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15,844
shakespeare
bird:train.json:2961
How many paragraphs contain the character Lord Abergavenny?
SELECT SUM(T1.ParagraphNum) FROM paragraphs AS T1 INNER JOIN characters AS T2 ON T1.character_id = T2.id WHERE T2.CharName = 'Lord Abergavenny'
[ "How", "many", "paragraphs", "contain", "the", "character", "Lord", "Abergavenny", "?" ]
[ { "id": 3, "type": "value", "value": "Lord Abergavenny" }, { "id": 4, "type": "column", "value": "paragraphnum" }, { "id": 5, "type": "column", "value": "character_id" }, { "id": 0, "type": "table", "value": "paragraphs" }, { "id": 1, "type": "table", "value": "characters" }, { "id": 2, "type": "column", "value": "charname" }, { "id": 6, "type": "column", "value": "id" } ]
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[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "O" ]
15,845
college_1
spider:train_spider.json:3210
How many different professors are there for the different schools?
SELECT count(*) , T1.school_code FROM department AS T1 JOIN professor AS T2 ON T1.dept_code = T2.dept_code GROUP BY T1.school_code
[ "How", "many", "different", "professors", "are", "there", "for", "the", "different", "schools", "?" ]
[ { "id": 0, "type": "column", "value": "school_code" }, { "id": 1, "type": "table", "value": "department" }, { "id": 2, "type": "table", "value": "professor" }, { "id": 3, "type": "column", "value": "dept_code" } ]
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[ "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,846
world_development_indicators
bird:train.json:2200
Which country has the lowest percentage of arable land?
SELECT CountryName FROM Indicators WHERE IndicatorName LIKE 'Arable land (% of land area)' ORDER BY Value DESC LIMIT 1
[ "Which", "country", "has", "the", "lowest", "percentage", "of", "arable", "land", "?" ]
[ { "id": 3, "type": "value", "value": "Arable land (% of land area)" }, { "id": 2, "type": "column", "value": "indicatorname" }, { "id": 1, "type": "column", "value": "countryname" }, { "id": 0, "type": "table", "value": "indicators" }, { "id": 4, "type": "column", "value": "value" } ]
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[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,847
products_gen_characteristics
spider:train_spider.json:5520
How many characteristics are there?
SELECT count(*) FROM CHARACTERISTICS
[ "How", "many", "characteristics", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "characteristics" } ]
[ { "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" ]
15,849
app_store
bird:train.json:2557
List down app that does not have negative sentiment and give their average rating?
SELECT T1.App, AVG(T2.Sentiment_Polarity) FROM playstore AS T1 INNER JOIN user_reviews AS T2 ON T1.App = T2.App WHERE T2.Sentiment != 'Negative' GROUP BY T1.App
[ "List", "down", "app", "that", "does", "not", "have", "negative", "sentiment", "and", "give", "their", "average", "rating", "?" ]
[ { "id": 5, "type": "column", "value": "sentiment_polarity" }, { "id": 2, "type": "table", "value": "user_reviews" }, { "id": 1, "type": "table", "value": "playstore" }, { "id": 3, "type": "column", "value": "sentiment" }, { "id": 4, "type": "value", "value": "Negative" }, { "id": 0, "type": "column", "value": "app" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 7 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,850
customers_campaigns_ecommerce
spider:train_spider.json:4624
Show all distinct product categories along with the number of mailshots in each category.
SELECT product_category , count(*) FROM mailshot_campaigns GROUP BY product_category
[ "Show", "all", "distinct", "product", "categories", "along", "with", "the", "number", "of", "mailshots", "in", "each", "category", "." ]
[ { "id": 0, "type": "table", "value": "mailshot_campaigns" }, { "id": 1, "type": "column", "value": "product_category" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,852
menu
bird:train.json:5539
What is the position coordinate on the page menu of the "Small Hominy" dish and how long did it appear?
SELECT T2.xpos, T2.ypos, T1.last_appeared - T1.first_appeared FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id WHERE T1.name = 'Small Hominy'
[ "What", "is", "the", "position", "coordinate", "on", "the", "page", "menu", "of", "the", "\"", "Small", "Hominy", "\"", "dish", "and", "how", "long", "did", "it", "appear", "?" ]
[ { "id": 7, "type": "column", "value": "first_appeared" }, { "id": 6, "type": "column", "value": "last_appeared" }, { "id": 5, "type": "value", "value": "Small Hominy" }, { "id": 3, "type": "table", "value": "menuitem" }, { "id": 9, "type": "column", "value": "dish_id" }, { "id": 0, "type": "column", "value": "xpos" }, { "id": 1, "type": "column", "value": "ypos" }, { "id": 2, "type": "table", "value": "dish" }, { "id": 4, "type": "column", "value": "name" }, { "id": 8, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-COLUMN", "I-COLUMN", "O" ]
15,853
e_commerce
bird:test.json:70
What is the product name and the color of the ordered items which have been shipped?
SELECT T1.product_name , T1.product_color FROM Products AS T1 JOIN Order_items AS T2 ON T1.product_id = T2.product_id JOIN Shipment_Items AS T3 ON T2.order_item_id = T3.order_item_id JOIN Shipments AS T4 ON T3.shipment_id = T4.shipment_id
[ "What", "is", "the", "product", "name", "and", "the", "color", "of", "the", "ordered", "items", "which", "have", "been", "shipped", "?" ]
[ { "id": 3, "type": "table", "value": "shipment_items" }, { "id": 1, "type": "column", "value": "product_color" }, { "id": 7, "type": "column", "value": "order_item_id" }, { "id": 0, "type": "column", "value": "product_name" }, { "id": 4, "type": "column", "value": "shipment_id" }, { "id": 6, "type": "table", "value": "order_items" }, { "id": 8, "type": "column", "value": "product_id" }, { "id": 2, "type": "table", "value": "shipments" }, { "id": 5, "type": "table", "value": "products" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O", "O", "O", "B-TABLE", "O" ]
15,854
protein_institute
spider:train_spider.json:1912
What is the name of the tallest building?
SELECT name FROM building ORDER BY height_feet DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "tallest", "building", "?" ]
[ { "id": 2, "type": "column", "value": "height_feet" }, { "id": 0, "type": "table", "value": "building" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,855
apartment_rentals
spider:train_spider.json:1221
What are the apartment number, start date, and end date of each apartment booking?
SELECT T2.apt_number , T1.booking_start_date , T1.booking_start_date FROM Apartment_Bookings AS T1 JOIN Apartments AS T2 ON T1.apt_id = T2.apt_id
[ "What", "are", "the", "apartment", "number", ",", "start", "date", ",", "and", "end", "date", "of", "each", "apartment", "booking", "?" ]
[ { "id": 1, "type": "column", "value": "booking_start_date" }, { "id": 2, "type": "table", "value": "apartment_bookings" }, { "id": 0, "type": "column", "value": "apt_number" }, { "id": 3, "type": "table", "value": "apartments" }, { "id": 4, "type": "column", "value": "apt_id" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "O" ]
15,856
coinmarketcap
bird:train.json:6295
List the names of the coins above the average price on April 28, 2013.
SELECT T1.name FROM coins AS T1 INNER JOIN historical AS T2 ON T1.id = T2.coin_id WHERE T2.date = '2018-04-28' AND T2.price > ( SELECT AVG(price) FROM historical WHERE date = '2018-04-28' )
[ "List", "the", "names", "of", "the", "coins", "above", "the", "average", "price", "on", "April", "28", ",", "2013", "." ]
[ { "id": 2, "type": "table", "value": "historical" }, { "id": 6, "type": "value", "value": "2018-04-28" }, { "id": 4, "type": "column", "value": "coin_id" }, { "id": 1, "type": "table", "value": "coins" }, { "id": 7, "type": "column", "value": "price" }, { "id": 0, "type": "column", "value": "name" }, { "id": 5, "type": "column", "value": "date" }, { "id": 3, "type": "column", "value": "id" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,857
student_loan
bird:train.json:4499
How many students are filed for bankruptcy?
SELECT COUNT(name) FROM filed_for_bankrupcy
[ "How", "many", "students", "are", "filed", "for", "bankruptcy", "?" ]
[ { "id": 0, "type": "table", "value": "filed_for_bankrupcy" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [ 4, 5, 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "I-TABLE", "I-TABLE", "O" ]
15,858
talkingdata
bird:train.json:1154
Please list the event IDs of the events that have happened on the device of the oldest user.
SELECT T2.event_id FROM gender_age AS T1 INNER JOIN events AS T2 ON T1.device_id = T2.device_id ORDER BY T1.age DESC LIMIT 1
[ "Please", "list", "the", "event", "IDs", "of", "the", "events", "that", "have", "happened", "on", "the", "device", "of", "the", "oldest", "user", "." ]
[ { "id": 1, "type": "table", "value": "gender_age" }, { "id": 4, "type": "column", "value": "device_id" }, { "id": 0, "type": "column", "value": "event_id" }, { "id": 2, "type": "table", "value": "events" }, { "id": 3, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 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", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
15,859
cre_Doc_and_collections
bird:test.json:677
What are the different descriptions of all the parent documents?
SELECT DISTINCT T2.Description FROM Document_Objects AS T1 JOIN Document_Objects AS T2 ON T1.Parent_Document_Object_ID = T2.Document_Object_ID
[ "What", "are", "the", "different", "descriptions", "of", "all", "the", "parent", "documents", "?" ]
[ { "id": 2, "type": "column", "value": "parent_document_object_id" }, { "id": 3, "type": "column", "value": "document_object_id" }, { "id": 1, "type": "table", "value": "document_objects" }, { "id": 0, "type": "column", "value": "description" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 9 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-TABLE", "O" ]
15,860
cre_Doc_Tracking_DB
spider:train_spider.json:4189
Count the total number of roles listed.
SELECT count(*) FROM ROLES
[ "Count", "the", "total", "number", "of", "roles", "listed", "." ]
[ { "id": 0, "type": "table", "value": "roles" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
15,861
card_games
bird:dev.json:446
What is percentage of the cards with a converted Mana Cost of 10 in set of Abyssal Horror?
SELECT CAST(SUM(CASE WHEN T1.convertedManaCost = 10 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.id), T1.name FROM cards AS T1 INNER JOIN sets AS T2 ON T2.code = T1.setCode WHERE T1.name = 'Abyssal Horror'
[ "What", "is", "percentage", "of", "the", "cards", "with", "a", "converted", "Mana", "Cost", "of", "10", "in", "set", "of", "Abyssal", "Horror", "?" ]
[ { "id": 10, "type": "column", "value": "convertedmanacost" }, { "id": 3, "type": "value", "value": "Abyssal Horror" }, { "id": 5, "type": "column", "value": "setcode" }, { "id": 1, "type": "table", "value": "cards" }, { "id": 0, "type": "column", "value": "name" }, { "id": 2, "type": "table", "value": "sets" }, { "id": 4, "type": "column", "value": "code" }, { "id": 6, "type": "value", "value": "100" }, { "id": 7, "type": "column", "value": "id" }, { "id": 11, "type": "value", "value": "10" }, { "id": 8, "type": "value", "value": "0" }, { "id": 9, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 14 ] }, { "entity_id": 3, "token_idxs": [ 16, 17 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 15 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 12 ] }, { "entity_id": 10, "token_idxs": [ 8, 9, 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", "O", "B-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-VALUE", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "I-VALUE", "O" ]
15,862
car_racing
bird:test.json:1592
Find the total number of drivers.
SELECT count(*) FROM driver
[ "Find", "the", "total", "number", "of", "drivers", "." ]
[ { "id": 0, "type": "table", "value": "driver" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,863
works_cycles
bird:train.json:7400
Please list the top 3 discounts with the highest discount percentage and fall under the reseller category.
SELECT Description, DiscountPct FROM SpecialOffer WHERE Category = 'Reseller' ORDER BY DiscountPct DESC LIMIT 0, 3
[ "Please", "list", "the", "top", "3", "discounts", "with", "the", "highest", "discount", "percentage", "and", "fall", "under", "the", "reseller", "category", "." ]
[ { "id": 0, "type": "table", "value": "specialoffer" }, { "id": 1, "type": "column", "value": "description" }, { "id": 2, "type": "column", "value": "discountpct" }, { "id": 3, "type": "column", "value": "category" }, { "id": 4, "type": "value", "value": "Reseller" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 16 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,864
superhero
bird:dev.json:820
How strong is the Hulk?
SELECT T2.attribute_value FROM superhero AS T1 INNER JOIN hero_attribute AS T2 ON T1.id = T2.hero_id INNER JOIN attribute AS T3 ON T2.attribute_id = T3.id WHERE T1.superhero_name = 'Hulk' AND T3.attribute_name = 'Strength'
[ "How", "strong", "is", "the", "Hulk", "?" ]
[ { "id": 0, "type": "column", "value": "attribute_value" }, { "id": 3, "type": "table", "value": "hero_attribute" }, { "id": 6, "type": "column", "value": "superhero_name" }, { "id": 8, "type": "column", "value": "attribute_name" }, { "id": 4, "type": "column", "value": "attribute_id" }, { "id": 1, "type": "table", "value": "attribute" }, { "id": 2, "type": "table", "value": "superhero" }, { "id": 9, "type": "value", "value": "Strength" }, { "id": 10, "type": "column", "value": "hero_id" }, { "id": 7, "type": "value", "value": "Hulk" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 4 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 1 ] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 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", "B-VALUE", "O" ]
15,865
works_cycles
bird:train.json:7158
To the products which could make the profit as 21.9037, what were their list price after October of 2012?
SELECT T1.ListPrice FROM Product AS T1 INNER JOIN ProductListPriceHistory AS T2 ON T1.ProductID = T2.ProductID WHERE T1.ListPrice - T1.StandardCost > 21.9037 AND STRFTIME('%Y-%m-%d', T2.StartDate) >= '2012-10-01'
[ "To", "the", "products", "which", "could", "make", "the", "profit", "as", "21.9037", ",", "what", "were", "their", "list", "price", "after", "October", "of", "2012", "?" ]
[ { "id": 2, "type": "table", "value": "productlistpricehistory" }, { "id": 6, "type": "column", "value": "standardcost" }, { "id": 5, "type": "value", "value": "2012-10-01" }, { "id": 0, "type": "column", "value": "listprice" }, { "id": 3, "type": "column", "value": "productid" }, { "id": 8, "type": "column", "value": "startdate" }, { "id": 7, "type": "value", "value": "%Y-%m-%d" }, { "id": 1, "type": "table", "value": "product" }, { "id": 4, "type": "value", "value": "21.9037" } ]
[ { "entity_id": 0, "token_idxs": [ 14, 15 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
15,867
music_1
spider:train_spider.json:3627
Find the names of the artists who are from Bangladesh and have never received rating higher than 7.
SELECT DISTINCT artist_name FROM artist WHERE country = "Bangladesh" EXCEPT SELECT DISTINCT artist_name FROM song WHERE rating > 7
[ "Find", "the", "names", "of", "the", "artists", "who", "are", "from", "Bangladesh", "and", "have", "never", "received", "rating", "higher", "than", "7", "." ]
[ { "id": 2, "type": "column", "value": "artist_name" }, { "id": 4, "type": "column", "value": "Bangladesh" }, { "id": 3, "type": "column", "value": "country" }, { "id": 0, "type": "table", "value": "artist" }, { "id": 5, "type": "column", "value": "rating" }, { "id": 1, "type": "table", "value": "song" }, { "id": 6, "type": "value", "value": "7" } ]
[ { "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": [ 9 ] }, { "entity_id": 5, "token_idxs": [ 14 ] }, { "entity_id": 6, "token_idxs": [ 17 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,868
sales
bird:train.json:5423
Identify customer IDs who bought products priced from 1000 to 2000.
SELECT DISTINCT T2.CustomerID FROM Products AS T1 INNER JOIN Sales AS T2 ON T1.ProductID = T2.ProductID WHERE T1.Price BETWEEN 1000 AND 2000
[ "Identify", "customer", "IDs", "who", "bought", "products", "priced", "from", "1000", "to", "2000", "." ]
[ { "id": 0, "type": "column", "value": "customerid" }, { "id": 6, "type": "column", "value": "productid" }, { "id": 1, "type": "table", "value": "products" }, { "id": 2, "type": "table", "value": "sales" }, { "id": 3, "type": "column", "value": "price" }, { "id": 4, "type": "value", "value": "1000" }, { "id": 5, "type": "value", "value": "2000" } ]
[ { "entity_id": 0, "token_idxs": [ 1, 2 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [ 8 ] }, { "entity_id": 5, "token_idxs": [ 10 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,869
music_tracker
bird:train.json:2049
What is the release title of the single under the "funk" tag that was released the oldest?
SELECT T1.groupName FROM torrents AS T1 INNER JOIN tags AS T2 ON T1.id = T2.id WHERE T2.tag LIKE 'funk' AND T1.releaseType = 'single' ORDER BY T1.groupYear LIMIT 1
[ "What", "is", "the", "release", "title", "of", "the", "single", "under", "the", "\"", "funk", "\"", "tag", "that", "was", "released", "the", "oldest", "?" ]
[ { "id": 7, "type": "column", "value": "releasetype" }, { "id": 0, "type": "column", "value": "groupname" }, { "id": 3, "type": "column", "value": "groupyear" }, { "id": 1, "type": "table", "value": "torrents" }, { "id": 8, "type": "value", "value": "single" }, { "id": 2, "type": "table", "value": "tags" }, { "id": 6, "type": "value", "value": "funk" }, { "id": 5, "type": "column", "value": "tag" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "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": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 11 ] }, { "entity_id": 7, "token_idxs": [ 3 ] }, { "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", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "B-VALUE", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,870
formula_1
spider:train_spider.json:2206
What are the names of all races that occurred after 12:00:00 or before 09:00:00?
SELECT name FROM races WHERE TIME > "12:00:00" OR TIME < "09:00:00"
[ "What", "are", "the", "names", "of", "all", "races", "that", "occurred", "after", "12:00:00", "or", "before", "09:00:00", "?" ]
[ { "id": 3, "type": "column", "value": "12:00:00" }, { "id": 4, "type": "column", "value": "09:00:00" }, { "id": 0, "type": "table", "value": "races" }, { "id": 1, "type": "column", "value": "name" }, { "id": 2, "type": "column", "value": "time" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 10 ] }, { "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", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
15,871
chinook_1
spider:train_spider.json:873
Please list all album titles in alphabetical order.
SELECT Title FROM ALBUM ORDER BY Title
[ "Please", "list", "all", "album", "titles", "in", "alphabetical", "order", "." ]
[ { "id": 0, "type": "table", "value": "album" }, { "id": 1, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O" ]
15,872
shop_membership
spider:train_spider.json:5409
What are the opening years in which at least two shops opened?
SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2
[ "What", "are", "the", "opening", "years", "in", "which", "at", "least", "two", "shops", "opened", "?" ]
[ { "id": 1, "type": "column", "value": "open_year" }, { "id": 0, "type": "table", "value": "branch" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O" ]
15,873
movie_3
bird:train.json:9208
Calculate customers' total payment amount in August, 2005.
SELECT SUM(amount) FROM payment WHERE SUBSTR(payment_date, 1, 7) = '2005-08'
[ "Calculate", "customers", "'", "total", "payment", "amount", "in", "August", ",", "2005", "." ]
[ { "id": 3, "type": "column", "value": "payment_date" }, { "id": 0, "type": "table", "value": "payment" }, { "id": 1, "type": "value", "value": "2005-08" }, { "id": 2, "type": "column", "value": "amount" }, { "id": 4, "type": "value", "value": "1" }, { "id": 5, "type": "value", "value": "7" } ]
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[ "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O" ]
15,874
behavior_monitoring
spider:train_spider.json:3113
Find the texts of assessment notes for teachers with last name "Schuster".
SELECT T1.text_of_notes FROM Assessment_Notes AS T1 JOIN Teachers AS T2 ON T1.teacher_id = T2.teacher_id WHERE T2.last_name = "Schuster"
[ "Find", "the", "texts", "of", "assessment", "notes", "for", "teachers", "with", "last", "name", "\"", "Schuster", "\"", "." ]
[ { "id": 1, "type": "table", "value": "assessment_notes" }, { "id": 0, "type": "column", "value": "text_of_notes" }, { "id": 5, "type": "column", "value": "teacher_id" }, { "id": 3, "type": "column", "value": "last_name" }, { "id": 2, "type": "table", "value": "teachers" }, { "id": 4, "type": "column", "value": "Schuster" } ]
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[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "O", "O" ]
15,875
dorm_1
spider:train_spider.json:5684
How many students are there?
SELECT count(*) FROM student
[ "How", "many", "students", "are", "there", "?" ]
[ { "id": 0, "type": "table", "value": "student" } ]
[ { "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" ]
15,876
hr_1
spider:train_spider.json:3524
What the full names, ids of each employee and the name of the country they are in?
SELECT T1.first_name , T1.last_name , T1.employee_id , T4.country_name FROM employees AS T1 JOIN departments AS T2 ON T1.department_id = T2.department_id JOIN locations AS T3 ON T2.location_id = T3.location_id JOIN countries AS T4 ON T3.country_id = T4.country_id
[ "What", "the", "full", "names", ",", "ids", "of", "each", "employee", "and", "the", "name", "of", "the", "country", "they", "are", "in", "?" ]
[ { "id": 10, "type": "column", "value": "department_id" }, { "id": 3, "type": "column", "value": "country_name" }, { "id": 2, "type": "column", "value": "employee_id" }, { "id": 8, "type": "table", "value": "departments" }, { "id": 9, "type": "column", "value": "location_id" }, { "id": 0, "type": "column", "value": "first_name" }, { "id": 6, "type": "column", "value": "country_id" }, { "id": 1, "type": "column", "value": "last_name" }, { "id": 4, "type": "table", "value": "countries" }, { "id": 5, "type": "table", "value": "locations" }, { "id": 7, "type": "table", "value": "employees" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,877
college_1
spider:train_spider.json:3295
What is the average gpa of the students enrolled in the course with code ACCT-211?
SELECT avg(T2.stu_gpa) FROM enroll AS T1 JOIN student AS T2 ON T1.stu_num = T2.stu_num JOIN CLASS AS T3 ON T1.class_code = T3.class_code WHERE T3.crs_code = 'ACCT-211'
[ "What", "is", "the", "average", "gpa", "of", "the", "students", "enrolled", "in", "the", "course", "with", "code", "ACCT-211", "?" ]
[ { "id": 6, "type": "column", "value": "class_code" }, { "id": 1, "type": "column", "value": "crs_code" }, { "id": 2, "type": "value", "value": "ACCT-211" }, { "id": 3, "type": "column", "value": "stu_gpa" }, { "id": 5, "type": "table", "value": "student" }, { "id": 7, "type": "column", "value": "stu_num" }, { "id": 4, "type": "table", "value": "enroll" }, { "id": 0, "type": "table", "value": "class" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O" ]
15,878
retail_world
bird:train.json:6616
Name all products supplied by Zaanse Snoepfabriek.
SELECT T1.ProductName FROM Products AS T1 INNER JOIN Suppliers AS T2 ON T1.SupplierID = T2.SupplierID WHERE T2.CompanyName = 'Zaanse Snoepfabriek'
[ "Name", "all", "products", "supplied", "by", "Zaanse", "Snoepfabriek", "." ]
[ { "id": 4, "type": "value", "value": "Zaanse Snoepfabriek" }, { "id": 0, "type": "column", "value": "productname" }, { "id": 3, "type": "column", "value": "companyname" }, { "id": 5, "type": "column", "value": "supplierid" }, { "id": 2, "type": "table", "value": "suppliers" }, { "id": 1, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5, 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-TABLE", "O", "B-VALUE", "I-VALUE", "O" ]
15,879
university
bird:train.json:8120
Give the name and score of the university ID 124.
SELECT T2.university_name, T1.score FROM university_ranking_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id WHERE T2.id = 124
[ "Give", "the", "name", "and", "score", "of", "the", "university", "ID", "124", "." ]
[ { "id": 2, "type": "table", "value": "university_ranking_year" }, { "id": 0, "type": "column", "value": "university_name" }, { "id": 6, "type": "column", "value": "university_id" }, { "id": 3, "type": "table", "value": "university" }, { "id": 1, "type": "column", "value": "score" }, { "id": 5, "type": "value", "value": "124" }, { "id": 4, "type": "column", "value": "id" } ]
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[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
15,880
sales_in_weather
bird:train.json:8155
How many units of item no.5 were sold in store no.3 on average on the days when the max temperature exceeded 90?
SELECT CAST(SUM(T1.units) AS REAL) / COUNT(T1.`date`) FROM sales_in_weather AS T1 INNER JOIN relation AS T2 ON T1.store_nbr = T2.store_nbr INNER JOIN weather AS T3 ON T2.station_nbr = T3.station_nbr WHERE T1.store_nbr = 3 AND T1.item_nbr = 5 AND T3.tmax > 90
[ "How", "many", "units", "of", "item", "no.5", "were", "sold", "in", "store", "no.3", "on", "average", "on", "the", "days", "when", "the", "max", "temperature", "exceeded", "90", "?" ]
[ { "id": 1, "type": "table", "value": "sales_in_weather" }, { "id": 3, "type": "column", "value": "station_nbr" }, { "id": 4, "type": "column", "value": "store_nbr" }, { "id": 2, "type": "table", "value": "relation" }, { "id": 6, "type": "column", "value": "item_nbr" }, { "id": 0, "type": "table", "value": "weather" }, { "id": 11, "type": "column", "value": "units" }, { "id": 8, "type": "column", "value": "tmax" }, { "id": 10, "type": "column", "value": "date" }, { "id": 9, "type": "value", "value": "90" }, { "id": 5, "type": "value", "value": "3" }, { "id": 7, "type": "value", "value": "5" } ]
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[ "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "I-TABLE", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,881
soccer_2016
bird:train.json:1802
Among all the matches SC Ganguly has played in, what is the highest winning margin?
SELECT MAX(T3.Win_Margin) FROM Player AS T1 INNER JOIN Player_Match AS T2 ON T1.Player_Id = T2.Player_Id INNER JOIN Match AS T3 ON T2.Match_Id = T3.Match_Id WHERE T1.Player_Name = 'SC Ganguly'
[ "Among", "all", "the", "matches", "SC", "Ganguly", "has", "played", "in", ",", "what", "is", "the", "highest", "winning", "margin", "?" ]
[ { "id": 5, "type": "table", "value": "player_match" }, { "id": 1, "type": "column", "value": "player_name" }, { "id": 2, "type": "value", "value": "SC Ganguly" }, { "id": 3, "type": "column", "value": "win_margin" }, { "id": 7, "type": "column", "value": "player_id" }, { "id": 6, "type": "column", "value": "match_id" }, { "id": 4, "type": "table", "value": "player" }, { "id": 0, "type": "table", "value": "match" } ]
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[ "O", "O", "O", "B-TABLE", "B-VALUE", "I-VALUE", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,882
legislator
bird:train.json:4736
How many current legislators do not have an account on ballotpedia.org ?
SELECT COUNT(*) FROM current WHERE ballotpedia_id = '' OR ballotpedia_id IS NULL
[ "How", "many", "current", "legislators", "do", "not", "have", "an", "account", "on", "ballotpedia.org", "?" ]
[ { "id": 1, "type": "column", "value": "ballotpedia_id" }, { "id": 0, "type": "table", "value": "current" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,883
bike_1
spider:train_spider.json:149
What is the average bike availability in stations that are not located in Palo Alto?
SELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = "Palo Alto")
[ "What", "is", "the", "average", "bike", "availability", "in", "stations", "that", "are", "not", "located", "in", "Palo", "Alto", "?" ]
[ { "id": 1, "type": "column", "value": "bikes_available" }, { "id": 2, "type": "column", "value": "station_id" }, { "id": 6, "type": "column", "value": "Palo Alto" }, { "id": 3, "type": "table", "value": "station" }, { "id": 0, "type": "table", "value": "status" }, { "id": 5, "type": "column", "value": "city" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 13, 14 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,885
language_corpus
bird:train.json:5759
State the Wikipedia page title that has revision page id of 28040864.
SELECT title FROM pages WHERE revision = 28040864
[ "State", "the", "Wikipedia", "page", "title", "that", "has", "revision", "page", "i", "d", "of", "28040864", "." ]
[ { "id": 2, "type": "column", "value": "revision" }, { "id": 3, "type": "value", "value": "28040864" }, { "id": 0, "type": "table", "value": "pages" }, { "id": 1, "type": "column", "value": "title" } ]
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[ "O", "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O" ]
15,886
government_shift
bird:test.json:381
Find details of all the services that have interacted with `` 15 ij '' for the the channel details.
select distinct t1.service_details from services as t1 join customer_interactions as t2 on t1.service_id = t2.service_id join channels as t3 on t2.channel_id = t3.channel_id where t3.channel_details = "15 ij"
[ "Find", "details", "of", "all", "the", "services", "that", "have", "interacted", "with", "`", "`", "15", "ij", "''", "for", "the", "the", "channel", "details", "." ]
[ { "id": 5, "type": "table", "value": "customer_interactions" }, { "id": 0, "type": "column", "value": "service_details" }, { "id": 2, "type": "column", "value": "channel_details" }, { "id": 6, "type": "column", "value": "channel_id" }, { "id": 7, "type": "column", "value": "service_id" }, { "id": 1, "type": "table", "value": "channels" }, { "id": 4, "type": "table", "value": "services" }, { "id": 3, "type": "column", "value": "15 ij" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,887
real_estate_rentals
bird:test.json:1398
Which countries and cities are included in addresses?
SELECT country , town_city FROM Addresses;
[ "Which", "countries", "and", "cities", "are", "included", "in", "addresses", "?" ]
[ { "id": 0, "type": "table", "value": "addresses" }, { "id": 2, "type": "column", "value": "town_city" }, { "id": 1, "type": "column", "value": "country" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,888
chicago_crime
bird:train.json:8680
What kind of location in Austin reported the most number of crimes?
SELECT T2.location_description FROM District AS T1 INNER JOIN Crime AS T2 ON T2.district_no = T1.district_no WHERE T1.district_name = 'Austin' GROUP BY T2.location_description ORDER BY COUNT(T2.case_number) DESC LIMIT 1
[ "What", "kind", "of", "location", "in", "Austin", "reported", "the", "most", "number", "of", "crimes", "?" ]
[ { "id": 0, "type": "column", "value": "location_description" }, { "id": 3, "type": "column", "value": "district_name" }, { "id": 5, "type": "column", "value": "district_no" }, { "id": 6, "type": "column", "value": "case_number" }, { "id": 1, "type": "table", "value": "district" }, { "id": 4, "type": "value", "value": "Austin" }, { "id": 2, "type": "table", "value": "crime" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 11 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 5 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "B-VALUE", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,889
customers_and_orders
bird:test.json:265
What are the product type code with at least two products?
SELECT product_type_code FROM Products GROUP BY product_type_code HAVING count(*) >= 2
[ "What", "are", "the", "product", "type", "code", "with", "at", "least", "two", "products", "?" ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 0, "type": "table", "value": "products" }, { "id": 2, "type": "value", "value": "2" } ]
[ { "entity_id": 0, "token_idxs": [ 10 ] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O" ]
15,890
restaurant
bird:train.json:1734
What is the region of 1149 El Camino Real?
SELECT T2.region FROM location AS T1 INNER JOIN geographic AS T2 ON T1.city = T2.city WHERE T1.street_num = 1149 AND T1.street_name = 'el camino real'
[ "What", "is", "the", "region", "of", "1149", "El", "Camino", "Real", "?" ]
[ { "id": 7, "type": "value", "value": "el camino real" }, { "id": 6, "type": "column", "value": "street_name" }, { "id": 2, "type": "table", "value": "geographic" }, { "id": 4, "type": "column", "value": "street_num" }, { "id": 1, "type": "table", "value": "location" }, { "id": 0, "type": "column", "value": "region" }, { "id": 3, "type": "column", "value": "city" }, { "id": 5, "type": "value", "value": "1149" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 6, 7 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 5 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 8 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-VALUE", "B-TABLE", "I-TABLE", "B-VALUE", "O" ]
15,891
professional_basketball
bird:train.json:2911
Please list the top five players with the most steals in the year 1997. Please give their full name.
SELECT DISTINCT T1.firstName, T1.middleName, T1.lastName FROM players AS T1 INNER JOIN player_allstar AS T2 ON T1.playerID = T2.playerID WHERE T2.season_id = 1997 ORDER BY T2.steals DESC LIMIT 5
[ "Please", "list", "the", "top", "five", "players", "with", "the", "most", "steals", "in", "the", "year", "1997", ".", "Please", "give", "their", "full", "name", "." ]
[ { "id": 4, "type": "table", "value": "player_allstar" }, { "id": 1, "type": "column", "value": "middlename" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 5, "type": "column", "value": "season_id" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 8, "type": "column", "value": "playerid" }, { "id": 3, "type": "table", "value": "players" }, { "id": 7, "type": "column", "value": "steals" }, { "id": 6, "type": "value", "value": "1997" } ]
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[ "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,892
allergy_1
spider:train_spider.json:449
What is the type of allergy Cat?
SELECT allergytype FROM Allergy_type WHERE allergy = "Cat"
[ "What", "is", "the", "type", "of", "allergy", "Cat", "?" ]
[ { "id": 0, "type": "table", "value": "allergy_type" }, { "id": 1, "type": "column", "value": "allergytype" }, { "id": 2, "type": "column", "value": "allergy" }, { "id": 3, "type": "column", "value": "Cat" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
15,893
mondial_geo
bird:train.json:8338
What is the height of the mountain on which river 'Lech' is located? Please also provide its longitude and latitude.
SELECT T1.Height, T1.Latitude, T1.Longitude FROM mountain AS T1 INNER JOIN geo_mountain AS T2 ON T1.Name = T2.Mountain INNER JOIN province AS T3 ON T3.Name = T2.Province INNER JOIN located AS T4 ON T4.Province = T3.Name WHERE T4.River = 'Lech'
[ "What", "is", "the", "height", "of", "the", "mountain", "on", "which", "river", "'", "Lech", "'", "is", "located", "?", "Please", "also", "provide", "its", "longitude", "and", "latitude", "." ]
[ { "id": 10, "type": "table", "value": "geo_mountain" }, { "id": 2, "type": "column", "value": "longitude" }, { "id": 1, "type": "column", "value": "latitude" }, { "id": 6, "type": "table", "value": "province" }, { "id": 7, "type": "column", "value": "province" }, { "id": 9, "type": "table", "value": "mountain" }, { "id": 11, "type": "column", "value": "mountain" }, { "id": 3, "type": "table", "value": "located" }, { "id": 0, "type": "column", "value": "height" }, { "id": 4, "type": "column", "value": "river" }, { "id": 5, "type": "value", "value": "Lech" }, { "id": 8, "type": "column", "value": "name" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "B-VALUE", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "B-COLUMN", "O" ]
15,894
soccer_2016
bird:train.json:1986
Which is the country of the city named "Rajkot"?
SELECT T1.Country_Name FROM Country AS T1 INNER JOIN city AS T2 ON T1.Country_Id = T2.Country_Id WHERE city_name = 'Rajkot'
[ "Which", "is", "the", "country", "of", "the", "city", "named", "\"", "Rajkot", "\"", "?" ]
[ { "id": 0, "type": "column", "value": "country_name" }, { "id": 5, "type": "column", "value": "country_id" }, { "id": 3, "type": "column", "value": "city_name" }, { "id": 1, "type": "table", "value": "country" }, { "id": 4, "type": "value", "value": "Rajkot" }, { "id": 2, "type": "table", "value": "city" } ]
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[ "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "O", "O" ]
15,896
college_1
spider:train_spider.json:3281
Find the last name and hire date of the professor who is in office DRE 102.
SELECT T1.emp_lname , T1.emp_hiredate FROM employee AS T1 JOIN professor AS T2 ON T1.emp_num = T2.emp_num WHERE T2.prof_office = 'DRE 102'
[ "Find", "the", "last", "name", "and", "hire", "date", "of", "the", "professor", "who", "is", "in", "office", "DRE", "102", "." ]
[ { "id": 1, "type": "column", "value": "emp_hiredate" }, { "id": 4, "type": "column", "value": "prof_office" }, { "id": 0, "type": "column", "value": "emp_lname" }, { "id": 3, "type": "table", "value": "professor" }, { "id": 2, "type": "table", "value": "employee" }, { "id": 5, "type": "value", "value": "DRE 102" }, { "id": 6, "type": "column", "value": "emp_num" } ]
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[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "B-VALUE", "I-VALUE", "O" ]
15,897
professional_basketball
bird:train.json:2811
In what year did the only team to beat the Houston in the final round of postseason series games earn its lowest ranking?
SELECT T2.year FROM series_post AS T1 INNER JOIN teams AS T2 ON T1.tmIDWinner = T2.tmID WHERE T1.round = 'DSF' AND T1.tmIDLoser = 'HSM' ORDER BY T2.rank ASC LIMIT 1
[ "In", "what", "year", "did", "the", "only", "team", "to", "beat", "the", "Houston", "in", "the", "final", "round", "of", "postseason", "series", "games", "earn", "its", "lowest", "ranking", "?" ]
[ { "id": 1, "type": "table", "value": "series_post" }, { "id": 4, "type": "column", "value": "tmidwinner" }, { "id": 8, "type": "column", "value": "tmidloser" }, { "id": 2, "type": "table", "value": "teams" }, { "id": 6, "type": "column", "value": "round" }, { "id": 0, "type": "column", "value": "year" }, { "id": 3, "type": "column", "value": "rank" }, { "id": 5, "type": "column", "value": "tmid" }, { "id": 7, "type": "value", "value": "DSF" }, { "id": 9, "type": "value", "value": "HSM" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 17 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 22 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 14 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,898
customers_and_addresses
spider:train_spider.json:6081
Find the name of customers who are living in Colorado?
SELECT t1.customer_name FROM customers AS t1 JOIN customer_addresses AS t2 ON t1.customer_id = t2.customer_id JOIN addresses AS t3 ON t2.address_id = t3.address_id WHERE t3.state_province_county = "Colorado"
[ "Find", "the", "name", "of", "customers", "who", "are", "living", "in", "Colorado", "?" ]
[ { "id": 2, "type": "column", "value": "state_province_county" }, { "id": 5, "type": "table", "value": "customer_addresses" }, { "id": 0, "type": "column", "value": "customer_name" }, { "id": 7, "type": "column", "value": "customer_id" }, { "id": 6, "type": "column", "value": "address_id" }, { "id": 1, "type": "table", "value": "addresses" }, { "id": 4, "type": "table", "value": "customers" }, { "id": 3, "type": "column", "value": "Colorado" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 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-TABLE", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,899
department_store
spider:train_spider.json:4746
What are the maximum and minimum product prices for each product type?
SELECT product_type_code , max(product_price) , min(product_price) FROM products GROUP BY product_type_code
[ "What", "are", "the", "maximum", "and", "minimum", "product", "prices", "for", "each", "product", "type", "?" ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 2, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 10, 11 ] }, { "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", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,900
headphone_store
bird:test.json:933
What are the model, class, and construction of the cheapest headphone?
SELECT model , CLASS , construction FROM headphone ORDER BY price LIMIT 1
[ "What", "are", "the", "model", ",", "class", ",", "and", "construction", "of", "the", "cheapest", "headphone", "?" ]
[ { "id": 3, "type": "column", "value": "construction" }, { "id": 0, "type": "table", "value": "headphone" }, { "id": 1, "type": "column", "value": "model" }, { "id": 2, "type": "column", "value": "class" }, { "id": 4, "type": "column", "value": "price" } ]
[ { "entity_id": 0, "token_idxs": [ 12 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,901
store_1
spider:train_spider.json:627
List title of albums have the number of tracks greater than 10.
SELECT T1.title FROM albums AS T1 JOIN tracks AS T2 ON T1.id = T2.album_id GROUP BY T1.id HAVING count(T1.id) > 10;
[ "List", "title", "of", "albums", "have", "the", "number", "of", "tracks", "greater", "than", "10", "." ]
[ { "id": 5, "type": "column", "value": "album_id" }, { "id": 2, "type": "table", "value": "albums" }, { "id": 3, "type": "table", "value": "tracks" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "column", "value": "id" }, { "id": 4, "type": "value", "value": "10" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 1 ] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [ 11 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-COLUMN", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "O" ]
15,902
movie_3
bird:train.json:9339
List down film titles from id 1 to 10.
SELECT title FROM film WHERE film_id BETWEEN 1 AND 10
[ "List", "down", "film", "titles", "from", "i", "d", "1", "to", "10", "." ]
[ { "id": 2, "type": "column", "value": "film_id" }, { "id": 1, "type": "column", "value": "title" }, { "id": 0, "type": "table", "value": "film" }, { "id": 4, "type": "value", "value": "10" }, { "id": 3, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "O", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,903
film_rank
spider:train_spider.json:4125
Count the number of markets that have a number of cities lower than 300.
SELECT count(*) FROM market WHERE Number_cities < 300
[ "Count", "the", "number", "of", "markets", "that", "have", "a", "number", "of", "cities", "lower", "than", "300", "." ]
[ { "id": 1, "type": "column", "value": "number_cities" }, { "id": 0, "type": "table", "value": "market" }, { "id": 2, "type": "value", "value": "300" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 8, 9, 10 ] }, { "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", "B-TABLE", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "B-VALUE", "O" ]
15,904
chinook_1
spider:train_spider.json:812
What is all the customer information for customers in NY state?
SELECT * FROM CUSTOMER WHERE State = "NY"
[ "What", "is", "all", "the", "customer", "information", "for", "customers", "in", "NY", "state", "?" ]
[ { "id": 0, "type": "table", "value": "customer" }, { "id": 1, "type": "column", "value": "state" }, { "id": 2, "type": "column", "value": "NY" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-COLUMN", "B-COLUMN", "O" ]
15,905
soccer_2016
bird:train.json:1930
What is the name of the youngest player?
SELECT Player_Name FROM Player ORDER BY DOB DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "youngest", "player", "?" ]
[ { "id": 1, "type": "column", "value": "player_name" }, { "id": 0, "type": "table", "value": "player" }, { "id": 2, "type": "column", "value": "dob" } ]
[ { "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" ]
15,906
book_publishing_company
bird:train.json:197
List all titles which have year to date sales higher than the average order by pubisher name.
SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.ytd_sales > ( SELECT AVG(ytd_sales) FROM titles )
[ "List", "all", "titles", "which", "have", "year", "to", "date", "sales", "higher", "than", "the", "average", "order", "by", "pubisher", "name", "." ]
[ { "id": 2, "type": "table", "value": "publishers" }, { "id": 3, "type": "column", "value": "ytd_sales" }, { "id": 1, "type": "table", "value": "titles" }, { "id": 4, "type": "column", "value": "pub_id" }, { "id": 0, "type": "column", "value": "title" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 15 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O" ]
15,907
hockey
bird:train.json:7777
In the year that the Montreal Canadiens had 24 penalty minutes in the Stanley Cup finals, how many wins did the team had in total?
SELECT T2.W FROM Teams AS T1 INNER JOIN TeamsSC AS T2 ON T1.tmID = T2.tmID AND T1.year = T2.year WHERE T1.name = 'Montreal Canadiens' AND T2.PIM = 24
[ "In", "the", "year", "that", "the", "Montreal", "Canadiens", "had", "24", "penalty", "minutes", "in", "the", "Stanley", "Cup", "finals", ",", "how", "many", "wins", "did", "the", "team", "had", "in", "total", "?" ]
[ { "id": 4, "type": "value", "value": "Montreal Canadiens" }, { "id": 2, "type": "table", "value": "teamssc" }, { "id": 1, "type": "table", "value": "teams" }, { "id": 3, "type": "column", "value": "name" }, { "id": 7, "type": "column", "value": "tmid" }, { "id": 8, "type": "column", "value": "year" }, { "id": 5, "type": "column", "value": "pim" }, { "id": 6, "type": "value", "value": "24" }, { "id": 0, "type": "column", "value": "w" } ]
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[ "O", "O", "B-COLUMN", "O", "O", "B-VALUE", "I-VALUE", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,908
car_road_race
bird:test.json:1353
Which teams won more than 1 race?
SELECT Winning_team FROM race GROUP BY Winning_team HAVING count(*) > 1
[ "Which", "teams", "won", "more", "than", "1", "race", "?" ]
[ { "id": 1, "type": "column", "value": "winning_team" }, { "id": 0, "type": "table", "value": "race" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
15,910
movielens
bird:train.json:2327
What's the ratio of gender in actors to actress in all the UK movies?
SELECT CAST(SUM(IIF(T3.a_gender = 'M', 1, 0)) AS REAL) / SUM(IIF(T3.a_gender = 'F', 1, 0)) FROM movies AS T1 INNER JOIN movies2actors AS T2 ON T1.movieid = T2.movieid INNER JOIN actors AS T3 ON T2.actorid = T3.actorid WHERE T1.country = 'UK'
[ "What", "'s", "the", "ratio", "of", "gender", "in", "actors", "to", "actress", "in", "all", "the", "UK", "movies", "?" ]
[ { "id": 4, "type": "table", "value": "movies2actors" }, { "id": 9, "type": "column", "value": "a_gender" }, { "id": 1, "type": "column", "value": "country" }, { "id": 5, "type": "column", "value": "actorid" }, { "id": 6, "type": "column", "value": "movieid" }, { "id": 0, "type": "table", "value": "actors" }, { "id": 3, "type": "table", "value": "movies" }, { "id": 2, "type": "value", "value": "UK" }, { "id": 7, "type": "value", "value": "1" }, { "id": 8, "type": "value", "value": "0" }, { "id": 10, "type": "value", "value": "F" }, { "id": 11, "type": "value", "value": "M" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [ 14 ] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 5 ] }, { "entity_id": 10, "token_idxs": [ 4 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "B-TABLE", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "B-TABLE", "O" ]
15,911
student_loan
bird:train.json:4389
List all students that have been absent for 6 months.
SELECT name FROM longest_absense_from_school WHERE `month` = 6
[ "List", "all", "students", "that", "have", "been", "absent", "for", "6", "months", "." ]
[ { "id": 0, "type": "table", "value": "longest_absense_from_school" }, { "id": 2, "type": "column", "value": "month" }, { "id": 1, "type": "column", "value": "name" }, { "id": 3, "type": "value", "value": "6" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 9 ] }, { "entity_id": 3, "token_idxs": [ 8 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-VALUE", "B-COLUMN", "O" ]
15,912
riding_club
spider:train_spider.json:1726
Please show the most common occupation of players.
SELECT Occupation FROM player GROUP BY Occupation ORDER BY COUNT(*) DESC LIMIT 1
[ "Please", "show", "the", "most", "common", "occupation", "of", "players", "." ]
[ { "id": 1, "type": "column", "value": "occupation" }, { "id": 0, "type": "table", "value": "player" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "O" ]
15,913
allergy_1
spider:train_spider.json:485
What is the last name of the youngest student?
SELECT LName FROM Student WHERE age = (SELECT min(age) FROM Student)
[ "What", "is", "the", "last", "name", "of", "the", "youngest", "student", "?" ]
[ { "id": 0, "type": "table", "value": "student" }, { "id": 1, "type": "column", "value": "lname" }, { "id": 2, "type": "column", "value": "age" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [ 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,914
book_publishing_company
bird:train.json:202
In which city is the store with the highest total sales quantity located?
SELECT T2.city FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id GROUP BY T2.city ORDER BY SUM(T1.qty) DESC LIMIT 1
[ "In", "which", "city", "is", "the", "store", "with", "the", "highest", "total", "sales", "quantity", "located", "?" ]
[ { "id": 3, "type": "column", "value": "stor_id" }, { "id": 2, "type": "table", "value": "stores" }, { "id": 1, "type": "table", "value": "sales" }, { "id": 0, "type": "column", "value": "city" }, { "id": 4, "type": "column", "value": "qty" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "B-TABLE", "O", "O", "O" ]
15,915
video_game
bird:test.json:1932
Count the number of games.
SELECT count(*) FROM game
[ "Count", "the", "number", "of", "games", "." ]
[ { "id": 0, "type": "table", "value": "game" } ]
[ { "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" ]
15,916
olympics
bird:train.json:4931
For Peter Kohnke, show the name of his/her region.
SELECT T1.region_name FROM noc_region AS T1 INNER JOIN person_region AS T2 ON T1.id = T2.region_id INNER JOIN person AS T3 ON T2.person_id = T3.id WHERE T3.full_name = 'Peter Kohnke'
[ "For", "Peter", "Kohnke", ",", "show", "the", "name", "of", "his", "/", "her", "region", "." ]
[ { "id": 5, "type": "table", "value": "person_region" }, { "id": 3, "type": "value", "value": "Peter Kohnke" }, { "id": 0, "type": "column", "value": "region_name" }, { "id": 4, "type": "table", "value": "noc_region" }, { "id": 2, "type": "column", "value": "full_name" }, { "id": 6, "type": "column", "value": "person_id" }, { "id": 8, "type": "column", "value": "region_id" }, { "id": 1, "type": "table", "value": "person" }, { "id": 7, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 1, 2 ] }, { "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": [ 11 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-VALUE", "I-VALUE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "B-COLUMN", "O" ]
15,917
language_corpus
bird:train.json:5791
What is the word ID for the second word for the biwords pair with most repetitions?
SELECT w2nd FROM biwords WHERE occurrences = ( SELECT MAX(occurrences) FROM biwords )
[ "What", "is", "the", "word", "ID", "for", "the", "second", "word", "for", "the", "biwords", "pair", "with", "most", "repetitions", "?" ]
[ { "id": 2, "type": "column", "value": "occurrences" }, { "id": 0, "type": "table", "value": "biwords" }, { "id": 1, "type": "column", "value": "w2nd" } ]
[ { "entity_id": 0, "token_idxs": [ 11 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
15,918
bbc_channels
bird:test.json:129
Find the number of programs for each channel. Return the name of each channel as well.
SELECT t1.name , count(*) FROM channel AS t1 JOIN program AS t2 ON t1.channel_id = t2.channel_id GROUP BY t1.channel_id
[ "Find", "the", "number", "of", "programs", "for", "each", "channel", ".", "Return", "the", "name", "of", "each", "channel", "as", "well", "." ]
[ { "id": 0, "type": "column", "value": "channel_id" }, { "id": 2, "type": "table", "value": "channel" }, { "id": 3, "type": "table", "value": "program" }, { "id": 1, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 11 ] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O" ]
15,919
sakila_1
spider:train_spider.json:2987
Count the number of items store 1 has in stock.
SELECT count(*) FROM inventory WHERE store_id = 1
[ "Count", "the", "number", "of", "items", "store", "1", "has", "in", "stock", "." ]
[ { "id": 0, "type": "table", "value": "inventory" }, { "id": 1, "type": "column", "value": "store_id" }, { "id": 2, "type": "value", "value": "1" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 5 ] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "B-VALUE", "O", "O", "O", "O" ]
15,920
works_cycles
bird:train.json:7392
Of the employees whose vacation hours are no more than 10, what is the age of the oldest employee at the time he/she was hired? Indicate his/her full name.
SELECT STRFTIME('%Y', T1.HireDate) - STRFTIME('%Y', T1.BirthDate), T2.FirstName, T2.MiddleName, T2.LastName FROM Employee AS T1 INNER JOIN Person AS T2 ON T1.BusinessEntityID = T2.BusinessEntityID WHERE T1.VacationHours <= 10 ORDER BY STRFTIME('%Y', T1.HireDate) - STRFTIME('%Y', T1.BirthDate) DESC LIMIT 1
[ "Of", "the", "employees", "whose", "vacation", "hours", "are", "no", "more", "than", "10", ",", "what", "is", "the", "age", "of", "the", "oldest", "employee", "at", "the", "time", "he", "/", "she", "was", "hired", "?", "Indicate", "his", "/", "her", "full", "name", "." ]
[ { "id": 7, "type": "column", "value": "businessentityid" }, { "id": 5, "type": "column", "value": "vacationhours" }, { "id": 1, "type": "column", "value": "middlename" }, { "id": 0, "type": "column", "value": "firstname" }, { "id": 10, "type": "column", "value": "birthdate" }, { "id": 2, "type": "column", "value": "lastname" }, { "id": 3, "type": "table", "value": "employee" }, { "id": 9, "type": "column", "value": "hiredate" }, { "id": 4, "type": "table", "value": "person" }, { "id": 6, "type": "value", "value": "10" }, { "id": 8, "type": "value", "value": "%Y" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 34 ] }, { "entity_id": 3, "token_idxs": [ 19 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 4, 5 ] }, { "entity_id": 6, "token_idxs": [ 10 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [ 27 ] }, { "entity_id": 10, "token_idxs": [ 29 ] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O" ]
15,921
airline
bird:train.json:5855
What are the codes of the airport found in Ankara, Turkey?
SELECT Code FROM Airports WHERE Description LIKE '%Ankara, Turkey%'
[ "What", "are", "the", "codes", "of", "the", "airport", "found", "in", "Ankara", ",", "Turkey", "?" ]
[ { "id": 3, "type": "value", "value": "%Ankara, Turkey%" }, { "id": 2, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "airports" }, { "id": 1, "type": "column", "value": "code" } ]
[ { "entity_id": 0, "token_idxs": [ 6 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 9, 10, 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-VALUE", "I-VALUE", "I-VALUE", "O" ]
15,923
icfp_1
spider:train_spider.json:2915
Which authors have last name "Ueno"? List their first names.
SELECT fname FROM authors WHERE lname = "Ueno"
[ "Which", "authors", "have", "last", "name", "\"", "Ueno", "\"", "?", "List", "their", "first", "names", "." ]
[ { "id": 0, "type": "table", "value": "authors" }, { "id": 1, "type": "column", "value": "fname" }, { "id": 2, "type": "column", "value": "lname" }, { "id": 3, "type": "column", "value": "Ueno" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "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", "B-TABLE", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "O" ]
15,924
music_1
spider:train_spider.json:3593
Return the names of songs for which format is mp3 and resolution is below 1000.
SELECT T2.song_name FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id WHERE T1.formats = "mp3" INTERSECT SELECT song_name FROM song WHERE resolution < 1000
[ "Return", "the", "names", "of", "songs", "for", "which", "format", "is", "mp3", "and", "resolution", "is", "below", "1000", "." ]
[ { "id": 5, "type": "column", "value": "resolution" }, { "id": 1, "type": "column", "value": "song_name" }, { "id": 3, "type": "column", "value": "formats" }, { "id": 2, "type": "table", "value": "files" }, { "id": 0, "type": "table", "value": "song" }, { "id": 6, "type": "value", "value": "1000" }, { "id": 7, "type": "column", "value": "f_id" }, { "id": 4, "type": "column", "value": "mp3" } ]
[ { "entity_id": 0, "token_idxs": [ 4 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 7 ] }, { "entity_id": 4, "token_idxs": [ 9 ] }, { "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, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_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", "B-COLUMN", "O", "B-COLUMN", "O", "O", "B-VALUE", "O" ]
15,925
legislator
bird:train.json:4737
Please list the official full names of all the current legislators who do not have an account on C-SPAN's video website.
SELECT official_full_name FROM current WHERE cspan_id IS NULL OR cspan_id = ''
[ "Please", "list", "the", "official", "full", "names", "of", "all", "the", "current", "legislators", "who", "do", "not", "have", "an", "account", "on", "C", "-", "SPAN", "'s", "video", "website", "." ]
[ { "id": 1, "type": "column", "value": "official_full_name" }, { "id": 2, "type": "column", "value": "cspan_id" }, { "id": 0, "type": "table", "value": "current" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 2, "token_idxs": [ 18, 19, 20 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O" ]
15,926
customers_and_addresses
spider:train_spider.json:6120
Tell me the number of orders with "Second time" as order detail.
SELECT count(*) FROM customer_orders WHERE order_details = "Second time"
[ "Tell", "me", "the", "number", "of", "orders", "with", "\"", "Second", "time", "\"", "as", "order", "detail", "." ]
[ { "id": 0, "type": "table", "value": "customer_orders" }, { "id": 1, "type": "column", "value": "order_details" }, { "id": 2, "type": "column", "value": "Second time" } ]
[ { "entity_id": 0, "token_idxs": [ 3, 4, 5 ] }, { "entity_id": 1, "token_idxs": [ 12, 13 ] }, { "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", "I-TABLE", "I-TABLE", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,927
car_retails
bird:train.json:1636
When were the products ordered by Cruz & Sons Co. on 2003-03-03 shipped?
SELECT t1.shippedDate FROM orders AS t1 INNER JOIN customers AS t2 ON t1.customerNumber = t2.customerNumber WHERE t2.customerName = 'Cruz & Sons Co.' AND t1.orderDate = '2003-03-03'
[ "When", "were", "the", "products", "ordered", "by", "Cruz", "&", "Sons", "Co.", "on", "2003", "-", "03", "-", "03", "shipped", "?" ]
[ { "id": 5, "type": "value", "value": "Cruz & Sons Co." }, { "id": 3, "type": "column", "value": "customernumber" }, { "id": 4, "type": "column", "value": "customername" }, { "id": 0, "type": "column", "value": "shippeddate" }, { "id": 7, "type": "value", "value": "2003-03-03" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 6, "type": "column", "value": "orderdate" }, { "id": 1, "type": "table", "value": "orders" } ]
[ { "entity_id": 0, "token_idxs": [ 16 ] }, { "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": [ 6, 7, 8, 9 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [ 11, 12, 13, 14, 15 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "B-COLUMN", "O" ]
15,928
customers_card_transactions
spider:train_spider.json:687
Show distinct first and last names for all customers with an account.
SELECT DISTINCT T1.customer_first_name , T1.customer_last_name FROM Customers AS T1 JOIN Accounts AS T2 ON T1.customer_id = T2.customer_id
[ "Show", "distinct", "first", "and", "last", "names", "for", "all", "customers", "with", "an", "account", "." ]
[ { "id": 0, "type": "column", "value": "customer_first_name" }, { "id": 1, "type": "column", "value": "customer_last_name" }, { "id": 4, "type": "column", "value": "customer_id" }, { "id": 2, "type": "table", "value": "customers" }, { "id": 3, "type": "table", "value": "accounts" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 11 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O" ]
15,929
driving_school
spider:train_spider.json:6713
What is the first name of all employees who do not give any lessons?
SELECT first_name FROM Staff EXCEPT SELECT T2.first_name FROM Lessons AS T1 JOIN Staff AS T2 ON T1.staff_id = T2.staff_id
[ "What", "is", "the", "first", "name", "of", "all", "employees", "who", "do", "not", "give", "any", "lessons", "?" ]
[ { "id": 1, "type": "column", "value": "first_name" }, { "id": 3, "type": "column", "value": "staff_id" }, { "id": 2, "type": "table", "value": "lessons" }, { "id": 0, "type": "table", "value": "staff" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 3, 4 ] }, { "entity_id": 2, "token_idxs": [ 13 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O" ]
15,930
retail_world
bird:train.json:6585
Indicate category name of soft drinks, coffees, teas, beers, and ales in description list.
SELECT CategoryName FROM Categories WHERE Description = 'Soft drinks, coffees, teas, beers, and ales'
[ "Indicate", "category", "name", "of", "soft", "drinks", ",", "coffees", ",", "teas", ",", "beers", ",", "and", "ales", "in", "description", "list", "." ]
[ { "id": 3, "type": "value", "value": "Soft drinks, coffees, teas, beers, and ales" }, { "id": 1, "type": "column", "value": "categoryname" }, { "id": 2, "type": "column", "value": "description" }, { "id": 0, "type": "table", "value": "categories" } ]
[ { "entity_id": 0, "token_idxs": [ 1 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [ 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "I-VALUE", "O", "B-COLUMN", "O", "O" ]
15,931
customer_deliveries
spider:train_spider.json:2846
Show the details of all trucks in the order of their license number.
SELECT truck_details FROM trucks ORDER BY truck_licence_number
[ "Show", "the", "details", "of", "all", "trucks", "in", "the", "order", "of", "their", "license", "number", "." ]
[ { "id": 2, "type": "column", "value": "truck_licence_number" }, { "id": 1, "type": "column", "value": "truck_details" }, { "id": 0, "type": "table", "value": "trucks" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 11, 12 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O" ]
15,932
customers_and_orders
bird:test.json:275
Show all payment method codes and the number of customers in each code.
SELECT payment_method_code , count(*) FROM Customers GROUP BY payment_method_code
[ "Show", "all", "payment", "method", "codes", "and", "the", "number", "of", "customers", "in", "each", "code", "." ]
[ { "id": 1, "type": "column", "value": "payment_method_code" }, { "id": 0, "type": "table", "value": "customers" } ]
[ { "entity_id": 0, "token_idxs": [ 9 ] }, { "entity_id": 1, "token_idxs": [ 2, 3, 4 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "I-COLUMN", "I-COLUMN", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O" ]
15,933
donor
bird:train.json:3304
What is the total number of students impacted by the projects with a donation from a donor with zip code "22205"?
SELECT SUM(T2.students_reached) FROM donations AS T1 INNER JOIN projects AS T2 ON T1.projectid = T2.projectid WHERE T1.donor_zip = 22205
[ "What", "is", "the", "total", "number", "of", "students", "impacted", "by", "the", "projects", "with", "a", "donation", "from", "a", "donor", "with", "zip", "code", "\"", "22205", "\"", "?" ]
[ { "id": 4, "type": "column", "value": "students_reached" }, { "id": 0, "type": "table", "value": "donations" }, { "id": 2, "type": "column", "value": "donor_zip" }, { "id": 5, "type": "column", "value": "projectid" }, { "id": 1, "type": "table", "value": "projects" }, { "id": 3, "type": "value", "value": "22205" } ]
[ { "entity_id": 0, "token_idxs": [ 13 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [ 16 ] }, { "entity_id": 3, "token_idxs": [ 21 ] }, { "entity_id": 4, "token_idxs": [ 6, 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", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O" ]
15,935
university
bird:train.json:7994
What is the name of the university that had the highest number of international students for 6 consecutive years?
SELECT T2.university_name FROM university_year AS T1 INNER JOIN university AS T2 ON T1.university_id = T2.id ORDER BY T1.pct_international_students DESC LIMIT 1
[ "What", "is", "the", "name", "of", "the", "university", "that", "had", "the", "highest", "number", "of", "international", "students", "for", "6", "consecutive", "years", "?" ]
[ { "id": 3, "type": "column", "value": "pct_international_students" }, { "id": 0, "type": "column", "value": "university_name" }, { "id": 1, "type": "table", "value": "university_year" }, { "id": 4, "type": "column", "value": "university_id" }, { "id": 2, "type": "table", "value": "university" }, { "id": 5, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 6 ] }, { "entity_id": 3, "token_idxs": [ 13, 14 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "O", "O" ]
15,936
soccer_2016
bird:train.json:1998
Among the matches in 2013, what is the percentage of winning of the team "Mumbai Indians"?
SELECT CAST(SUM(CASE WHEN T2.Match_Winner = 7 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.Match_Winner) FROM Team AS T1 INNER JOIN Match AS T2 ON T1.Team_Id = T2.Match_Winner WHERE T2.Match_Date LIKE '2013%'
[ "Among", "the", "matches", "in", "2013", ",", "what", "is", "the", "percentage", "of", "winning", "of", "the", "team", "\"", "Mumbai", "Indians", "\"", "?" ]
[ { "id": 5, "type": "column", "value": "match_winner" }, { "id": 2, "type": "column", "value": "match_date" }, { "id": 4, "type": "column", "value": "team_id" }, { "id": 1, "type": "table", "value": "match" }, { "id": 3, "type": "value", "value": "2013%" }, { "id": 0, "type": "table", "value": "team" }, { "id": 6, "type": "value", "value": "100" }, { "id": 7, "type": "value", "value": "0" }, { "id": 8, "type": "value", "value": "1" }, { "id": 9, "type": "value", "value": "7" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 4 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [ 3 ] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "O", "O", "O", "O" ]
15,937
codebase_comments
bird:train.json:663
What is the task of method number 2?
SELECT SUBSTR(SUBSTR(Name, INSTR(Name, '.') + 1), 1, INSTR(SUBSTR(Name, INSTR(Name, '.') + 1), '.') - 1) task FROM Method WHERE Id = 2
[ "What", "is", "the", "task", "of", "method", "number", "2", "?" ]
[ { "id": 0, "type": "table", "value": "method" }, { "id": 4, "type": "column", "value": "name" }, { "id": 1, "type": "column", "value": "id" }, { "id": 2, "type": "value", "value": "2" }, { "id": 3, "type": "value", "value": "1" }, { "id": 5, "type": "value", "value": "." } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 7 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 6 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-TABLE", "B-COLUMN", "B-VALUE", "O" ]
15,938
inn_1
spider:train_spider.json:2583
Return the name, rate, check in and check out date for the room with the highest rate.
SELECT T2.roomName , T1.Rate , T1.CheckIn , T1.CheckOut FROM Reservations AS T1 JOIN Rooms AS T2 ON T1.Room = T2.RoomId GROUP BY T1.Room ORDER BY T1.Rate DESC LIMIT 1;
[ "Return", "the", "name", ",", "rate", ",", "check", "in", "and", "check", "out", "date", "for", "the", "room", "with", "the", "highest", "rate", "." ]
[ { "id": 5, "type": "table", "value": "reservations" }, { "id": 1, "type": "column", "value": "roomname" }, { "id": 4, "type": "column", "value": "checkout" }, { "id": 3, "type": "column", "value": "checkin" }, { "id": 7, "type": "column", "value": "roomid" }, { "id": 6, "type": "table", "value": "rooms" }, { "id": 0, "type": "column", "value": "room" }, { "id": 2, "type": "column", "value": "rate" } ]
[ { "entity_id": 0, "token_idxs": [ 14 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 4 ] }, { "entity_id": 3, "token_idxs": [ 6, 7 ] }, { "entity_id": 4, "token_idxs": [ 9, 10 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O" ]
15,939
college_completion
bird:train.json:3748
In Yale University, what is the average number of Black students per year who were bachelor's/equivalent-seeking cohort at 4-year institutions between 2002 to 2005?
SELECT AVG(T2.grad_cohort) FROM institution_details AS T1 INNER JOIN institution_grads AS T2 ON T2.unitid = T1.unitid WHERE T1.chronname = 'Yale University' AND T2.year BETWEEN 2002 AND 2005 AND T2.race = 'B' AND T2.cohort = '4y bach'
[ "In", "Yale", "University", ",", "what", "is", "the", "average", "number", "of", "Black", "students", "per", "year", "who", "were", "bachelor's", "/", "equivalent", "-", "seeking", "cohort", "at", "4", "-", "year", "institutions", "between", "2002", "to", "2005", "?" ]
[ { "id": 0, "type": "table", "value": "institution_details" }, { "id": 1, "type": "table", "value": "institution_grads" }, { "id": 5, "type": "value", "value": "Yale University" }, { "id": 2, "type": "column", "value": "grad_cohort" }, { "id": 4, "type": "column", "value": "chronname" }, { "id": 12, "type": "value", "value": "4y bach" }, { "id": 3, "type": "column", "value": "unitid" }, { "id": 11, "type": "column", "value": "cohort" }, { "id": 6, "type": "column", "value": "year" }, { "id": 7, "type": "value", "value": "2002" }, { "id": 8, "type": "value", "value": "2005" }, { "id": 9, "type": "column", "value": "race" }, { "id": 10, "type": "value", "value": "B" } ]
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[ "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-COLUMN", "B-TABLE", "O", "B-VALUE", "O", "B-VALUE", "O" ]
15,940
menu
bird:train.json:5530
Tally the dishes that have appeared on the menu for more than 100 years.
SELECT T1.name FROM Dish AS T1 INNER JOIN MenuItem AS T2 ON T1.id = T2.dish_id WHERE T1.last_appeared - T1.first_appeared > 100
[ "Tally", "the", "dishes", "that", "have", "appeared", "on", "the", "menu", "for", "more", "than", "100", "years", "." ]
[ { "id": 7, "type": "column", "value": "first_appeared" }, { "id": 6, "type": "column", "value": "last_appeared" }, { "id": 2, "type": "table", "value": "menuitem" }, { "id": 5, "type": "column", "value": "dish_id" }, { "id": 0, "type": "column", "value": "name" }, { "id": 1, "type": "table", "value": "dish" }, { "id": 3, "type": "value", "value": "100" }, { "id": 4, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 8 ] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 5 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "O", "O", "B-VALUE", "O", "O" ]
15,941
image_and_language
bird:train.json:7526
Identify the border's coordinates on the X and Y axes that enclose a folk in image no. 6.
SELECT T1.X, T1.Y FROM IMG_OBJ AS T1 INNER JOIN OBJ_CLASSES AS T2 ON T1.OBJ_CLASS_ID = T2.OBJ_CLASS_ID WHERE T1.IMG_ID = 6 AND T2.OBJ_CLASS = 'folk'
[ "Identify", "the", "border", "'s", "coordinates", "on", "the", "X", "and", "Y", "axes", "that", "enclose", "a", "folk", "in", "image", "no", ".", "6", "." ]
[ { "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": "folk" }, { "id": 0, "type": "column", "value": "x" }, { "id": 1, "type": "column", "value": "y" }, { "id": 6, "type": "value", "value": "6" } ]
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[ "O", "O", "O", "O", "O", "O", "O", "B-COLUMN", "O", "B-COLUMN", "O", "O", "O", "O", "B-VALUE", "O", "O", "O", "O", "B-VALUE", "O" ]
15,942
california_schools
bird:dev.json:46
Which state special schools have the highest number of enrollees from grades 1 through 12?
SELECT T2.School FROM frpm AS T1 INNER JOIN schools AS T2 ON T1.CDSCode = T2.CDSCode WHERE T2.DOC = 31 ORDER BY T1.`Enrollment (K-12)` DESC LIMIT 1
[ "Which", "state", "special", "schools", "have", "the", "highest", "number", "of", "enrollees", "from", "grades", "1", "through", "12", "?" ]
[ { "id": 5, "type": "column", "value": "Enrollment (K-12)" }, { "id": 2, "type": "table", "value": "schools" }, { "id": 6, "type": "column", "value": "cdscode" }, { "id": 0, "type": "column", "value": "school" }, { "id": 1, "type": "table", "value": "frpm" }, { "id": 3, "type": "column", "value": "doc" }, { "id": 4, "type": "value", "value": "31" } ]
[ { "entity_id": 0, "token_idxs": [ 3 ] }, { "entity_id": 1, "token_idxs": [ 10 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [ 12 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "O", "O", "B-TABLE", "O", "B-VALUE", "O", "O", "O" ]
15,944
law_episode
bird:train.json:1306
In which episodes was Anthony Azzara not credited?
SELECT T1.title FROM Episode AS T1 INNER JOIN Credit AS T2 ON T1.episode_id = T2.episode_id INNER JOIN Person AS T3 ON T3.person_id = T2.person_id WHERE T2.credited = 'false' AND T3.name = 'Anthony Azzara'
[ "In", "which", "episodes", "was", "Anthony", "Azzara", "not", "credited", "?" ]
[ { "id": 8, "type": "value", "value": "Anthony Azzara" }, { "id": 9, "type": "column", "value": "episode_id" }, { "id": 4, "type": "column", "value": "person_id" }, { "id": 5, "type": "column", "value": "credited" }, { "id": 2, "type": "table", "value": "episode" }, { "id": 1, "type": "table", "value": "person" }, { "id": 3, "type": "table", "value": "credit" }, { "id": 0, "type": "column", "value": "title" }, { "id": 6, "type": "value", "value": "false" }, { "id": 7, "type": "column", "value": "name" } ]
[ { "entity_id": 0, "token_idxs": [] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 2 ] }, { "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": [ 4, 5 ] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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-VALUE", "I-VALUE", "O", "B-TABLE", "O" ]
15,945
allergy_1
spider:train_spider.json:532
What are the distinct first names and cities of the students who have allergy either to milk or to cat?
SELECT DISTINCT T1.fname , T1.city_code FROM Student AS T1 JOIN Has_Allergy AS T2 ON T1.stuid = T2.stuid WHERE T2.Allergy = "Milk" OR T2.Allergy = "Cat"
[ "What", "are", "the", "distinct", "first", "names", "and", "cities", "of", "the", "students", "who", "have", "allergy", "either", "to", "milk", "or", "to", "cat", "?" ]
[ { "id": 3, "type": "table", "value": "has_allergy" }, { "id": 1, "type": "column", "value": "city_code" }, { "id": 2, "type": "table", "value": "student" }, { "id": 5, "type": "column", "value": "allergy" }, { "id": 0, "type": "column", "value": "fname" }, { "id": 4, "type": "column", "value": "stuid" }, { "id": 6, "type": "column", "value": "Milk" }, { "id": 7, "type": "column", "value": "Cat" } ]
[ { "entity_id": 0, "token_idxs": [ 5 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 12 ] }, { "entity_id": 4, "token_idxs": [ 10 ] }, { "entity_id": 5, "token_idxs": [ 13 ] }, { "entity_id": 6, "token_idxs": [ 16 ] }, { "entity_id": 7, "token_idxs": [ 19 ] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "O", "O", "B-COLUMN", "O", "O", "B-COLUMN", "O" ]
15,946
department_store
spider:train_spider.json:4745
For each product type, return the maximum and minimum price.
SELECT product_type_code , max(product_price) , min(product_price) FROM products GROUP BY product_type_code
[ "For", "each", "product", "type", ",", "return", "the", "maximum", "and", "minimum", "price", "." ]
[ { "id": 1, "type": "column", "value": "product_type_code" }, { "id": 2, "type": "column", "value": "product_price" }, { "id": 0, "type": "table", "value": "products" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 3 ] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "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" ]
15,947
superhero
bird:dev.json:802
Who is the tallest superhero?
SELECT superhero_name FROM superhero ORDER BY height_cm DESC LIMIT 1
[ "Who", "is", "the", "tallest", "superhero", "?" ]
[ { "id": 1, "type": "column", "value": "superhero_name" }, { "id": 0, "type": "table", "value": "superhero" }, { "id": 2, "type": "column", "value": "height_cm" } ]
[ { "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" ]
15,948
e_commerce
bird:test.json:85
What are the usernames and passwords of all customers whose phone number starts with '+12'?
SELECT login_name , login_password FROM Customers WHERE phone_number LIKE '+12%'
[ "What", "are", "the", "usernames", "and", "passwords", "of", "all", "customers", "whose", "phone", "number", "starts", "with", "'", "+12", "'", "?" ]
[ { "id": 2, "type": "column", "value": "login_password" }, { "id": 3, "type": "column", "value": "phone_number" }, { "id": 1, "type": "column", "value": "login_name" }, { "id": 0, "type": "table", "value": "customers" }, { "id": 4, "type": "value", "value": "+12%" } ]
[ { "entity_id": 0, "token_idxs": [ 8 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [ 5 ] }, { "entity_id": 3, "token_idxs": [ 10, 11 ] }, { "entity_id": 4, "token_idxs": [ 15 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "O", "O", "B-COLUMN", "O", "O", "B-TABLE", "O", "B-COLUMN", "I-COLUMN", "O", "O", "O", "B-VALUE", "O", "O" ]
15,949
superhero
bird:dev.json:745
Give the publisher ID of Star Trek.
SELECT id FROM publisher WHERE publisher_name = 'Star Trek'
[ "Give", "the", "publisher", "ID", "of", "Star", "Trek", "." ]
[ { "id": 2, "type": "column", "value": "publisher_name" }, { "id": 0, "type": "table", "value": "publisher" }, { "id": 3, "type": "value", "value": "Star Trek" }, { "id": 1, "type": "column", "value": "id" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [ 5, 6 ] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "B-COLUMN", "O", "B-VALUE", "I-VALUE", "O" ]
15,950
music_2
spider:train_spider.json:5195
What is the label with the most albums?
SELECT label FROM albums GROUP BY label ORDER BY count(*) DESC LIMIT 1
[ "What", "is", "the", "label", "with", "the", "most", "albums", "?" ]
[ { "id": 0, "type": "table", "value": "albums" }, { "id": 1, "type": "column", "value": "label" } ]
[ { "entity_id": 0, "token_idxs": [ 7 ] }, { "entity_id": 1, "token_idxs": [ 3 ] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "O", "B-COLUMN", "O", "O", "O", "B-TABLE", "O" ]
15,951
authors
bird:train.json:3627
For the paper which was presented by "Zvezdan Protić", was it preprinted?
SELECT CASE WHEN T1.Year = 0 THEN 'TRUE' ELSE 'FALSE' END FROM Paper AS T1 INNER JOIN PaperAuthor AS T2 ON T1.Id = T2.PaperId WHERE T2.Name = 'Zvezdan Protić' AND T1.ConferenceId = 0 AND T1.JournalId = 0
[ "For", "the", "paper", "which", "was", "presented", "by", "\"", "Zvezdan", "Protić", "\"", ",", "was", "it", "preprinted", "?" ]
[ { "id": 6, "type": "value", "value": "Zvezdan Protić" }, { "id": 7, "type": "column", "value": "conferenceid" }, { "id": 1, "type": "table", "value": "paperauthor" }, { "id": 9, "type": "column", "value": "journalid" }, { "id": 4, "type": "column", "value": "paperid" }, { "id": 0, "type": "table", "value": "paper" }, { "id": 2, "type": "value", "value": "FALSE" }, { "id": 5, "type": "column", "value": "name" }, { "id": 10, "type": "value", "value": "TRUE" }, { "id": 11, "type": "column", "value": "year" }, { "id": 3, "type": "column", "value": "id" }, { "id": 8, "type": "value", "value": "0" } ]
[ { "entity_id": 0, "token_idxs": [ 2 ] }, { "entity_id": 1, "token_idxs": [] }, { "entity_id": 2, "token_idxs": [] }, { "entity_id": 3, "token_idxs": [] }, { "entity_id": 4, "token_idxs": [] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [ 8, 9 ] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-TABLE", "O", "O", "O", "O", "O", "B-VALUE", "I-VALUE", "O", "O", "O", "O", "O", "O" ]
15,952
sakila_1
spider:train_spider.json:2969
Return the title and inventory id of the film that is rented most often.
SELECT T1.title , T2.inventory_id FROM film AS T1 JOIN inventory AS T2 ON T1.film_id = T2.film_id JOIN rental AS T3 ON T2.inventory_id = T3.inventory_id GROUP BY T2.inventory_id ORDER BY count(*) DESC LIMIT 1
[ "Return", "the", "title", "and", "inventory", "i", "d", "of", "the", "film", "that", "is", "rented", "most", "often", "." ]
[ { "id": 0, "type": "column", "value": "inventory_id" }, { "id": 4, "type": "table", "value": "inventory" }, { "id": 5, "type": "column", "value": "film_id" }, { "id": 2, "type": "table", "value": "rental" }, { "id": 1, "type": "column", "value": "title" }, { "id": 3, "type": "table", "value": "film" } ]
[ { "entity_id": 0, "token_idxs": [ 5, 6 ] }, { "entity_id": 1, "token_idxs": [ 2 ] }, { "entity_id": 2, "token_idxs": [ 12 ] }, { "entity_id": 3, "token_idxs": [ 9 ] }, { "entity_id": 4, "token_idxs": [ 4 ] }, { "entity_id": 5, "token_idxs": [] }, { "entity_id": 6, "token_idxs": [] }, { "entity_id": 7, "token_idxs": [] }, { "entity_id": 8, "token_idxs": [] }, { "entity_id": 9, "token_idxs": [] }, { "entity_id": 10, "token_idxs": [] }, { "entity_id": 11, "token_idxs": [] }, { "entity_id": 12, "token_idxs": [] }, { "entity_id": 13, "token_idxs": [] }, { "entity_id": 14, "token_idxs": [] }, { "entity_id": 15, "token_idxs": [] }, { "entity_id": 16, "token_idxs": [] }, { "entity_id": 17, "token_idxs": [] }, { "entity_id": 18, "token_idxs": [] }, { "entity_id": 19, "token_idxs": [] } ]
[ "O", "O", "B-COLUMN", "O", "B-TABLE", "B-COLUMN", "I-COLUMN", "O", "O", "B-TABLE", "O", "O", "B-TABLE", "O", "O", "O" ]