|
How many different clients have rented materials from Jon Stephens?
|
SELECT COUNT(T1.customer_id) FROM rental AS T1 INNER JOIN staff AS T2 ON T1.staff_id = T2.staff_id WHERE T2.first_name = 'Jon' AND T2.last_name = 'Stephens'
|
[
"How",
"many",
"different",
"clients",
"have",
"rented",
"materials",
"from",
"Jon",
"Stephens",
"?"
] |
[
{
"id": 2,
"type": "column",
"value": "customer_id"
},
{
"id": 4,
"type": "column",
"value": "first_name"
},
{
"id": 6,
"type": "column",
"value": "last_name"
},
{
"id": 3,
"type": "column",
"value": "staff_id"
},
{
"id": 7,
"type": "value",
"value": "Stephens"
},
{
"id": 0,
"type": "table",
"value": "rental"
},
{
"id": 1,
"type": "table",
"value": "staff"
},
{
"id": 5,
"type": "value",
"value": "Jon"
}
] |
[
{
"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": [
8
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
9
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-VALUE",
"O"
] |
16,017
|
city_record
|
spider:train_spider.json:6300
|
Find the number of matches in different competitions.
|
SELECT count(*) , Competition FROM MATCH GROUP BY Competition
|
[
"Find",
"the",
"number",
"of",
"matches",
"in",
"different",
"competitions",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "competition"
},
{
"id": 0,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
16,018
|
software_company
|
bird:train.json:8529
|
What is the average age of first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department?
|
SELECT AVG(T1.age) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T2.RESPONSE = 'true'
|
[
"What",
"is",
"the",
"average",
"age",
"of",
"first",
"60,000",
"customers",
"who",
"sent",
"a",
"true",
"response",
"to",
"the",
"incentive",
"mailing",
"sent",
"by",
"the",
"marketing",
"department",
"?"
] |
[
{
"id": 1,
"type": "table",
"value": "mailings1_2"
},
{
"id": 0,
"type": "table",
"value": "customers"
},
{
"id": 2,
"type": "column",
"value": "response"
},
{
"id": 6,
"type": "column",
"value": "refid"
},
{
"id": 3,
"type": "value",
"value": "true"
},
{
"id": 4,
"type": "column",
"value": "age"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
8
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": [
4
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,019
|
computer_student
|
bird:train.json:1016
|
How many professional or master/graduate courses are there?
|
SELECT COUNT(*) FROM course WHERE courseLevel = 'Level_500'
|
[
"How",
"many",
"professional",
"or",
"master",
"/",
"graduate",
"courses",
"are",
"there",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "courselevel"
},
{
"id": 2,
"type": "value",
"value": "Level_500"
},
{
"id": 0,
"type": "table",
"value": "course"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
7
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
16,020
|
hockey
|
bird:train.json:7629
|
Name the deceased players whose death country is different from his birth country order by birth year.
|
SELECT firstName, lastName FROM Master WHERE birthCountry != deathCountry ORDER BY birthYear
|
[
"Name",
"the",
"deceased",
"players",
"whose",
"death",
"country",
"is",
"different",
"from",
"his",
"birth",
"country",
"order",
"by",
"birth",
"year",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "birthcountry"
},
{
"id": 4,
"type": "column",
"value": "deathcountry"
},
{
"id": 1,
"type": "column",
"value": "firstname"
},
{
"id": 5,
"type": "column",
"value": "birthyear"
},
{
"id": 2,
"type": "column",
"value": "lastname"
},
{
"id": 0,
"type": "table",
"value": "master"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
0
]
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": [
5,
6
]
},
{
"entity_id": 5,
"token_idxs": [
15,
16
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
16,021
|
store_1
|
spider:train_spider.json:572
|
How many albums has Billy Cobam released?
|
SELECT count(*) FROM albums AS T1 JOIN artists AS T2 ON T1.artist_id = T2.id WHERE T2.name = "Billy Cobham";
|
[
"How",
"many",
"albums",
"has",
"Billy",
"Cobam",
"released",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "Billy Cobham"
},
{
"id": 4,
"type": "column",
"value": "artist_id"
},
{
"id": 1,
"type": "table",
"value": "artists"
},
{
"id": 0,
"type": "table",
"value": "albums"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 5,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"O"
] |
16,023
|
simpson_episodes
|
bird:train.json:4297
|
What award did the episode that aired on 11/30/2008 win?
|
SELECT T1.award FROM Award AS T1 INNER JOIN Episode AS T2 ON T1.episode_id = T2.episode_id WHERE T1.result = 'Winner' AND T2.air_date = '2008-11-30';
|
[
"What",
"award",
"did",
"the",
"episode",
"that",
"aired",
"on",
"11/30/2008",
"win",
"?"
] |
[
{
"id": 3,
"type": "column",
"value": "episode_id"
},
{
"id": 7,
"type": "value",
"value": "2008-11-30"
},
{
"id": 6,
"type": "column",
"value": "air_date"
},
{
"id": 2,
"type": "table",
"value": "episode"
},
{
"id": 4,
"type": "column",
"value": "result"
},
{
"id": 5,
"type": "value",
"value": "Winner"
},
{
"id": 0,
"type": "column",
"value": "award"
},
{
"id": 1,
"type": "table",
"value": "award"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
1
]
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": [
6
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
16,024
|
movie_platform
|
bird:train.json:161
|
What is the average number of followers of the lists created by the user who rated the movie "Pavee Lackeen: The Traveller Girl" on 3/27/2011 at 2:06:34 AM?
|
SELECT CAST(SUM(T4.list_followers) AS REAL) / COUNT(T2.list_id) FROM ratings AS T1 INNER JOIN lists_users AS T2 ON T1.user_id = T2.user_id INNER JOIN movies AS T3 ON T1.movie_id = T3.movie_id INNER JOIN lists AS T4 ON T2.list_id = T4.list_id WHERE T3.movie_title LIKE 'Pavee Lackeen: The Traveller Girl' AND T1.rating_timestamp_utc LIKE '2011-03-27 02:06:34'
|
[
"What",
"is",
"the",
"average",
"number",
"of",
"followers",
"of",
"the",
"lists",
"created",
"by",
"the",
"user",
"who",
"rated",
"the",
"movie",
"\"",
"Pavee",
"Lackeen",
":",
"The",
"Traveller",
"Girl",
"\"",
"on",
"3/27/2011",
"at",
"2:06:34",
"AM",
"?"
] |
[
{
"id": 4,
"type": "value",
"value": "Pavee Lackeen: The Traveller Girl"
},
{
"id": 5,
"type": "column",
"value": "rating_timestamp_utc"
},
{
"id": 6,
"type": "value",
"value": "2011-03-27 02:06:34"
},
{
"id": 10,
"type": "column",
"value": "list_followers"
},
{
"id": 3,
"type": "column",
"value": "movie_title"
},
{
"id": 8,
"type": "table",
"value": "lists_users"
},
{
"id": 9,
"type": "column",
"value": "movie_id"
},
{
"id": 2,
"type": "column",
"value": "list_id"
},
{
"id": 7,
"type": "table",
"value": "ratings"
},
{
"id": 11,
"type": "column",
"value": "user_id"
},
{
"id": 1,
"type": "table",
"value": "movies"
},
{
"id": 0,
"type": "table",
"value": "lists"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": [
17
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
19,
20,
21,
22,
23,
24
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
27,
28,
29
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
6
]
},
{
"entity_id": 11,
"token_idxs": [
13
]
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"O"
] |
16,025
|
shipping
|
bird:train.json:5675
|
How many shipments were delivered to a customer from New York?
|
SELECT COUNT(*) FROM shipment AS T1 INNER JOIN customer AS T2 ON T1.cust_id = T2.cust_id WHERE T2.state = 'NY'
|
[
"How",
"many",
"shipments",
"were",
"delivered",
"to",
"a",
"customer",
"from",
"New",
"York",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "shipment"
},
{
"id": 1,
"type": "table",
"value": "customer"
},
{
"id": 4,
"type": "column",
"value": "cust_id"
},
{
"id": 2,
"type": "column",
"value": "state"
},
{
"id": 3,
"type": "value",
"value": "NY"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
7
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
1
]
},
{
"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-VALUE",
"B-TABLE",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
16,028
|
toxicology
|
bird:dev.json:264
|
What are the labels for TR000, TR001 and TR002?
|
SELECT molecule_id, T.label FROM molecule AS T WHERE T.molecule_id IN ('TR000', 'TR001', 'TR002')
|
[
"What",
"are",
"the",
"labels",
"for",
"TR000",
",",
"TR001",
"and",
"TR002",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "molecule_id"
},
{
"id": 0,
"type": "table",
"value": "molecule"
},
{
"id": 2,
"type": "column",
"value": "label"
},
{
"id": 3,
"type": "value",
"value": "TR000"
},
{
"id": 4,
"type": "value",
"value": "TR001"
},
{
"id": 5,
"type": "value",
"value": "TR002"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": [
5
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": [
9
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O",
"B-VALUE",
"O"
] |
16,029
|
university
|
bird:train.json:7989
|
How many state universities are there?
|
SELECT COUNT(*) FROM university WHERE university_name LIKE '%State%'
|
[
"How",
"many",
"state",
"universities",
"are",
"there",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "university_name"
},
{
"id": 0,
"type": "table",
"value": "university"
},
{
"id": 2,
"type": "value",
"value": "%State%"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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"
] |
16,030
|
movie_1
|
spider:train_spider.json:2455
|
What are the names of the directors who created a movie with a 5 star rating, and what was the name of those movies?
|
SELECT T1.director , T1.title FROM Movie AS T1 JOIN Rating AS T2 ON T1.mID = T2.mID WHERE T2.stars = 5
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"directors",
"who",
"created",
"a",
"movie",
"with",
"a",
"5",
"star",
"rating",
",",
"and",
"what",
"was",
"the",
"name",
"of",
"those",
"movies",
"?"
] |
[
{
"id": 0,
"type": "column",
"value": "director"
},
{
"id": 3,
"type": "table",
"value": "rating"
},
{
"id": 1,
"type": "column",
"value": "title"
},
{
"id": 2,
"type": "table",
"value": "movie"
},
{
"id": 4,
"type": "column",
"value": "stars"
},
{
"id": 6,
"type": "column",
"value": "mid"
},
{
"id": 5,
"type": "value",
"value": "5"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
10
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": [
14
]
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,031
|
student_club
|
bird:dev.json:1377
|
How many student have the position of president?
|
SELECT COUNT(member_id) FROM member WHERE position = 'President'
|
[
"How",
"many",
"student",
"have",
"the",
"position",
"of",
"president",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "President"
},
{
"id": 3,
"type": "column",
"value": "member_id"
},
{
"id": 1,
"type": "column",
"value": "position"
},
{
"id": 0,
"type": "table",
"value": "member"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
5
]
},
{
"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",
"O",
"B-COLUMN",
"O",
"B-VALUE",
"O"
] |
16,032
|
customers_card_transactions
|
spider:train_spider.json:691
|
How many customers do we have?
|
SELECT count(*) FROM Customers
|
[
"How",
"many",
"customers",
"do",
"we",
"have",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "customers"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O"
] |
16,033
|
computer_student
|
bird:train.json:1021
|
Among the faculty affiliated professor, how many professors teaches professional or master/undergraduate courses?
|
SELECT COUNT(*) FROM person AS T1 INNER JOIN taughtBy AS T2 ON T1.p_id = T2.p_id INNER JOIN course AS T3 ON T3.course_id = T2.course_id WHERE T1.hasPosition = 'Faculty_aff' AND T1.professor = 1 AND T3.courseLevel = 'Level_500'
|
[
"Among",
"the",
"faculty",
"affiliated",
"professor",
",",
"how",
"many",
"professors",
"teaches",
"professional",
"or",
"master",
"/",
"undergraduate",
"courses",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "hasposition"
},
{
"id": 5,
"type": "value",
"value": "Faculty_aff"
},
{
"id": 8,
"type": "column",
"value": "courselevel"
},
{
"id": 3,
"type": "column",
"value": "course_id"
},
{
"id": 6,
"type": "column",
"value": "professor"
},
{
"id": 9,
"type": "value",
"value": "Level_500"
},
{
"id": 2,
"type": "table",
"value": "taughtby"
},
{
"id": 0,
"type": "table",
"value": "course"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 10,
"type": "column",
"value": "p_id"
},
{
"id": 7,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
15
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
2
]
},
{
"entity_id": 6,
"token_idxs": [
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-VALUE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
16,034
|
bakery_1
|
bird:test.json:1495
|
List the distinct ids of all customers who bought a cake with lemon flavor?
|
SELECT DISTINCT T3.CustomerId FROM goods AS T1 JOIN items AS T2 ON T1.Id = T2.Item JOIN receipts AS T3 ON T2.Receipt = T3.ReceiptNumber WHERE T1.Flavor = "Lemon" AND T1.Food = "Cake"
|
[
"List",
"the",
"distinct",
"ids",
"of",
"all",
"customers",
"who",
"bought",
"a",
"cake",
"with",
"lemon",
"flavor",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "receiptnumber"
},
{
"id": 0,
"type": "column",
"value": "customerid"
},
{
"id": 1,
"type": "table",
"value": "receipts"
},
{
"id": 4,
"type": "column",
"value": "receipt"
},
{
"id": 6,
"type": "column",
"value": "flavor"
},
{
"id": 2,
"type": "table",
"value": "goods"
},
{
"id": 3,
"type": "table",
"value": "items"
},
{
"id": 7,
"type": "column",
"value": "Lemon"
},
{
"id": 8,
"type": "column",
"value": "food"
},
{
"id": 9,
"type": "column",
"value": "Cake"
},
{
"id": 11,
"type": "column",
"value": "item"
},
{
"id": 10,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
6
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
13
]
},
{
"entity_id": 7,
"token_idxs": [
12
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
10
]
},
{
"entity_id": 10,
"token_idxs": [
3
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"B-COLUMN",
"O"
] |
16,035
|
public_review_platform
|
bird:train.json:3943
|
List the category of the business with high review count but received 2 stars.
|
SELECT T3.category_name FROM Business AS T1 INNER JOIN Business_Categories ON T1.business_id = Business_Categories.business_id INNER JOIN Categories AS T3 ON Business_Categories.category_id = T3.category_id WHERE T1.stars = 2 AND T1.review_count LIKE 'High'
|
[
"List",
"the",
"category",
"of",
"the",
"business",
"with",
"high",
"review",
"count",
"but",
"received",
"2",
"stars",
"."
] |
[
{
"id": 3,
"type": "table",
"value": "business_categories"
},
{
"id": 0,
"type": "column",
"value": "category_name"
},
{
"id": 7,
"type": "column",
"value": "review_count"
},
{
"id": 4,
"type": "column",
"value": "category_id"
},
{
"id": 9,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "categories"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "column",
"value": "stars"
},
{
"id": 8,
"type": "value",
"value": "High"
},
{
"id": 6,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": [
5
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
13
]
},
{
"entity_id": 6,
"token_idxs": [
12
]
},
{
"entity_id": 7,
"token_idxs": [
8,
9
]
},
{
"entity_id": 8,
"token_idxs": [
7
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-VALUE",
"B-COLUMN",
"I-COLUMN",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
16,036
|
car_retails
|
bird:train.json:1585
|
List the product code of the top five motorcycles, by descending order, the number of quantity in stock.
|
SELECT productCode, quantityInStock FROM products WHERE productLine = 'Motorcycles' ORDER BY quantityInStock DESC LIMIT 5
|
[
"List",
"the",
"product",
"code",
"of",
"the",
"top",
"five",
"motorcycles",
",",
"by",
"descending",
"order",
",",
"the",
"number",
"of",
"quantity",
"in",
"stock",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "quantityinstock"
},
{
"id": 1,
"type": "column",
"value": "productcode"
},
{
"id": 3,
"type": "column",
"value": "productline"
},
{
"id": 4,
"type": "value",
"value": "Motorcycles"
},
{
"id": 0,
"type": "table",
"value": "products"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
17,
18,
19
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
8
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"I-COLUMN",
"O"
] |
16,037
|
donor
|
bird:train.json:3152
|
Name the project titles meant for school whereby 65% of the students are on reduced lunch.
|
SELECT T1.title FROM essays AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T2.poverty_level LIKE 'highest%'
|
[
"Name",
"the",
"project",
"titles",
"meant",
"for",
"school",
"whereby",
"65",
"%",
"of",
"the",
"students",
"are",
"on",
"reduced",
"lunch",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "poverty_level"
},
{
"id": 5,
"type": "column",
"value": "projectid"
},
{
"id": 2,
"type": "table",
"value": "projects"
},
{
"id": 4,
"type": "value",
"value": "highest%"
},
{
"id": 1,
"type": "table",
"value": "essays"
},
{
"id": 0,
"type": "column",
"value": "title"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
2
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,038
|
music_1
|
spider:train_spider.json:3579
|
Give me a list of the names of all songs ordered by their resolution.
|
SELECT song_name FROM song ORDER BY resolution
|
[
"Give",
"me",
"a",
"list",
"of",
"the",
"names",
"of",
"all",
"songs",
"ordered",
"by",
"their",
"resolution",
"."
] |
[
{
"id": 2,
"type": "column",
"value": "resolution"
},
{
"id": 1,
"type": "column",
"value": "song_name"
},
{
"id": 0,
"type": "table",
"value": "song"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
9
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
13
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O"
] |
16,039
|
mondial_geo
|
bird:train.json:8226
|
List the infant mortality of country with the least Amerindian.
|
SELECT T1.Infant_Mortality FROM population AS T1 INNER JOIN ethnicGroup AS T2 ON T1.Country = T2.Country WHERE T2.Name = 'Amerindian' ORDER BY T2.Percentage ASC LIMIT 1
|
[
"List",
"the",
"infant",
"mortality",
"of",
"country",
"with",
"the",
"least",
"Amerindian",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "infant_mortality"
},
{
"id": 2,
"type": "table",
"value": "ethnicgroup"
},
{
"id": 1,
"type": "table",
"value": "population"
},
{
"id": 4,
"type": "value",
"value": "Amerindian"
},
{
"id": 5,
"type": "column",
"value": "percentage"
},
{
"id": 6,
"type": "column",
"value": "country"
},
{
"id": 3,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
2,
3
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": [
9
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
5
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"O"
] |
16,040
|
apartment_rentals
|
spider:train_spider.json:1244
|
Show the addresses of the buildings that have apartments with more than 2 bathrooms.
|
SELECT T1.building_address FROM Apartment_Buildings AS T1 JOIN Apartments AS T2 ON T1.building_id = T2.building_id WHERE T2.bathroom_count > 2
|
[
"Show",
"the",
"addresses",
"of",
"the",
"buildings",
"that",
"have",
"apartments",
"with",
"more",
"than",
"2",
"bathrooms",
"."
] |
[
{
"id": 1,
"type": "table",
"value": "apartment_buildings"
},
{
"id": 0,
"type": "column",
"value": "building_address"
},
{
"id": 3,
"type": "column",
"value": "bathroom_count"
},
{
"id": 5,
"type": "column",
"value": "building_id"
},
{
"id": 2,
"type": "table",
"value": "apartments"
},
{
"id": 4,
"type": "value",
"value": "2"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
4
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": [
13
]
},
{
"entity_id": 4,
"token_idxs": [
12
]
},
{
"entity_id": 5,
"token_idxs": [
5
]
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"B-VALUE",
"B-COLUMN",
"O"
] |
16,041
|
music_4
|
spider:train_spider.json:6197
|
How many distinct artists have volumes?
|
SELECT COUNT(DISTINCT Artist_ID) FROM volume
|
[
"How",
"many",
"distinct",
"artists",
"have",
"volumes",
"?"
] |
[
{
"id": 1,
"type": "column",
"value": "artist_id"
},
{
"id": 0,
"type": "table",
"value": "volume"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-TABLE",
"O"
] |
16,042
|
aircraft
|
spider:train_spider.json:4825
|
List the names of aircrafts and the number of times it won matches.
|
SELECT T1.Aircraft , COUNT(*) FROM aircraft AS T1 JOIN MATCH AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft
|
[
"List",
"the",
"names",
"of",
"aircrafts",
"and",
"the",
"number",
"of",
"times",
"it",
"won",
"matches",
"."
] |
[
{
"id": 0,
"type": "column",
"value": "winning_aircraft"
},
{
"id": 4,
"type": "column",
"value": "aircraft_id"
},
{
"id": 1,
"type": "column",
"value": "aircraft"
},
{
"id": 2,
"type": "table",
"value": "aircraft"
},
{
"id": 3,
"type": "table",
"value": "match"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
4
]
},
{
"entity_id": 3,
"token_idxs": [
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
16,043
|
regional_sales
|
bird:train.json:2612
|
How many furniture cushions orders which have date of order in 2018?
|
SELECT SUM(CASE WHEN T1.OrderDate LIKE '%/%/18' AND T2.`Product Name` = 'Furniture Cushions' THEN 1 ELSE 0 END) FROM `Sales Orders` AS T1 INNER JOIN Products AS T2 ON T2.ProductID = T1._ProductID
|
[
"How",
"many",
"furniture",
"cushions",
"orders",
"which",
"have",
"date",
"of",
"order",
"in",
"2018",
"?"
] |
[
{
"id": 9,
"type": "value",
"value": "Furniture Cushions"
},
{
"id": 0,
"type": "table",
"value": "Sales Orders"
},
{
"id": 8,
"type": "column",
"value": "Product Name"
},
{
"id": 3,
"type": "column",
"value": "_productid"
},
{
"id": 2,
"type": "column",
"value": "productid"
},
{
"id": 6,
"type": "column",
"value": "orderdate"
},
{
"id": 1,
"type": "table",
"value": "products"
},
{
"id": 7,
"type": "value",
"value": "%/%/18"
},
{
"id": 4,
"type": "value",
"value": "0"
},
{
"id": 5,
"type": "value",
"value": "1"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3,
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": [
9
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": [
2
]
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"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-COLUMN",
"O",
"O",
"O"
] |
16,044
|
farm
|
spider:train_spider.json:54
|
Show the census ranking of cities whose status are not "Village".
|
SELECT Census_Ranking FROM city WHERE Status != "Village"
|
[
"Show",
"the",
"census",
"ranking",
"of",
"cities",
"whose",
"status",
"are",
"not",
"\"",
"Village",
"\"",
"."
] |
[
{
"id": 1,
"type": "column",
"value": "census_ranking"
},
{
"id": 3,
"type": "column",
"value": "Village"
},
{
"id": 2,
"type": "column",
"value": "status"
},
{
"id": 0,
"type": "table",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
7
]
},
{
"entity_id": 3,
"token_idxs": [
11
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
16,045
|
superhero
|
bird:dev.json:805
|
List the full names of superheroes with missing weight.
|
SELECT DISTINCT full_name FROM superhero WHERE full_name IS NOT NULL AND (weight_kg IS NULL OR weight_kg = 0)
|
[
"List",
"the",
"full",
"names",
"of",
"superheroes",
"with",
"missing",
"weight",
"."
] |
[
{
"id": 0,
"type": "table",
"value": "superhero"
},
{
"id": 1,
"type": "column",
"value": "full_name"
},
{
"id": 2,
"type": "column",
"value": "weight_kg"
},
{
"id": 3,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
5
]
},
{
"entity_id": 1,
"token_idxs": [
2,
3
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O"
] |
16,046
|
mondial_geo
|
bird:train.json:8433
|
What is the population gap between the United Kingdom and Italy?
|
SELECT MAX(Population) - MIN(Population) FROM country WHERE Name = 'United Kingdom' OR Name = 'Italy'
|
[
"What",
"is",
"the",
"population",
"gap",
"between",
"the",
"United",
"Kingdom",
"and",
"Italy",
"?"
] |
[
{
"id": 2,
"type": "value",
"value": "United Kingdom"
},
{
"id": 4,
"type": "column",
"value": "population"
},
{
"id": 0,
"type": "table",
"value": "country"
},
{
"id": 3,
"type": "value",
"value": "Italy"
},
{
"id": 1,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": [
7,
8
]
},
{
"entity_id": 3,
"token_idxs": [
10
]
},
{
"entity_id": 4,
"token_idxs": [
3
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"O"
] |
16,047
|
superhero
|
bird:dev.json:825
|
Identify the gender of the superhero who has the ability of Phoenix Force.
|
SELECT T4.gender FROM superhero AS T1 INNER JOIN hero_power AS T2 ON T1.id = T2.hero_id INNER JOIN superpower AS T3 ON T2.power_id = T3.id INNER JOIN gender AS T4 ON T1.gender_id = T4.id WHERE T3.power_name = 'Phoenix Force'
|
[
"Identify",
"the",
"gender",
"of",
"the",
"superhero",
"who",
"has",
"the",
"ability",
"of",
"Phoenix",
"Force",
"."
] |
[
{
"id": 3,
"type": "value",
"value": "Phoenix Force"
},
{
"id": 2,
"type": "column",
"value": "power_name"
},
{
"id": 4,
"type": "table",
"value": "superpower"
},
{
"id": 8,
"type": "table",
"value": "hero_power"
},
{
"id": 5,
"type": "column",
"value": "gender_id"
},
{
"id": 7,
"type": "table",
"value": "superhero"
},
{
"id": 9,
"type": "column",
"value": "power_id"
},
{
"id": 10,
"type": "column",
"value": "hero_id"
},
{
"id": 0,
"type": "column",
"value": "gender"
},
{
"id": 1,
"type": "table",
"value": "gender"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
2
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
11,
12
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": [
5
]
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
16,048
|
european_football_2
|
bird:dev.json:1127
|
Locate players with vision scores of 90 and above, state the country of these players.
|
SELECT DISTINCT t4.name FROM Player_Attributes AS t1 INNER JOIN Player AS t2 ON t1.player_api_id = t2.player_api_id INNER JOIN Match AS t3 ON t2.player_api_id = t3.home_player_8 INNER JOIN Country AS t4 ON t3.country_id = t4.id WHERE t1.vision > 89
|
[
"Locate",
"players",
"with",
"vision",
"scores",
"of",
"90",
"and",
"above",
",",
"state",
"the",
"country",
"of",
"these",
"players",
"."
] |
[
{
"id": 7,
"type": "table",
"value": "player_attributes"
},
{
"id": 9,
"type": "column",
"value": "player_api_id"
},
{
"id": 10,
"type": "column",
"value": "home_player_8"
},
{
"id": 5,
"type": "column",
"value": "country_id"
},
{
"id": 1,
"type": "table",
"value": "country"
},
{
"id": 2,
"type": "column",
"value": "vision"
},
{
"id": 8,
"type": "table",
"value": "player"
},
{
"id": 4,
"type": "table",
"value": "match"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "value",
"value": "89"
},
{
"id": 6,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
12
]
},
{
"entity_id": 2,
"token_idxs": [
3
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": [
1
]
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": [
14,
15
]
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"I-COLUMN",
"O"
] |
16,049
|
food_inspection
|
bird:train.json:8792
|
Which business had the most number of high risk violations? Give the name of the business.
|
SELECT T2.name FROM violations AS T1 INNER JOIN businesses AS T2 ON T1.business_id = T2.business_id WHERE T1.risk_category = 'High Risk' GROUP BY T2.name ORDER BY COUNT(T2.name) DESC LIMIT 1
|
[
"Which",
"business",
"had",
"the",
"most",
"number",
"of",
"high",
"risk",
"violations",
"?",
"Give",
"the",
"name",
"of",
"the",
"business",
"."
] |
[
{
"id": 3,
"type": "column",
"value": "risk_category"
},
{
"id": 5,
"type": "column",
"value": "business_id"
},
{
"id": 1,
"type": "table",
"value": "violations"
},
{
"id": 2,
"type": "table",
"value": "businesses"
},
{
"id": 4,
"type": "value",
"value": "High Risk"
},
{
"id": 0,
"type": "column",
"value": "name"
}
] |
[
{
"entity_id": 0,
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13
]
},
{
"entity_id": 1,
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9
]
},
{
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1
]
},
{
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},
{
"entity_id": 4,
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7,
8
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},
{
"entity_id": 5,
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},
{
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},
{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
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{
"entity_id": 10,
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
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},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"B-TABLE",
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"O",
"O"
] |
16,050
|
thrombosis_prediction
|
bird:dev.json:1199
|
How many patients who underwent testing in 1997 had protein levels outside the normal range?
|
SELECT COUNT(ID) FROM Laboratory WHERE (ALB <= 6.0 OR ALB >= 8.5) AND STRFTIME('%Y', Date) = '1997'
|
[
"How",
"many",
"patients",
"who",
"underwent",
"testing",
"in",
"1997",
"had",
"protein",
"levels",
"outside",
"the",
"normal",
"range",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "laboratory"
},
{
"id": 2,
"type": "value",
"value": "1997"
},
{
"id": 7,
"type": "column",
"value": "date"
},
{
"id": 3,
"type": "column",
"value": "alb"
},
{
"id": 4,
"type": "value",
"value": "6.0"
},
{
"id": 5,
"type": "value",
"value": "8.5"
},
{
"id": 1,
"type": "column",
"value": "id"
},
{
"id": 6,
"type": "value",
"value": "%Y"
}
] |
[
{
"entity_id": 0,
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},
{
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},
{
"entity_id": 2,
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7
]
},
{
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},
{
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},
{
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},
{
"entity_id": 6,
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},
{
"entity_id": 7,
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},
{
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},
{
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},
{
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},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
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},
{
"entity_id": 13,
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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",
"O",
"O",
"O",
"B-VALUE",
"O",
"O",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,051
|
music_1
|
spider:train_spider.json:3540
|
What are the file sizes and formats for all songs with a resolution lower than 800?
|
SELECT DISTINCT T1.file_size , T1.formats FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id WHERE T2.resolution < 800
|
[
"What",
"are",
"the",
"file",
"sizes",
"and",
"formats",
"for",
"all",
"songs",
"with",
"a",
"resolution",
"lower",
"than",
"800",
"?"
] |
[
{
"id": 4,
"type": "column",
"value": "resolution"
},
{
"id": 0,
"type": "column",
"value": "file_size"
},
{
"id": 1,
"type": "column",
"value": "formats"
},
{
"id": 2,
"type": "table",
"value": "files"
},
{
"id": 3,
"type": "table",
"value": "song"
},
{
"id": 6,
"type": "column",
"value": "f_id"
},
{
"id": 5,
"type": "value",
"value": "800"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
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3
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9
]
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{
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},
{
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15
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},
{
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{
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},
{
"entity_id": 8,
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},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
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},
{
"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O"
] |
16,052
|
food_inspection
|
bird:train.json:8838
|
How many of the businesses are located at 1825 POST St #223, San Francisco?
|
SELECT COUNT(business_id) FROM businesses WHERE address = '1825 POST St #223' AND city = 'SAN FRANCISCO'
|
[
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"are",
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"1825",
"POST",
"St",
"#",
"223",
",",
"San",
"Francisco",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "1825 POST St #223"
},
{
"id": 5,
"type": "value",
"value": "SAN FRANCISCO"
},
{
"id": 1,
"type": "column",
"value": "business_id"
},
{
"id": 0,
"type": "table",
"value": "businesses"
},
{
"id": 2,
"type": "column",
"value": "address"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
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"entity_id": 0,
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4
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},
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{
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5
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{
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"entity_id": 11,
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},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"I-VALUE",
"O",
"B-VALUE",
"I-VALUE",
"O"
] |
16,053
|
public_review_platform
|
bird:train.json:3890
|
What is the closing and opening time of businesses located at Tempe with highest star rating?
|
SELECT T2.closing_time, T2.opening_time FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T1.city LIKE 'Tempe' ORDER BY T1.stars DESC LIMIT 1
|
[
"What",
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"opening",
"time",
"of",
"businesses",
"located",
"at",
"Tempe",
"with",
"highest",
"star",
"rating",
"?"
] |
[
{
"id": 3,
"type": "table",
"value": "business_hours"
},
{
"id": 0,
"type": "column",
"value": "closing_time"
},
{
"id": 1,
"type": "column",
"value": "opening_time"
},
{
"id": 7,
"type": "column",
"value": "business_id"
},
{
"id": 2,
"type": "table",
"value": "business"
},
{
"id": 5,
"type": "value",
"value": "Tempe"
},
{
"id": 6,
"type": "column",
"value": "stars"
},
{
"id": 4,
"type": "column",
"value": "city"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
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5,
6
]
},
{
"entity_id": 2,
"token_idxs": [
8
]
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": [
11
]
},
{
"entity_id": 6,
"token_idxs": [
14
]
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
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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",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"I-COLUMN",
"O",
"B-TABLE",
"O",
"O",
"B-VALUE",
"O",
"O",
"B-COLUMN",
"O",
"O"
] |
16,054
|
authors
|
bird:train.json:3556
|
How many of the papers are preprinted or not published?
|
SELECT COUNT(Id) FROM Paper WHERE Year = 0
|
[
"How",
"many",
"of",
"the",
"papers",
"are",
"preprinted",
"or",
"not",
"published",
"?"
] |
[
{
"id": 0,
"type": "table",
"value": "paper"
},
{
"id": 1,
"type": "column",
"value": "year"
},
{
"id": 3,
"type": "column",
"value": "id"
},
{
"id": 2,
"type": "value",
"value": "0"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": []
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": []
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"O"
] |
16,055
|
flight_1
|
spider:train_spider.json:432
|
What are the names of the aircraft that the least people are certified to fly?
|
SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid GROUP BY T1.aid ORDER BY count(*) DESC LIMIT 1
|
[
"What",
"are",
"the",
"names",
"of",
"the",
"aircraft",
"that",
"the",
"least",
"people",
"are",
"certified",
"to",
"fly",
"?"
] |
[
{
"id": 2,
"type": "table",
"value": "certificate"
},
{
"id": 3,
"type": "table",
"value": "aircraft"
},
{
"id": 1,
"type": "column",
"value": "name"
},
{
"id": 0,
"type": "column",
"value": "aid"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
3
]
},
{
"entity_id": 2,
"token_idxs": [
12
]
},
{
"entity_id": 3,
"token_idxs": [
6
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O",
"O",
"O"
] |
16,056
|
architecture
|
spider:train_spider.json:6950
|
What are the distinct names and nationalities of the architects who have ever built a mill?
|
SELECT DISTINCT T1.name , T1.nationality FROM architect AS T1 JOIN mill AS t2 ON T1.id = T2.architect_id
|
[
"What",
"are",
"the",
"distinct",
"names",
"and",
"nationalities",
"of",
"the",
"architects",
"who",
"have",
"ever",
"built",
"a",
"mill",
"?"
] |
[
{
"id": 5,
"type": "column",
"value": "architect_id"
},
{
"id": 1,
"type": "column",
"value": "nationality"
},
{
"id": 2,
"type": "table",
"value": "architect"
},
{
"id": 0,
"type": "column",
"value": "name"
},
{
"id": 3,
"type": "table",
"value": "mill"
},
{
"id": 4,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
4
]
},
{
"entity_id": 1,
"token_idxs": [
6
]
},
{
"entity_id": 2,
"token_idxs": [
9
]
},
{
"entity_id": 3,
"token_idxs": [
15
]
},
{
"entity_id": 4,
"token_idxs": []
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-COLUMN",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"O",
"O",
"O",
"B-TABLE",
"O"
] |
16,057
|
law_episode
|
bird:train.json:1267
|
How many episodes did J.K. Simmons' role appear on the show?
|
SELECT COUNT(T1.role) FROM Credit AS T1 INNER JOIN Person AS T2 ON T2.person_id = T1.person_id WHERE T2.name = 'J.K. Simmons'
|
[
"How",
"many",
"episodes",
"did",
"J.K.",
"Simmons",
"'",
"role",
"appear",
"on",
"the",
"show",
"?"
] |
[
{
"id": 3,
"type": "value",
"value": "J.K. Simmons"
},
{
"id": 5,
"type": "column",
"value": "person_id"
},
{
"id": 0,
"type": "table",
"value": "credit"
},
{
"id": 1,
"type": "table",
"value": "person"
},
{
"id": 2,
"type": "column",
"value": "name"
},
{
"id": 4,
"type": "column",
"value": "role"
}
] |
[
{
"entity_id": 0,
"token_idxs": []
},
{
"entity_id": 1,
"token_idxs": [
8,
9
]
},
{
"entity_id": 2,
"token_idxs": []
},
{
"entity_id": 3,
"token_idxs": [
4,
5
]
},
{
"entity_id": 4,
"token_idxs": [
7
]
},
{
"entity_id": 5,
"token_idxs": []
},
{
"entity_id": 6,
"token_idxs": []
},
{
"entity_id": 7,
"token_idxs": []
},
{
"entity_id": 8,
"token_idxs": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"O",
"B-VALUE",
"I-VALUE",
"O",
"B-COLUMN",
"B-TABLE",
"I-TABLE",
"O",
"O",
"O"
] |
16,059
|
shakespeare
|
bird:train.json:3005
|
What is the description of the chapter where the character whose abrreviated name is 1Play appeared first?
|
SELECT T2.Description FROM paragraphs AS T1 INNER JOIN chapters AS T2 ON T1.chapter_id = T2.id INNER JOIN characters AS T3 ON T1.character_id = T3.id WHERE T3.Abbrev = '1Play' ORDER BY T1.chapter_id LIMIT 1
|
[
"What",
"is",
"the",
"description",
"of",
"the",
"chapter",
"where",
"the",
"character",
"whose",
"abrreviated",
"name",
"is",
"1Play",
"appeared",
"first",
"?"
] |
[
{
"id": 7,
"type": "column",
"value": "character_id"
},
{
"id": 0,
"type": "column",
"value": "description"
},
{
"id": 1,
"type": "table",
"value": "characters"
},
{
"id": 4,
"type": "column",
"value": "chapter_id"
},
{
"id": 5,
"type": "table",
"value": "paragraphs"
},
{
"id": 6,
"type": "table",
"value": "chapters"
},
{
"id": 2,
"type": "column",
"value": "abbrev"
},
{
"id": 3,
"type": "value",
"value": "1Play"
},
{
"id": 8,
"type": "column",
"value": "id"
}
] |
[
{
"entity_id": 0,
"token_idxs": [
3
]
},
{
"entity_id": 1,
"token_idxs": [
9
]
},
{
"entity_id": 2,
"token_idxs": [
11
]
},
{
"entity_id": 3,
"token_idxs": [
14
]
},
{
"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": []
},
{
"entity_id": 9,
"token_idxs": []
},
{
"entity_id": 10,
"token_idxs": []
},
{
"entity_id": 11,
"token_idxs": []
},
{
"entity_id": 12,
"token_idxs": []
},
{
"entity_id": 13,
"token_idxs": []
},
{
"entity_id": 14,
"token_idxs": []
},
{
"entity_id": 15,
"token_idxs": []
},
{
"entity_id": 16,
"token_idxs": []
},
{
"entity_id": 17,
"token_idxs": []
},
{
"entity_id": 18,
"token_idxs": []
},
{
"entity_id": 19,
"token_idxs": []
}
] |
[
"O",
"O",
"O",
"B-COLUMN",
"O",
"O",
"B-TABLE",
"O",
"O",
"B-TABLE",
"O",
"B-COLUMN",
"O",
"O",
"B-VALUE",
"O",
"O",
"O"
] |
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